Notes for Reading Geochemical Fingerprints
Go over syllabus
structure of class:
introduction of some applications so have road-map of how geochemistry used,
Processes of differentiation,
Statistical methods
Analytical methods
Applications
2-times through approach: go through processes and analytical methods, then see them
again as we go through applications. Text book picks up mainly in the applications.
puzzle solving homework assignments and some labs
These to be done mostly outside of class. Will set up times for lab to be open in evening.
2 exams, First will cover processes and analytical techniques, 2nd will cover applications.
Report to class on a published paper using geochemistry to address some problem. about
20 minutes each (for 10 students).
Mostly Archaeological examples….some environmental or geological.
feel free to correct my pronunciation!
Deemphasize details of chemical processes, chemical equilibrium.
But cover it some. There is not single or simple procedure for applying geochemical
methods to archaeological finds. Have to be creative and innovative. If you don’t
understand how geochemical differentiation works, then can’t be creative or innovative in
applying it.
Colossi of Memnon: (use computer graphic or overhead, showing N. and S. Colossi)
(goal: start thinking about uncertainty in data and what it means, how a graph helps
understand that uncertainty and whether data distinguish two materials as being different
or the same)
built 3200 years ago, 18th Egyptian dynast, memorial for Amenhotep III, set up on West
bank of Nile.
Invading Assyrians in the 7th century BC, and Persian in 6th and 5th centuries, tried to
destroy (Assyrians in particular liked to obliterate people and culture to minimize future
revolt).
Built fires to try to crack stone. But stone made of Quartzite…Monomineralic, and
simple compositional structure. (Quartz=SiO2) Also the structure of quartz is isometric,
meaning its structure is the same in all directions. It expands more evenly when gets hot.
Does not crack. Also, coefficient of expansion not real high to begin with. Efforts failed.
Earthquake succeeded in 27BC, Northern of the 2 Colossi lost upper half of body.
Repaired by Roman emperor Septimius Severus about 200 years later (according to
Greek Historian Strabo)
Did repair use Quartzite from same area, or had area of active quarrying changed?
Where was the quarry?
Show computer graphic or overhead of map from Bowman et al. 1984.
Major quarries north and south of area of Colossi. (Gebel el Ahmar, Silsila, Aswan)
But quartzite made mainly of quartz. Can’t always tell apart. Sometimes trace
constituents show up as color differences, or may be differences in minor minerals. But
Trace chemistry a good way to tell (explain trace chemistry).
Data table 1 (major elements). (hand out) Quarries at Silsila and Silwa strikingly
different even in major element chemistry (show with CaCO3, and SiO2)
Rear block looks like Aswan by SiO2 analysis. But the problem is that SiO2 could not be
measured by their analytical technique! It was calculated by subtracting everything else
from 100%. Not very credible.
Have them look at other elements and try to decide which quarry each came from (Rear
block added by Romans, Main block part of original). explain “<” symbol and
significance.
(prompt to compare rear and main…are they the same? how can we tell? go through
consideration of +/- uncertainty. Ask specific elements, MnO, TiO2?
Data table 2 (trace elements) (hand out)
Can look at other elements. Decreases the chance that there is a chance correlation
between rocks that weren’t from the same site! All elements need to match
up…otherwise might be fluke correlation.
Have them look at Th. Could you identify the source on the basis of Th? Why or why
not?
No: Th varies too much within sources and both parts of pedestals are within range of
each source.
Show graph of Eu vs Fe. Useful to show with two elements that distinguish. More
reliable to use all elements of course. But human brains can’t deal with it as easily and
hard to illustrate on a flat piece of paper by any means other than statistical reports. Nice
to have a graph. Randy Korotev, if you can’t see it in a graph, all the statistical tests in
the world aren’t going to help you.
graph gives view of scatter. important in assessing variation and whether one can really
tell which group something belongs to.
Eu probably in feldspar-so mineralogical analysis could have yielded similar results. But,
less data: 1 variable, mineral proportions, less reliable than many compositional
variables.
bowman et al, 1984, archaeometry v26, 218-229.
Review: Geochemistry as a tool,
1) look at processes because need to understand them in order to know how to use.
2) Look at statistics (mostly conceptual) because otherwise don’t know what
geochemistry is telling you. (Consider how data acquired, # samples, uncertainty)
3) Examine processes and technologies used in past (glass, ceramics, metals, etc),
because can’t understand how to use geochemistry unless understand what it’s being
applied to.
4) Look at examples of application as practice in using tool and to show some of ways it
can be used.
Summary of ideas from Colossi of Memnon example:
Define uncertainty, precision, accuracy
Each quarry has a unique geochemical signature, even if rock type is the same
To use geochemistry, you have to consider not only the measured concentration
of an element, but how much natural variation and analytical uncertainty
there is in the measurements
More measurements increases confidence.
Considering more elements yields a more believable result because it decreases the
likelihood of a chance correlation. More measurements also increases
confidence.
Graphing the geochemical data can make it easier for the human mind to visualize
whether the two compositions are the same or different within the chemical
variation.
Mineralogy affects material behavior as well as chemistry
Another note: authenticity of an artifact can be tested through geochemistry. The
repairs to the N. Colossus were readily distinguishable from the original on the
basis of geochemistry.
Activity: Write down, as though trying to convince someone else, where the blocks
of the northern Colossus came from and why you believe it. Trade your
paragraph with someone else who will critique it.
Pre-industrial Pb pollution:
Introduce idea that one needs to know background level before human pollution
contribution can be determined.
background: that which would exist without human input
historical: that concentration which has existed historically.
Lake stratigraphy, provides a means to establish historical pollution, background
pollution, and the effects of human activity over an extended period of time.
When might you expect Pb levels in lake sediments to increase and why?
How is Pb getting into the lake sediments (source: direct deposit from air, washed into
lake from air deposit on land, washed into lake from human caused land sources)?
Computer image or overhead of Europe showing Sweden: look at lake sediments in
Sweden from ~Bronze Age to Present.
Influenced by any local mining, but more significantly by any air borne material
generated by the developing metal industry.
Show Computer graphic or overhead of Graphical representation of sediment core Pb
deposition data from 3 lakes and fly ash data from one.
Analysis: industrial revolution…where is it? Blip at very right, last 150 years or so.
shows up in SCP (spheroidal carbonaceous particles…..fly ash characteristic of oil and
coal burning).
But increase in Pb before this. Draw on board, showing start of rise around 500BC, peak
around 0 BC, dip, then increase into present age.
Renberg et al., 1994 Nature 368, 323-326.
Show computer graphic or overhead of onset of metallurgical techniques (cupellation is a
process where metal is purified by oxidation at high temperature with oxidizable metals
dissolving into a containing cupel), coinage, Roman Pb mines, etc.
Can establish the present human contribution of Pb to lake sediment
This reflects Pb in atmosphere
Can establish past human contribution of Pb to lake sediment
This can be correlated to coin manufacture and mining of Pb by Roman Empire
Other factors to consider: weather patterns, where Pb brought from
might look for effect of going to unleaded gasoline
Summary of ideas from Pre-industrial Pb input into lake sediments:
Stratigraphic variations in chemistry, such as in lake sediments, can reveal past
changes in pollutants in the atmosphere.
This can help establish the present human input of pollutants to the atmosphere
It can identify or confirm past mining and industrial activity.
Key idea is often the correlation of chemical trends with time with known activities.
Greek Attic Red-on-black pottery:
530BC a new pottery technique was invented in Athens. Involved a striking red-on-black
color.
Even into the 1940’s it was not obvious how it was done.
Problem was, chemical analysis revealed that there was no difference, chemically,
between the red and black areas. Not simply painted on. No pigments. Not a glaze (a
material of different composition, melts at a lower temperature producing a glassy
coating).
How was it done?
Understanding the progress of technological development, and how technological skills
were maintained, applied, and spread to other areas of interest. Aided by understanding
what was done….relationships with other, similar processes help us understand the
development of the society and its technologies.
Various metal oxides can act as pigments.
FeO = dark
Fe2O3 = red
Fe3O4 = black.
MnO = black
Go back to an earlier technology in the same Greek tradition, invented in Corinth about
700BC.
(Show overhead of black on red, ca. 560 BC)
Black on red. Easier technique. But also no difference in composition.
But the black areas were finer-grained, smaller particles, under a microscope.
Before the pot was fired, a finer-grained slurry was painted onto the pot as a slip
(slip is a wetter,thinner slurry added to a ceramic before firing, often to provide a
smoother finish)
The pot was fired. Iron present in the clay of the pot converts to Fe2O3 when heated in
the presence of oxygen.
2FeO(dark) + ½ O2 = Fe2O3 (red)
The fine grained slip prevents oxygen from getting to the slip-painted areas. The rest of
the pot turns red, voila! Black on red!
In the 1940’s realized that the Red on Black was a similar, but more complex process.
Observed under microscope that Red areas were rough and porous,……black areas were
fine grained, smooth, not porous.
Process:
1) select finer particle slip, add wood ash for alkali (flux = lowers melting T slightly),
paint areas that will be black (areas in between the figures)
2) fire in oxidizing atm at 850C. entire pot red.
3) Add green and wet wood to fire, produces CO, reducing atmosphere. Increase
Temperature…….pot turns black as Fe is reduced to magnetite…. slip melts and seals
ceramic.
4) Temperature decreased slightly, dry wood replaces wet and the conditions are
returned to oxidizing. non-slip portions of the pot oxidize to red, but the vitreous slip has
sealed other parts of the pot and oxygen cannot reach the Fe to oxidize it….stays black.
Pottery in the Attic style (like these) in the Metropolitan Museum of Art were examined
once this technique was understood. The colors in these pots were found to be a result of
different pigments used in the pots. Thus, they were shown to be forgeries.
Summary of Greek Attic Red-on-Black Pottery:
Texture as well as chemistry can yield information about what manufacturing process
was used (pottery, also metals)
Understanding chemistry of color and be valuable in trying to understand how something
was made.
Understanding how something was made provides insight into cultural and technological
change.
Geochemistry Puzzle Assignment #1:
Atmospheric Mercury deposition in Minnesota Lakes in modern times.
Be careful, complete, and neat in your answers. I don't want un-interpretable scribbles
with numbers strewn all over the place, nor do I want hand-drawn graphs on notebook
paper. Be professional!
This assignment is intended to exercise your ability to graph and analyze data. A large
part of applying geochemical data is the creative ability to conceive of ways to graph or
manipulate chemical numbers to help you understand what it really tells you about the
problem you are addressing.
This problem is not intended to be a simple calculation, but rather it is intended to be a
puzzle where the real goal is to figure out what calculation to do, what graph to draw, or
how to interpret either calculations or graphs. Key things to remember are that mercury
is added both directly to the lake surface (surface area on the table below) from the air,
and also runs into the lake from the associated drainage basin (catchment area in the table
below).
This problem is adapted from the research of Swain et al., 1992 Increasing rates of
Atmospheric Mercury deposition in midcontinental North America, Science v257, 784787.
1) Considering the data provided, how has Hg deposition in Minnesota lakes changed
with time? (hint: look at time vs Hg accumulation graphs)
2) How does the accumulation rate change with lake surface area and catchment area
(catchment area is the area of land that drains into the lake)?
(hint: look at the data table and consider accumulation rates, lake areas, and catchment
areas…are simple relationships seen between accumulation rate and either lake area or
catchment area?)
3) Consider Thrush lake and Kjostad lake. Why doesn’t the deposition rate increase by
25x when the lake size increases by 25x? (hint: consider the units in which deposition
rate is reported)
4) How much Hg is being deposited directly into the water from the atmosphere today?
(report in micrograms per square meter per year- units is an important hint in figuring out
how to figure out the answer). hint: the way to think of this problem is to imagine a lake
that has no catchment area at all (catchment area excludes the lake area), or catchment
area/lake area = 0. You can make a graph showing accumulation rate (flux) vs
catchment/lake area and project to 0.
5) How much Hg was being deposited directly into the water from the atmosphere in
preindustrial times? hint: use the same hint as question 4.
6) Assuming that this same amount of Hg is being deposited on each square meter of
land in the catchment areas (as is being deposited on water in question 4), how much of
the Hg deposited on land washes off into the lake? hint: pick a lake, say Meander.
Subtract the amount of Hg deposited directly into the lake from the total accumulation.
The remainder must be the amount washed in from the catchment. How much is this per
square meter compared to the deposition per square meter? Does most Hg that deposited
in soil areas (non-lake) stay in the soil or does it wash off into surrounding lakes?
7) Hg accumulation rate is actually calculated by measuring concentration as a function
of time of accumulation. Time is determined by 210Pb dating (a radiodating technique).
Suppose that for a particular layer of sediment, the sediment accumulation rate as
measured from the Pb-isotope ages of the sediments, is 4 grams per square meter per year
(4gm-2year-1). If the concentration of Hg in the sediment of that layer is 5parts per
million (5ppm), what is the Hg flux into the sediment (in micrograms of Hg per square
meter per year)?
Hint: this is not a hard math problem. The challenge is to conceptualize what you are
doing and why, then do the simple calculation.
Data determined from Swain et al., 1992. Flux is in micrograms per square meter per
year (gm-2year-1). Area is in millions of square meters.
Lake
Surface area
catchment area
Dunnigan
Little Rock
Cedar
Meander
Thrush
Mountain
Kjostad
32.9
18.2
39.1
39.6
6.6
15.7
167.7
46
35
88
127
24
82
985
postindustrial
flux
16.0
18.6
20.1
22.2
26.3
31.7
29.2
preindustrial
flux
4.5
4.6
6.0
6.7
8.0
6.5
9.1
Partitioning:
For this class, mainly need to have a conceptual understanding of the fact that different
elements partition into materials differently. For example, Alcohol partitions into a gas
phase more than into a liquid water phase. Thus, when heat water, alcohol evaporates
preferentially. But some remains in water.
Rock-magma
hydrothermal system-ore deposit
sediments-groundwater
water-air
liquid water- ice
two different crystals in a rock or magma
The degree to which any element partitions between any two materials can be measured
as a function of T, P, X, fO2, pH. That is what I want to get to primarily in this lecture.
However, it is good to have an understanding of the chemistry associated with this
partitioning. It is good for you to grapple with it. So I’m going to at least mention the
roots of this relationship mathematically.
Components of Energy:
Work = w
w=
note: negative sign indicates work is positive when volume decreases.
Changes in volume and pressure affect work. Compressing something increases energy,
expanding lessens (or uses) energy (transfers it to the surroundings).
Heat = q
q=
This defines a relationship between temperature and heat. As add heat to something, its
temperature increases. The equation shows how increasing T results in an increase in
heat (energy) to the system.
E (change in internal energy) = q + w.
This expression is equivalent to the 1rst Law of Thermodynamics in that it shows a
balance of energy between what is added to a system and what that system contains.
(Energy can be converted from one form to another, but it cannot be created or destroyed)
We’re going to skip the mathematical derivation, but there are important terms that we
simply define because they are useful in describing what makes a reaction “go”. These
arise from transformations of E.
Enthalpy = H  E + PV
Entropy = dS =
notes: the ratio of dq/T is found in experiments to be a state function, meaning that it is
only dependent on its present state, not the pathway it took to get there. This ratio then is
a fundamental property of a material as T changes. The result is that T affects the ability
of heat to do work, low-temp heat can’t do as much work as high-T heat.
We have come to associate entropy with the degree of randomness of a system, with
higher temperature favoring greater randomness and the universe trending toward either
equal or greater entropy (2nd law of thermo.)
Gibbs Free Energy = a value that tells us whether a reaction will proceed or not, and to
what degree. Therefore a key in understanding partitioning, a reaction of an element
between two materials.
Gibbs Free Energy = G  H – TS.
G = 0 at equilibrium
G > 0 reaction proceeds towards reactants
G < 0 reaction proceeds toward products
at equilibrium,
Can be modified to account for other changing variables of the system. For example, at
constant P but changing volume, the term +PV can be added (where H is taken at
STP). More pressure makes reaction favor the lower volume reactant or product. go
through example of graphite-diamond transition considering effect of P (delta V), and
melt-solid transition considering the effect of T (Delta S)
RTln [products]/[reactants] = RTlnK
Examples of what K (equilibrium constant) is:
Ca++ + CO3--  CaCO3 (note: living things can alter result from equilibrium)
K = [CaCO3]/([Ca++][CO3--])
note: [ ] designates chemical activity often
approximated by concentration, or concentration times a fudge factor.
Ways of thinking of equilibrium (all equivalent):
1) [CaCO3]/([Ca++][CO3--]) must stay constant at equilibrium. If we increase Ca++,
CaCO3 must increase to compensate.
2) If we increase Ca++ (reactant), G will decrease and reaction will proceed toward
products (CaCO3)
3) key idea: if increase the activity (concentration) on one side of a reaction, the reaction
will proceed in the opposite direction.
Every balance of compositions is a function of T, P, X. Living things, and kinetics
(rates of reactions, may not be equilibrium), also affect.
The result is that everything has a unique compositional fingerprint. But tracking that
fingerprint can be complex because so many things can cause differences.
Focus on partitioning:
We can imagine reactions between any two things for each element:
Yb in seawater  Yb in a clam shell.
H – TS = -RT ln([Ybshell]/[Ybsea]) [rest of K]
Zn in seawater  Zn in flint
Zn in groundwater  Zn in flint (can modify original composition)
Ti in mineral  Ti in magma
weathering can modify compositions (T, P, fO2, pH)
e.g. Clays reflect source rock and weathering conditions
Partition Coefficient: A simple ratio, simplifies chemistry
Concentration of an element in one material
D=
Concentration of an element in another material
This ratio is related to K, but each value of D is only valid for a particular T, P, X of
interest. So D = f(T, P, X).
partitioning of VOC’s between water and air (story of trees to “clean” ground water at
Clay County Land Fill)
Partitioning of Hg: Hg dissolves in hot water. As T, P, X of the water change as this
hydrothermal water migrates in the Earth, Hg can precipitate. Process for ore formation.
Fractional Crystallization:
As crystal grow from a magma (or hydrothermal solution), the composition of the
remaining magma must change.
Also works backwards (Partial Melting). As a rock begins to melt, the composition of
mineral (solid) and melt portions must change.
To understand this, consider an element that is almost entirely excluded from the solid.
D(solid)/D(liquid) << 1
Consider 1 million atoms total, 1000 of them are our element of interest (element E)
Partial melting case:
What is the concentration in the solid before melting? (0.1%)
What is the concentration in the solid after some melting? (~0%)
What is the concentration in the liquid when completely m elted? (0.1%)
What is the concentration in the liquid when half the rock is melted? (0.2%)
What is the concentration in the liquid when the rock is 10% melted? (1%)
For each prompt: how much E is in the solid (or liquid) and how much solid or liquid is
there?
Obsidian compositional variations:
Igneous rocks involve melting and crystallization. Variations in the degree of melting or
crystallization have a big effect on composition.
Suppose, underground, the magma
that the obsidian flow is derived
from is slowly crystallizing.
Consider an element excluded
from the solid (often Th, or REE
are excluded).
Will the concentration of this element be higher or lower in flow 3 from flow 1?
It is possible to figure out not only which region an obsidian point came from, but which
flow, even if they are compositionally similar. If quarrying occurs top down, this can
yield temporal information.
Geochemistry Puzzle Assignment #2:
Geochemistry of volcanic glass in archaeological sites.
Suppose that you have three archaeological digs near a single active volcano. It is known
from geological work that the magma-chamber-source for this volcano contains
crystallizing feldspar. Eruptions often contain phenocrysts of feldspar. Experimental
studies show that the partition coefficient for Ni between feldspar and melt is very low
(say <0.01 for Conc Ni in feldspar divided by conc. Ni in residual melt). Analysis of
small glass beads found in the artifact horizon at each site, associated with an eruption of
this volcano, yield the following results:
Glass beads at site 1 contain 6ppm Ni.
Glass beads at site 2 contain 10ppm Ni.
Glass beads at site 3 contain 5ppm Ni.
1) Which of these 3 sites is the oldest and which is the youngest? Explain your
reasoning. (hint: how will the concentration of Ni in the remaining melt change as some
of the melt crystallizes into feldspar which contains almost no Ni?)
2) What fraction of the melt present at the eruption seen at the oldest site has crystallized
at the time of the 2nd oldest site? (Hint: consider all the Ni to remain with the melt. How
much does the amount of melt need to change to yield the observed change in Ni
concentration?)
3) What fraction of the melt present at the eruption seen at the 2nd oldest site has
crystallized at the time of the youngest site?
4) In a separate study, a researcher estimated the relative ages of these three sites based
on relative changes in pottery style, assuming that pottery styles change at a regular and
predictable rate. The model for the rate at which pottery changes suggests that more time
has passed between the oldest and 2nd oldest sites than between the 2nd oldest and
youngest sites. Does the geochemistry data support this claim or not? Explain.
Soil chemistry:
Review Soil horizons (see Phys Geol. notes)
See physical geology notes for pedalfers and pedacals and USDA soil classification
system
Sequence of elemental solubilities: Na and K, Ca, Si, Fe, Al
Soil Maturity
Sequence of stabilities of inherited minerals in clay fraction of soil:
soluble salts (gypsum and halite)
Calcite,
Dolomite, apatite
Olivine, feldspathoids,
Amphiboles, pyroxenes
Biotite, glauconite, mg-chlorite
Feldspars (K and Na feldspars more stable than Ca, more Ca= faster weathering)
More resistant inherited minerals include
Vermiculite, slightly weathered micas
Muscovite
Quartz
Secondary minerals resulting from weathering of primary minerals
Montmorillinite, smectite
Typical weathering reactions in wet temperate (above) and wet tropical (lower)
environments:
K-spar + H+ = K+ + kaolite
Formation of gibbsite and dissolution of silica
Al2Si2O5 (OH)4 + 5H2O = 2Al(OH)3 + 2Si(OH)4
reaction direction if increase acidity? Have increased (OH)- in water. Consider
H2O = H+ + OH- Adding OH- on right side is like decreasing H+, thus increasing
acidity moves reaction to right.
Phase Diagrams:
Because chemical reactions depend on T, P, and X (as seen from chemical reactions and
Gibbs Free Energy expression), we can make plots of T, P, and Composition showing
where reactions occur. These are called phase diagrams, or for soil or water reactions,
fence diagrams. Very helpful in understanding visually how reactions depend on T, P, X.
In Archaeology, soil composition depends on climate (T, fO2, pH).
CaCO3 + H+  Ca++ + HCO3Talk through what happens if more acidic (lower pH, higher H+)
relative to reaction stuff we learned before.
(consider both lnK, and the idea that reation always goes other way)
Show on an Eh, pH plot with a simple vertical line. On which side will CaCO3 occur?
This is one of most common soil minerals that reflects climate.
Show Fe diagram and talk about the ferric Fe under more oxidizing conditions, and
ferrous Fe under more reducing conditions. Discuss the siderite - ferric hydroxide
reaction line relative to the reaction FeCO3 + 1/4O2 + 2.5H2O ↔ Fe(OH)3 + HCO3- + H+.
or FeCO3 + 2H2O + OH- ↔ Fe(OH)3 + HCO3- + 1/2H2
Then show the natural environment Eh-pH plot (overhead, or computer)
Then overlay soluble Fe diagram over natural environments. Talk about soils and climate
and chemistry: We don’t get into nuts and bolts of doing it in this class and won’t do any
problem sets of this, but wanted you to be introduced to the concept.
talk about reactions, which involve
H=, which O2. Predict effect of
increasing CO2.
From Easterbrook 1993
Formation of kaolinite from K-spar, also production of gibbsite (bauxite) as H2SiO4
drops as SiO2 is leached.
Orthoclase + carbonic acid + water = kaolinite, + potassium ions + carbonate ions, +
silicic acid
4KAlSi3O8 + 4H2CO3 + 18H2O = Al4Si4O10 (OH)8 + 4K+ + 4HCO3- + 8H4SiO4 +
kaolinite + H+ = Gibbsite + silicic acid
Isotopes:
Two days: lecture and video each day.
ISOTOPICS PART I: STABLE ISOTOPES & PART II: GEOCHRONOLOGY (VHS)
1997. Pt. I , 23 min. Pt.II, 29 min. sd. color. #52820 Part I: Stable Isotopes Presents the
definition of isotopes, and the use of isotopes to study the ice ages, the Earth's crust, and
groundwater ontamination. Part II: Geochronology Covers assessing volcanic hazards,
dating of fossil human ancestors, determining the age of the Earth, explanation of
radioactive decay and half-life, and the use of isotopes to study extinction of dinosaurs.
What are isotopes?
protons, neutrons, electrons explanation.
explain stable and unstable
important stable isotopes in geology:
16
O. 17O, 18O go through numbers of protons and neutrons: usually look at 16 and 18
because they have bigger difference (Atomic number oxygen = 8)
12
C, 13C (note 14C is radioactive) (Atomic number carbon = 6)
32
S, 33S, 34S, 36S (usually look at 32 and 34 because they are the most abundant (32=95%,
34=4.2%) (Atomic number sulfur = 16)
36
Ar, 38Ar, 40Ar (Atomic number argon = 18)
Value of isotopes?
talk about chemically identical but different weight gives slightly different properties.
Usually look at lighter stable isotopes. bigger proportional difference between 12C and
13
C than between 206Pb and 207Pb. So less effect in lead from difference in mass of atom.
e.g. lighter more easily evaporated.
explain oxygen isotopes locked up in polar ice and affect on ocean balance and therefore
balance in sediment and fossils.
concept of delta values:
 0/00 = (
isotopic ratio for sample
- 1)  1000
isotopic ratio for standard
value increases when the heavier isotopes is more abundant in the sample than in the
standard. e.g. 18O/16O, 34S/32S, etc.
Overhead or computer graphic of climate change
over past 66my from sediment cores and ice
cores. Or give as handout.
-mention SMOW standard (std mean ocean water)
slightly different partitioning properties.
Carbonate ion reaction (exchange)
C16O32- + 3H218O  C18O32- + 3H216O
C18O32-/C16O32K=
(H218O/H216O)3
reactions depend on T. So can infer temperature of sea water from which carbonate
precipitated.
 = K⅓
Living things alter reaction from strict equilibrium.
mention Kinetic balance vs equilibrium balance.
Radiogenic isotopes
40
Ar example, stripping of planetary atmospheres. Derivation of radiogenic 40Ar from
radioactive 40K. Others primordial.
other comments on usage:
ground water, rainwater, primordial water have different isotopic ratios for O
Bone has C and O, can reflect diet (you are what you eat)
past climate
past temperatures (other than climate)
organic activity, microbial activity
changes in ocean chemistry through time
Carbon and sulfur in hydrocarbons (petroleum prospecting)
Show video, Part I, 23 minutes.
Unstable (radioactive) isotopes:
Parent-Daughter idea. Nucleus is not energetically favorable, over time it “decays” to
become a different nucleus that is more stable.
beta decay: (explain origin of beta particle in nucleus, conversion of neutron to a proton
= changes element)
electron capture: (backwards beta decay sort of, usually from K shell, conversion of a
proton to a neutron = changes element)
alpha decay: (helium nuclei, 2P,2N)
In each, nucleus can be left in a high energy “excited” state, which when it goes to lower
energy state releases gamma rays. For electron capture, or X-rays produced when
missing electron in K shell is replaced.
Important systems: (ones in bold: go through decay process)
40K/40Ar electron capture (K=19P, 21N : Ar=18P, 22N) (explain)
half-life 1.3billion years.
Concept of half-life: connect probability of decay to half-life. In one half-life, a
particular nuclei has 50% chance of decaying. Like flipping a coin. If one half-life, flip
1000 coins, how many (about) will be heads? 2nd half life, how many heads? and so on.
Each half-life, half decay.
Concept of setting clock to 0. Have to know when the “starting time” is, or what it
means. Is it since the origin of atoms? Since the origin of the Earth? Since the origin of
a rock? Since something happened to a rock?
Ar is a gas, evaporates when the rock is melted and all 40Ar lost. So starts out at 0. Then
make new 40Ar through radioactive decay of 40K.
Go through a simplified example and have them figure out how much time passed.
40
K/40Ca beta (K=19P, 21N : Ca=20P, 20N)
U/206Pb 8alpha + 6beta (4.5by halflife) (decays through several intermediate steps that
are also unstable)
235 207
U/ Pb 7alpha+4beta (710my halflife)
232
Th/208Pb 6alpha+4beta (13.9by halflife)
87Rb/87Sr beta (Rb=37P, 50N : Sr 38P, 49N) (48.8by halflife)
14 14
C/ N beta (C=6P,8N : N=7P,7N) 5730 years
147Sm/143Nd alpha (Sm=62P,85N : Nd=60P, 83N) (106by halflife)
187
Re/187Os beta (Re=75P, 112N : Os=76P, 111N) (43by halflife)
176
Lu/176Hf beta (Lu=71P,105N : Hf=72P,104N) (36by halflife)
others
238
Be-10 2.5 M.Y.
Fission
Explanation of 14C systematics:
Steady-state production in the atmosphere by cosmic-rays
14
N + neutron (produced by cosmic rays interacting with atoms)
14
C + proton
This carbon becomes incorporated into living things, which maintain a balance of stable
carbon (12C, 13C) and 14C related to the balance in the atmosphere.
When a living things dies, it stops maintaining the balance with the atmosphere. Decay
of 14C causes the amount of 14C in the remains to decline.
By measuring how much 14C is left we can determine the amount of time that has passed.
If half of the original 14C is left, how old?
If ¼ of the original 14C is left, how old?
Concerns: Unlike other radiometric methods, we don’t measure the amount of daughter
(14N) and so we don’t have an actual measurement of the initial 14C. We estimate the
initial 14C by assuming the amount is related to the amount of 14C produced in the
atmosphere. However, the balance of 14C may not have remained the same through time,
method has been calibrated against tree rings to see how atmospheric 14C may have
changed through time.
Can get to intermediate values (not just equal steps of ½) by:
N/N0 = (1-)t
N=number of parent remaining, N0 = initial parent, = fraction of N that decay in unit
time, t=number of time units. (for example, years)
half-life = ln2/
87
Rb/87Sr systematics and the concept of the isochron:
Rock clock set to 0 when rock melts. All minerals have the same proportion of 87Sr/86Sr
(stable and radiogenic are “mixed”)
However, some minerals within the rock have more parent than others (87Rb). once rock
solidifies, 87Sr will accumulate more rapidly in minerals with more 87Rb (remind of
PARTITIONING). (NOTE: can also do whole rock isochron where rocks with different
initial 87Rb are used)
General derivation of graphical relationship:
dN/dt = N (this is the more general expression of the simplified relationship given
above)
integrating with respect to time yields:
ln(N/N0) = -t
taking exponential
N=N0e-t
Since N0 = N + accumulated daughter(D)
N = (N+D) e-t
or, rearranging
D(e-t) = N(1- e-t), so dividing by e-t yields
D = N(et -1)
But, for 87Sr, some daughter is already present in rock, even after melting. To handle
this, we put expression in a form that normalizes to nonradiogenic 86Sr
87
Sr/86Sr =
87
Sr0/86Sr + 87Rb/86Sr (et -1)
Intercept related to the INITIAL 87Sr
slope related to the age of the rock (t)
Initial 87Sr/86Sr also tells us something. It tells us about whether previous separations
have taken place. If fractional melting takes place, Rb goes with the melted part. Then
let it sit for a while, get lots of 87Sr. So higher 87Sr can tell us that this particular batch of
material has been separated from the mantle for a long time.
Also, can reset the minerals (by metamorphism), but whole rock isochron still gives age
of original formation. So can get 2 ages: one of when rock 1rst formed, one of when
metamorphism occurred.
Show Video part II.
Geochemistry Puzzle Assignment #3:
Radiometric dating calculations.
Part I. Rb/Sr dating example: Age of igneous lunar sample 10044, 30 (from
Papanastassiu et al, 1970; among first dates for lunar rocks ever done)
Mass spectrometer analysis results:
87Rb/86Sr
sample fraction
whole rock
0.00982
plagioclase
0.00159
pyroxene - A
0.0252
pyroxene - B
0.0197
“ilmenite”
0.0501
“Crystobalite” – A
0.0629
“Crystobalite” – B
0.0844
87Sr/86Sr
0.6996212
0.699196
0.7006011
0.7001111
0.701738
0.702365
0.703625
Method hints:
Graph the data.
Graphically determine the slope (one could use linear regression, but you can just
“eyeball” the slope with a ruler and pencil).
Calculate the age from the expression:
87
Sr/86Sr =
87
Sr0/86Sr + 87Rb/86Sr (et -1)
Where the slope = (et -1)
Add 1 to both sides and take the natural log such that
ln(slope+1) = t
where t=time,
and  is the decay constant which, for 87Rb is 1.42x10-11 decays per year (this
corresponds to a half-life of 50 billion years).
Using the scatter in the data as a guide, draw what you think are the maximum deviations
possible for the slope (if you do linear regression, the regression program should give you
an uncertainty estimate of the slope--you can use this value in the calculation). Then
calculate the slope in the same way to give you an estimate of the uncertainty. Include
this uncertainty in your report of the age.
AGE of 10044,30: _______________________________
Part II: Radiocarbon dating example.
Notes: radiometric analysis (counting of beta decays) is cheaper for larger samples, say
300mg to 4 g total carbon. Accelerator Mass Spectrometry is used for smaller samples
(say 100mg to 300mg). By convention, all radiocarbon dates are referenced to 1950.
Important corrections include corrections for past atmospheric 14C (which was different
due to variations in the Earth’s and Sun’s magnetic fields which altered the production
rate for 14C) and isotopic fractionation. For radiometric analysis, beta decays are counted
with a scintillation detector.
Suppose you use the radiometric method, counting decays in a 2 gram sample. After
counting for 24 hours, you record 9763.2 total decays.
At this point, calculate the percentage error from counting statistics. (hint: the
percentage error = sqrt(counts)*100/counts = 100/sqrt(counts).)
percentage error from counting statistics = ___________________________
You do an analogous count on 5 grams of modern carbon in equilibrium with the
atmosphere (counting for 5 days to minimize statistical uncertainty) and derive an activity
of 67.8 decays per minute. Percentage error from counting statistics = ______________.
Remember that the decay equation is
N = N0e-t.
where N = the number of atoms remaining, N0 is the initial number,  is the decay
constant, and t= time.
Rearranging and taking the natural log yields:
ln (N/N0) = -t
N0 , the number of atoms, is proportional to the number of decays per minute per gram.
N, the number of atoms initially, is equal to the modern atoms, and is proportional to the
number of decays per minute per gram in modern carbon (actually it isn’t exactly equal to
the modern concentration because this has changed somewhat through time).
= 1.21x10-4/sec (corresponding to a half life of 5730 years)
Calculate the radiometric age of the sample:
_______________________________________
Note: The true age can be derived by applying calibration curves to this result to account
for changes in atmospheric 14C through time, etc.
Variation Diagrams (“visual statistics”):
“interactive” lecture: Concepts are ones understood by practice, not memorization!
topics to integrate: linear regression, distinguishing populations, cluster analysis, timedependent variation, and correlations between elements
Reviews of: partitioning, previous discussion of the importance of evaluating variation in
a value in order to understand whether you can distinguish populations.
A variation diagram is a plot of the variation in concentration of one element in a suite of
sample against the variation in concentration of another element.
You are doing a survey of flows from a single Hawaiian volcano (say Mona Loa)
and its effect on communities through time. As part of this study, you want to relate
composition to time period of each lava flow.
You know that Hawaii eruptions occur from a magma chamber in which the
mineral olivine is crystallizing. The olivine is denser than the melt, sinking to the bottom
of the chamber, and is effectively removed from the melt.
Experiments show that the partition coefficient for Yb in olivine is very low
(nearly 0) (Dol/melt for Yb <<1) and the partition coefficient for Ni is high (Dol/melt for
Ni ~ 10).
1) Consider variation diagram, and predict what the plot of many different flows over
time would look like:
2) Now, which of these flows is the most recent, and which is older?
3) Consider the plot of 2 flows provided (not shown otherwise the answer to questions
above would be obvious!). How much olivine has crystallized between the two?
handout.
Math notes for fractional crystallization puzzle with variation diagrams:
Concentration in olivine = D*Concentration in the melt (This is definition of partition
coefficient)
Thus:
Let X = the amount of Ni in the olivine.
If we consider that there are 20 atoms of Ni total, and 10 million atoms total (about 2ppm
Ni before any crystallization) then we can calculate the concentration of Ni in melt after
50% crystallization as follows:
X/amount atoms in Ol = 10* (20-X)/amount atoms in melt
at 50% crystallization, amount Ol = amount melt = 5 million atoms
Thus,
X/5 million = 10* (20-X)/5 million
or X = 10*(20-X)
or 11X = 200
or X=18.18
The concentration of Ni in the melt goes from 2ppm with NO crystallization, to (2018.18)/5 million or 0.364ppm at 50% crystallization.
By similar calculation, for Yb (D~0, initial Yb also at 2ppm for convenience):
Let Y= number of Yb atoms in Olivine
Y/amount Ol = 0*(20-Y)/amount of melt
Amount of Ol = Amount of melt (as before)
Y=0 (there is almost no Yb in the olivine. In reality there will always be some, but it is
often low enough to ignore for this type of calculation)
Thus the concentration of Yb in the melt is
(20-0)/5million = 4ppm. The concentration has doubled as the amount of melt was
reduced by half.
The general equation for the change in the composition of a fractionally crystallizing
magma, derived from the type of reasoning given above is:
CiL/Ci0 = F(Di-1)
Rayleigh Equation
L
Where Ci = Concentration in the liquid, Ci0 = initial concentration in the liquid, F =
fraction of the liquid crystallized, Di is the total partition coefficient for element i
between solid and liquid.
Figure for Variation diagram puzzle (draw on board)
Scatter plots and cluster analysis using variation diagrams:
What can you tell?
two different populations or not? (yes)
If you took a single sample, could you tell to which population it belonged? (Two
sources of pottery clay…..could you tell which source a particular pot came from?)
Answer: depends. There is a zone in middle where you would be unsure.
More variation = more difficult to distinguish.
Variation from both analytical uncertainty, and from natural variation in the source
material.
Statistics:
Definition: Body of concepts and methods used to collect and interpret data and to draw
conclusions in situations where uncertainty and variation are present.
Statistical population: Complete set of all possible measurements and record of some
qualitative trait, corresponding to the entire collection of units from which inferences are
made.
Sample: A set of measurements and records from which the total population is inferred.
Statistics provides a means to assess the uncertainty in the sample and provides guidance
and criteria for setting up the sampling method.
Data can be
discrete: can take only restricted values (e.g. integers, male-female, etc)
usually plotted on a histogram.
continuous: can take any possible number of successive values (limits of
measurement make this “discrete” at some level). Usually plotted as a smooth curve.
Chemical data usually continuous, but may apply to discontinuous objects.
Comparing a single sample to the distribution of the larger sampling:
Is the single sample a member of the larger sampling?
Depends on where it occurs. If very near “peak” larger chance that it is than if it is off on
the side.
If sample is within 2sigma standard deviation of mean, often consider it at least not
inconsistent with membership in the group. Outside 2 sigma often taken as evidence that
it is outside the group. If it is outside 2sigma, there is still a 5% chance that it could
belong to the group.
e.g. you have a particular pot. Wonder if clay could have come from a known source, or
if it must be another source. Test with a single element.
Mean =
Standard deviation of a single sample determined by evaluating how much variation there
is in the entire sampling.
SD = sqrt(
)
(1-sigma)
Example: mean Yb for pottery from a known clay source = 2ppm. Standard deviation
for a single measurement for this sampling is 0.2ppm (1 sigma) or 0.4ppm (2 sigma).
You find a pot with a Yb concentration of 2.4ppm. What do you conclude?
[5% chance that the hypothesis that it is from a different source is wrong.]
comparing two populations:
Can you identify which population an individual sample belongs to?
depends. More elements helps (remind of scatter plot).
Can you tell the two populations apart?
Introduce T test and Anova test.
Simplified approach, often sufficiently rigorous:
Test whether there is overlap between the two means, taking into account SD of the
mean.
SD of the mean  SD of a single measurement/sqrt(number of measurements)
Now taking example above, suppose that you had 16 measurements of pottery from the
known clay quarry, and 16 measurements of pottery from the other location which you
wondered if it was from that quarry.
The mean for the first is 2ppm, and the mean for the 2nd is 2.4ppm. The standard
deviation of the first sample is 0.2ppm (1-sigma) and the standard deviation of the second
sample is 0.4ppm (1-sigma - there is more variation from measurement to measurement
in this set of pottery). What can you conclude?
[Differ by much more than 2 sigma, so are different at much greater than the 95%
confidence interval.]
Statistics: Body of concepts and methods used to collect and interpret data and to draw
conclusions in situations where uncertainty and variation are present.
Statistical population: Complete set of all possible measurements and record of some
qualitative trait, corresponding to the entire collection of units from which inferences are
made.
Sample: A set of measurements and records from which the total population is inferred.
Statistics provides a means to assess the uncertainty in the sample and provides guidance
and criteria for setting up the sampling method.
Some examples of things to test:
Is a particular sample or subsample a member of an identified grouping?
Method: Compare values, taking into account standard deviations
example: The Colossi at Memnon.
Are two groups equivalent or different?
Method: Ttest, Anova, Discriminate, Univariate, Nonparametric comparisons (for
non-normal distributions).
example: statistical lab assignment
Are two variables within a single grouping correlated to each other?
Method: linear regression analysis, non-linear correlation analysis
example: The amount of Pb in a particular lake varies over some time period.
The amount of fly ash also varies. The question arises, are these two correlated, possibly
indicating that a primary source of Pb is the fly ash, or the industrial activity that results
in it.
Among a large group of samples, can subgroupings be identified?
Method: cluster analysis.
example: Are obsidian points from a single quarry with variable composition, or
are the points from different quarries?
Among a group of samples with correlated variations among variables, can key correlated
variations be identified?
Method: Principle component analysis, factor analysis
example: A particular group uses clay from three sources to make a certain type
of pottery. But they use different amounts from each source at different times. Can the
composition of each of the three sources be extracted from the compositions of the
composite pots and how they vary?
Reading Geochemical Fingerprints: LAB #1
Experience with Statistics
General notes on MS Excel statistics. Access the statistical package by clicking on Data,
then on Data Analysis (if data analysis is not available, you need to add it by clicking on
the microsoft symbol in the upper left, then on "excel options"--you'll have to figure it out
from there.)
Part I: Simple statistics and comparing two data sets
Use ONE of the following three data sets. For that data set, do the following:
A) Consider the basic statistics for at least two variables for each of the two different
groups of your data set (e.g. Green Glass B and D are one data set but two different
groups, B and D-consider them separately). Do this using "Descriptive Statistics" of the
Excel Data Analysis package. Make sure that the Summary Statistics Box is checked.
i) Report results
ii) In one sentence, explain what each of the reported values means (this may
require some online searching to learn the difference (for example) among Standard
Error, Standard Deviation, and Sample Variance.)
iii) Is the variance for the variable equal or different between the two different
groups of your data set (of course it won't be the exact same number-I'm asking that you
think about whether they are fairly close or not. Think about it. - you can actually test
this question using the 'F-test two sample for variances facility in Data Analysis)
iv) Considering the Means and Standard Error, would you say that these two
groups are the same or different? Explain your reasoning in detail.
v) Plot two of the variables on a two-variable variation diagram (for both
groups). Does the statistical answer match what seems reasonable visually?
B) Do a statistical test of the same data set used in (A) to see if the two groups are the
same or different.
i) Use the t-test, two sample assuming equal variances. Report results.
ii) The null hypothesis for this test is that the two groups are the same. The P
value is the probability that the null hypothesis is true (well, simplified for nonstatisticians). Thus, smaller values of P correspond to higher probabilities that the two
groups are different. So, are your two groups different? (This is a two-tail problem-one
tail problems correspond to questions like 'is group B mean larger than group D').
iii) use the t-test, two samples assuming non-equal variances. What one thing is
different in the output? Explain what this means about how the test is done.
Part II. Correlation and Regression
A) Is there any correlation between different elements in Green Glass B in Data Set 1?
That is, when one element changes, does another element change in a coordinated way,
or are variations in the two elements uncoupled from each other?
i) Consider if there is any correlation between MgO (Y axis) and Sm (X axis).
Use Regression in the Data Analysis package. Report results.
ii) At what level of confidence is the overall regression significant? At what
level of confidence is the intercept non-zero? At what level of confidence is the slope
non-zero (that is, a correlation exists)?
iii) Plot MgO vs Sm (include in report). Do you see a correlation? Is it
significant do you think?
iv) MgO is compatible in silicate melts, and Sm is incompatible. Is the apparent
correlation consistent with fractional crystallization producing a correlation? EXPLAIN.
B) Sometimes variables are correlated, but do not initially appear to be because of
multiple correlations among several variables. To understand this, we're going to create a
"fake" data set (which should also help you understand the concept of how geochemical
fingerprinting works-and provide a fairly rigorous introduction to using spreadsheets to
manipulate data!).
Consider how various sources of materials affect the composition of ceramic or glass
materials. Set up a spread sheet to calculate the "fake" compositions, such that there are
12 different glass or ceramic samples, each with 5 different elements. Each glass or
ceramic sample is itself a mixture of three different "source" materials (previous glass
materials, clay samples, whatever). The composition of the source materials is given
below, as well as the proportions of each source that make up each glass or ceramic
sample. The compositions are as follows:
MgO
Yb
Ni
Sr
Lu
Source 1
1
6
3
1
7
Source 2
2
1
3
5
6
Source 3
3
4
6
2
1
Sample number
1
2
3
4
5
6
7
8
9
10
11
12
Source 1
5%
5%
5%
5%
10%
10%
10%
15%
15%
15%
20%
20%
Source 2
5%
10%
15%
20%
5%
10%
15%
5%
10%
15%
5%
10%
Source 3
90%
85%
80%
75%
85%
80%
75%
80%
75%
70%
75%
70%
After constructing a table in the spread sheet that lists the composition of each sample,
consider the correlation between Yb and Ni.
i) Graph Yb vs Ni (in the spread sheet program). Are they correlated (using your
eye-evaluation of the graph)?
ii) Do a linear regression of Ni = A + B(Yb). Report results. Are they correlated
(using statistical tests)? (The R2 value is a measure of what fraction of the total variation
in Ni is explained by the correlation to Yb. You can also examine the value of B, as well
as the uncertainty in B, and ask if the value of B is significantly different from 0. A value
of 0 means that there is no correlation between Yb and Ni). You can also consider the
listed significance of F test, which is a probability that there is no significance to the
regression).
Actually, Yb and Ni ARE correlated, but that correlation is masked because Ni also
varies with MgO, hiding the correlation to Yb. You can see this by doing a different
regression.
iii) Do a regression to the expression Ni = A + B(Yb) + C(MgO). Again examine
the value for R2 (which is now 1 because we have created a fake set of data that must be
exactly correlated, thus all of the variation in the data is explained by the correlation).
Also, examine the values for B and C and whether those values are significantly different
from 0 (that is, they are more than 2 sigma different from 0). Consider the signficance of
F test. Discuss results.
Data Set 1) Volcanic Glass beads from the Moon.
First Set of Beads (Green Glass B)
Sample
gg409
gg394
gg153
gg358
gg271
gg
SiO2
45.81
46.24
46.24
46.29
45.77
46.00
MgO
17.08
17.04
16.82
17.08
17.12
17.24
FeO
18.99
18.61
18.78
18.52
18.78
18.77
CaO
8.8
8.7
8.8
8.8
8.9
8.7
Co
73.3
72.1
72.6
71.0
72.2
71.7
Sm
0.871
0.893
0.888
0.855
0.888
0.851
type
B
B
B
B
B
B
Co
80.5
78.6
81.0
79.0
76.6
Sm
0.705
0.740
0.674
0.754
0.659
type
D
D
D
D
D
Second Set of Beads (Green Glass D)
Sample
gg
gg
gg
gg
gg
SiO2
45.06
45.10
45.12
45.15
45.50
MgO
17.71
17.6
17.48
17.39
17.4
FeO
20.28
20.09
20.31
20.15
19.77
CaO
8.3
8.3
8.3
8.5
8.4
Data Set 2) Gryphaea population-size data (be sure to use all data, recognizing that the
data for each population are in two columns:
Data Set 3) Use some data of interest to you. There must be at least two sets of data,
e.g. pottery from two different sites, lava from two different volcanoes, or from two
different flows from the same volcano, obsidian points used by two different groups of
people, sediment samples from two different lakes, or a single lake but representing
different periods of time etc. You must have at least 5 separate measurements for each
data set.
You must have at least 2 measured variables for each set of data. e.g. analysis of at least
2 elements, measurement of at least 2 dimensional values, etc.
Analytical Methods, X-ray methods
Diffraction analysis (XRD, TEM):
Concept: measure the angle at which incoming X-rays constructively interfere from a
crystalline material.
Use: Identifies mineralogy of sample, chemistry indirectly. Can get qualitative (kinds of
minerals present) or quantitative (proportions of minerals) information. Mineralogy
reveals information both about source and processing. Firing, for example, alters
mineralogy of pottery while leaving its chemistry mostly unchanged.
Can also reveal information about defects in crystals or size of microcrystalline materials
(broadening of peaks)
Discuss concept of diffraction:
Explain concept of X-ray wavelength.
(error in picture: n=the number of wavelengths, not the number of d spacings, so it can be due to the angle, as well
as the number of d spacings.)
where the constructively interfere defined by the
Bragg equation: n = 2dsin
Use known and fixed value for wavelength (anode of Cu for example, want long
wavelength so won’t excite) Knowing  allows us to determine d which is unique to each
mineral which has a unique spacing of atoms in the crystal structure.
Note: mention TEM, TEM also useful in observing microstructures and defects
X-ray emission spectroscopy:
concept: kick electron out of its spot, then when it falls back in, measure the
characteristic energy emitted
Use: determine chemical composition of materials for elements with X-ray emission not
easily absorbed by atoms in good vacuum (usually elements heavier than about Ne).
Discuss X-ray excitation, Inner shell electrons quantum energy levels.
Principle Quantum number (K,L,M,N shells)
Angular Quantum number () shape of sub shell
Magnetic Quantum number (J), refers to orientation of , -, 0, or 
spin Quantum number (s) , + or – one-half.
Methods of excitation:
X-ray excitation (X-ray fluorescence), used for bulk samples most commonly, both major
and minor elements
Electron excitation (EMP, SEM), penetrate less than X-ray, and control beam more
easily, used on small samples and single minerals in a sample, narrow focus, energy
controlled by voltage drop imposed on charged electrons.
SEM (backscatter and X-ray emission) valuable for examining textures, small scale
compositional variations.
Proton excitation (PIXE= Particle induced X-ray emission) Don’t penetrate surface,
useful for extremely thin samples (air samples), or where only extreme surface is of
interest. Lower background (explain background) so more sensitive.
Methods of X-ray analysis:
energy dispersive (Pulse height analysis related to energy of photon)
wave-length dispersive (diffraction crystal and angle method)
Energy is proportional to 1/
Counting statistics:
S.D. (as a percent)= 100/sqrt(N) where N = number of pulses accumulated.
(note: 100*sqrtN/N
= 100/sqrtN)
X-ray absorption spectroscopy
concept: absorbing energy to kick out electron, vs emitting energy when electron falls
back into its spot)
XANES: (X-ray Absorption Near Edge-Structure Spectroscopy) Monochromotic
focused beam, look at small samples, get more detailed information about state of atom in
target material.
<XANES can provide information about vacant orbitals, electronic configuration and site symmetry of the absorbing atom. The
absolute position of the edge contains information about the oxidation state of the absorbing atom. In the near edge region, multiple
scattering events dominate. Theoretical multiple scattering calculations are compared with experimental XANES spectra in order to
determine the geometrical arrangement of the atoms surrounding the absorbing atom.>
The electron column and all of its components listed below are under vacuum. The
vacuum system for any electron beam instrument is an integral part of the instrument; a
high vacuum is necessary to prevent electrons within the beam from interacting
(scattering) with anything other than the specimen. Without a vacuum, it is conceivable
that 90% of the electron beam would still reach the specimen, but half of the electrons
could retain only a fraction of their initial energy after Coulombically interacting with
gaseous molecules.
The electron gun provides the source for the electrons. It is primarily responsible
for the electron beam's energy, and the first focal point that is termed the initial
crossover, d0 (diameter ˜100μm). The three primary components of the gun are the
electron emitter (filament or cathode), the biasing cylinder (Wehnelt or grid cap) and the
anode. Current runs through the filament (filament current). This heats up the filament
and causes electrons to "boil off". A high voltage imposed between the filament and the
anode plate causes electron to accelerate down the column (the beam current).
The condenser lens is the first electromagnetic lens below the gun and is
generally a combination of two separate lenses. Its function is two-fold: (1) it is the
primary de-magnifier for the electron gun's crossover (approximately 1/10,000X), and (2)
adjustment of its focal point relative to the CL aperture by which the user varies the
amount of the electron beam (i.e., the beam current) which will ultimately reach the
specimen or target. Below the condenser lens, the intermediate spot’s diameter, d´, might
be de-magnified to 50-200 nanometers.
The objective lens has only one primary purpose -- to focus (or defocus) the
primary electron probe on the target. Depending on the instrument, it can de-magnify the
intermediate spot, d´, after the condenser lens on the order of 10 to 100 times, ultimately
reducing the final probe diameter, dp, to approximately 5nm. The objective lens also has
an aperture associated with it that is not shown in the Figure above. The final aperture is
important because the aperture's diameter is an adjustable parameter of the electron
column, and is often used to coarsely modify the character of the instrument; for
example, from high resolution imaging to quantitative x-ray analysis. This aperture can
also be considered analogous to a camera’s aperture … that is, not
only controlling illumination but also offering control of depth of focus.
The specimen holder, although not part of the electron column, plays an
important role in the interaction of the beam and sample. Its primary purposes are to
orient the specimen in x-y-z space relative to the beam, move the specimen in the x-y
plane and provide rotation and tilt if desired. In terms of the relationship between the
specimen and the focusing of the electron beam, the most important function of the
sample stage is in controlling the working distance from the final lens, or pole piece, to
the specimen. This distance, known as the working distance, is sometimes continuously
adjustable and is a consideration along with the size of the objective lens aperture for
optimizing such imaging parameters as the depth of focus, and ultimate spot size.
The scanning coils provide the means by which the electron beam is scanned or
rastered over an area on the target, much the same way an electron beam in your
television or computer screen is rastered across the face of the picture tube. The scanning
coils and display CRT are synchronized with the scan generator, which can also provide
other scan related features such as image shift, scan rotation, selected area scans, picture
within a picture, etc.
1
The secondary electron detector is one of several detectors, many of which are
located in close proximity of the electron beam’s interaction with the specimen. All
detectors send a signal to the viewing and photo CRTs via amplification and
synchronization with the scanning coils. Some of these detectors are necessarily
configured for line-of-sight detection, which include all x-ray spectrometers, cathodoluminescence and backscattered electron detectors.
Components we might make special note of with regard to the basic design of
EPMA versus SEM instruments are the specimen stage, reflected light viewing and the
objective lens. The specimen stage in an EPMA generally does not include capability for
variable working distance and tilt because such variability would alter the take-off angle
to the x-ray spectrometer(s). Even the capability to rotate the specimen within a
microprobe is found only in a very few instruments.
Reflected light viewing is generally more convenient for finding your way around
on a large flat specimen, and so it is generally considered a requirement for EPMA.
Cassegrainian mirrors (Figure 4-1) that allow a pathway for electrons along the optical
axis are generally preferred over oblique optical viewing. Commonly found in geological
laboratories is the transmitted light option available on most microprobes, sometime
including an option for cross polarized (darkfield) light.
The objective lens on a microprobe is designed specifically for line-of-sight
detection toward the x-ray spectrometer(s). Notice in Figure 4-1 (and 4-6) how the final
lens accommodates the take-off angle to the x-ray spectrometer.
Example analysis puzzle. Data from Tabb Prissel
microprobe data.
Give students counts and seconds for standard. Figure peak
height and error.
Give for one or other sample point, calculate conc and
whether significant.
point one (distant from Ni metal interface)
Spect
115.68
115.48
115.08
position
cnts
4079.14 4026.15 17504.2
73
75
15
sec
1050
1050
4200
nA
172.564 172.072 171.693
cnts/sec
0.02251 0.02228 0.02427
/nA
28
39
4
114.68
114.48
4521.17
33
1050
170.549
0.02524
72
4618.17
45
1050
170.339
0.02582
06
0.00030
78
0.00020
34
0.00017
08
0.00360
78
Point 2 near Ni metal interface
cnts
sec
nA
cnts/sec
/nA
479
150
20.511
0.15568
88
522
150
20.229
0.17203
03
2339
600
20.171
0.19326
43
520
150
20.076
0.17267
72
507
150
19.888
0.16995
17
0.02567
73
0.01696
6
JEOL-Ni standard
cnts
2164
sec
30
nA
21.606
cnts/sec
3.33857
/nA
88
19023
30
21.593
29.3659
98
299764
90
21.549
154.564
53
6806
30
21.434
10.5844
3
1988
30
21.381
3.09932
49
151.345
58
100
Analytical Methods, non-X-ray methods
Overview of analytical methods key concept
All analysis is based on different properties of materials
Properties include:
Difference in Mass: e.g. mass spectroscopy
Differences in diffusivity, mobility (related to mass and/or partioning or retention by
the immobile phase): gas/liquid chromatography
Differences in thermochemical potentials: electrochemical analysis, pH measurements,
titrations.
Differences in thermal properties: e.g. thermogravimetry
Differences in optical/refractory properties: e.g. XRD, optical mineralogy
Differences in radioactivity: 14C dating (other techniques often use mass), also
imposed radioactivity from activation analysis.
Differences in energy levels
Type of transition Wavelength and E of transition
example methods
Inner electrons:
X-ray,
XRF, EMP etc.
Outer electrons:
visible,
AAS etc
Molecular vibrations,
IR, Microwave,
IR spectroscopy,
rotations, etc:
Mossbauer, Raman.
Nuclear:
X-ray, -ray,
INAA
Magnetic:
NMR, ESR(microwave)
AAS: Use high-T flame to atomize, vaporize, examine absorption of a wavelength that is
absorbed by each particular element by transitions in its outer electrons. Compare to a
standard.
(note: could also look at emission from these transitions)
use liquid sample: need to dissolve samples.
used a lot for soluble rocks, such as carbonates, used in environmental problems,
especially as involves water. Can be used for other materials if they can be dissolved.
particularly good for elements Alkalis, Zn, Cd, Al, Cr, In, Mn, Pb, heavier REE.
INAA: activate by irradiation in a nuclear reactor, exposes to Neutrons which bombard
and destabilized nuclei, measure gamma radiation from return from excited state,
compare to standards irradiated at the same time, same location, same duration. Energy
levels unique to elements, like X-rays were.
good for many trace elements, including REE, Y, Co, others.
FTIR (Fourier Transform IR): IR spectrum derived using an interferogram and
mathematical process (Fourier transform).
ICP-MS: ICP Inductively coupled plasma = means to atomize and ionize (a special type
of plasm that derives its sustaining power by induction from a high-frequency magnetic
field), can also be used with AA. MS = mass spectroscopy can analyze mass of particles
in the plasma.
Reading Geochemical Fingerprints Lab (Extra lab):
Analytical Chemical methodologies, using voltammetry as a conceptual example.
I will give you a sample of ferrous sulfate solution. I want you to measure the
concentration of Fe in the solution (in grams of hydrous ferrous sulfate per ml water).
(the range of concentrations possible is 0.004g/ml to 0.054g/ml).
A voltammetric scan measures the current through the solution that results from an applied voltage. The
voltage changes from a starting voltage, to a set peak voltage at some chosen rate. We will do a simplified
cathodic stripping voltammetric analysis. In this method, the voltage is held constant for a while,
concentrating the species of interest on the electrode, then the voltage is changed such that the reduced
species reoxidizes back into the liquid. The electrical current that results is directly proportional to the
concentration.
The current derived for a voltammetric scan is a function of
1) the rate at which voltage changes
2) the voltage chosen
3) the electrical resistance (distance between electrodes)
4) the surface area of electrodes exposed to the solution
5) the concentration of electroactive species present (such as Fe)
I will do the experiment (protecting my instrument of course!) with the following parameters for a
differential pulse experiment:
-2000mV starting voltage, 600mV ending voltage, 50mV pulse height, 10mV step height, 8, 4, 3 for other
parameters yields a scan rate of about 1200mV per second. The electrodes will be left at the starting
potential (-2000mV) for 30 seconds before the analysis is done.
Your assignment is:
1) Design an experimental methodology to measure the concentration of Fe in a solution.
2) Using your experimental method, measure the Fe concentration in the unknown
sample
Hints:
You need to think about controlling the distance between electrodes and electrode surface
area. You need to think about minimizing the error or variation in these values.
You need to develop a means to compare your unknown to something that you do know.
ALL analytical methods compare an unknown to a sample or samples that ARE
KNOWN. You have iron sulfate with which to make standard (known) solutions.
You need to assess the precision of your measurements to understand whether your
measurements are sufficiently precise to be meaningful. To do this, you need to take
repeated measurements (remember, the entire experimental set up is part of the
measurement, if you only repeat measurements with the exact same experimental
assembly, it may not reflect all of the potential error and uncertainty in your
measurements).
Optical Petrography
Texture
size, size distribution, point counting (for archaeology relates to both source and process,
e.g. for pottery, tools, metalworking, example: bimodal size distribution in pottery)
grain angularity, skeletal grains, packing, overgrowths, orientation
Processes:
accumulation
crystallization
change/deformation (metamorphism, metal working, pottery firing etc)
sedimentary textures (packing, cementation, overgrowths)
metamorphic textures (foliation, augen)
igneous textures (crystalline intergrown texture, porphyritic)
cumulate textures (sedimentary-like with interstitial igneous)
weathering or reaction textures
eutectic textures (explain very briefly with simple binary diagram) (bainite faster cooling
more feathery than pearlite, intergrowth of ferrite and cementite from austenite,
reveals cooling history, affects hardness)
annealing, deformation structure (cold working, develop fabric like foliation, hot
working, annealing, develop twinning, can anneal out twins or deformation
structures, changes grain size).
Particle identification (Mineralogy or Fossils)
Thin section (30microns thick) or polished section (for metals and ore minerals that are
opaque)
Petrographic microscope: Polarizer produces plane (not plain) light. In crystal exposed
to electromagnetic field by atoms, resolves light into two planes, with light vibrating in
different directions. Because vibrating in different directions they travel at different
speeds. This has 2 effects, 1) refraction difference (Calcite rhomb), 2) interference
colors (2 are resolved back into one by analyzer lens).
Amount out of phase is unique to each crystal, so can be used to identify minerals.
When the polarized light exactly matches one of the directions in the crystal, all light will
stay in that plane. Then it is cancelled by analyzer lens and the crystal goes to extinction.
Isotropic minerals always dark because they do not break light into the 2 planes, so it
always goes through in the same plane as the polarizer, which is perpendicular to the
analyzer. (e.g. garnet).
Clues to identify minerals: grain morphology, cleavage planes and angles, color,
pleochroism, interference colors.
Point Counting: Can assess grain size distribution, or mineral proportions
Quantitative analysis: measure angles of extinction, optic figures, refractive index (by
optical oils or by comparison).
Show calcite birefringence.
Look at some thin sections with scope and camera.
Reading Geochemical Fingerprints
Review for first exam
Note: More than a "vague idea" is necessary for each of the following. You will need to
have a thorough understanding of each, and be able to use that understanding to solve
problems.
I) Examples of geochemical fingerprints in Archaeology
Key Idea to Understand: Geochemistry is valuable in a variety of ways to puzzles in
archaeology or the environment, because it provides a fingerprint identifying sources or
changes through time, and because it helps us interpret the development of technological
processes.
Key thing to be able to do: Be able to explain what geochemistry revealed in each of
the examples given, or interpret what particular geochemical information revealed in each
case
II Principles of geochemical differentiation
A) Petrologic and ore-forming processes.
Key Idea to Understand: understand what partitioning is, the conditions that
affect it, and the implications for chemical variations in natural materials. Understand
Gibbs Free Energy equations and equilibrium constants.
Key thing to be able to do: Be able to predict and interpret geochemical trends
within the context of simple partitioning problems. (e.g. if magma is crystallizing,
partition coefficient for Yb is less than one, how does concentration change in the
residual melt?) Be able to apply Gibbs Free Energy and equilibrium constant to
predicting the direction a reaction will go if a parameter of the environment changes.
B) Climate/weathering/Soil forming processes
Key Idea to Understand: Understand the implications of Eh and pH on mineral or
species stability in the environment. Understand the relationship to Gibbs Free Energy
(at a conceptual level).
Key thing to be able to do: Read a Eh-pH diagram in some simple way (e.g. tell
me what reaction would occur if I changed Eh or pH.
C) Isotopic differentiation
Key Idea to Know: Know what stable and unstable isotopes are, and understand
how each can be used to learn about archaeological or geological events or materials.
Key thing to be able to do: Be able to interpret isotopic data to derive an age (for
the examples of an imaginary K-Ar analog, 14C, and Rb/Sr that we did).
D) Statistical Clustering
Key Idea to Understand: Understand the concept of variation in data, what causes
it, how it can be evaluated numerically, and its implications for our interpretation of data.
Key thing to be able to do: Be able to assess whether a particular item belongs to
a sample, and whether two different samples are in fact a single larger sample or are
different.
Key thing to be able to do: Be able to construct or interpret a two-element
variation diagram
III) Analytical tools and methods
A) X-ray methods
Key Idea to Understand: Understand the concept of using X-ray emission or
absorption to analyze materials (especially how it distinguishes elements). Understand
the difference between X-ray diffraction and X-ray fluorescence.
Key thing to be able to do: Be able to explain the key parts and function of an
electron microprobe. Be able to explain the theoretical concept of the generation of xrays and how this reveals composition. If I give you data for an analysis, along with data
for a standard, be able to tell me the actual concentration (ignoring matrix corrections,
which we didn’t talk about!).
B) Non-X-ray methods
Key Idea to Understand: Understand how properties of materials can be
capitalized upon to reveal all kinds of stuff about those materials.
Key thing to be able to do: If I give you a list of physical properties of materials,
and a 2nd list of analytical methods, be able to match them up.
E) Petrographic Analysis (we didn't get to this one, so won't be on exam)
Key Idea to Understand: Understand how the crossed polarizing lenses turns a
microscope into an analytical tool
Key thing to be able to do: Be able to explain what particular features seen under
a microscope would tell us. Or, going the other way, what feature of a material would
tell us some particular information.
Begin Part II, Applications in Archaeology.
I will follow text fairly closely, interpreting it for you. You can interpret too, catch me in
mistakes.
GLASS
What is glass?
Amorphous vs crystalline
cooling rate: glass vs crystals
Composition effects crystallization (melting) temperature and propensity to crystallize.
Effect on melting T: More pure material (fewer components or higher proportion of one
or two results in higher melting T. Often somewhat equal proportions of 3 components
yields significantly lower melting T. Also, most natural rock materials have relatively
high melting temperatures (900-1300C). Extra amounts of components such as Na and
Pb can significantly lower melting T.
Effect on viscosity, workability, and tendency to crystallize:
Network formers vs network modifiers.
formers = Si, Al. Explain 3-D network formed by interlocking silica tetrahedral.
modified by network modifiers, such as Ca, Na, Pb, Mg,
pure SiO2 most prone to glassify, but melting T~ 1700C, well above ancient
technological ability.
Composition:
SiO2: main component of glass, called former. (~60-70% in early glass)
Na2O: Decreases T, called the modifier or flux (~10-20% in early glass)
CaO: Prevents Na from leaching out by water, and reduces T, called stabilizer (~5-10%
in early glass.)
Introduce and explain idea of ternary diagram.
Na and Ca Components added as carbonates, CO2 lost during melting.
Source of Alkalis (Na, Ca, and impurities)
Most natural rock will have too much Ca and not enough Na, resulting in high melting T.
Halophytic Desert plants (Salicornia and Salsola) (grow in saline, alkaline soil of arid
regions, rich in alkaline elements) contain both Ca and Na. Burn, organics lost as gas,
Ca, Na, Mg remain in ash. Generally, these plants had high Mg and K impurity
compared to later sources of Na (although some plants found with lower Mg).
Later source of Na was trona (a sodium carbonate, evaporite mineral). Had much lower
Mg, K impurity. (about 8th century BC)
HOW WILL THIS SHOW UP ON VARIATION DIAGRAM?
(look at variation in impurity with Na)
Mg impurity could also be added with Ca (e.g. some in shells, a lot in the mineral
dolomite ((CaMg)CO3).
HOW DISTINGUISH WHETHER MG IN THE GLASS WAS COMING FROM THE
NA SOURCE OR THE CA SOURCE?
on basis of which correlates with.
Ca source: Sometimes a lot of CaCO3 in sandstone, or sand, as shells, or cement
between grains. Shells from beach, limestone, dolostone (see above).
Si source:
Quartz (SiO2). Sand, sandstone.
need to find ones with low impurities, particularly Fe which occurs both as cement in
sandstone and in minerals such as olivine and pyroxene, amphibole and biotite and some
clays. (last more common in sandstone)
Common mineral impurities (those that survive weathering process): feldspars, (K, Na,
Ca, Al, Si), titanite and sphene (Ca, Ti, Si), chromite (Fe, Cr), epidote (Ca2(Al,Fe)3SiO4)
Colorants:
Color (absorption of specific wavelengths (by outer shell electrons, analogous to AAS
etc).
and Opacity (crystalline materials that absorb all wavelengths.
effected by elements present, oxidation state, crystallinity.
oxidation state function of fuel used, T, how long in furnace, design of furnace. (note:
oxidation state does not appear to always be controlled by furnace conditions, but by
internal equilibrium in the glass according to what species are added)
Fe++ = very dark, brown
Fe++ and Fe+++ = pale green
Fe+++ = pale yellow, sometimes red
Mn oxide also used as decolorant (to get rid of faint green of Fe) by oxidation of Fe to
+++, reduction of Mn to ++, both lighter colors
Mn+++ = purple, violet
Mn++++ = pink
Cu+ = bright sealing wax red or dull brown red. (bright from enamel, cuprous oxide
precipitate, growing as dendrites in the glass, requires heat treatment with Pb in glass)
Cu++= turquoise bluegreen
Pb = yellow, also is a softener, easier to cut
Co = blue
Sb = white, produces opacity by crystallizing Calcium antimonite, giving opaque colors
provided by other elements. (e.g. yellow lead antimonite crystals) (note detailed shape of
crystals, degree of dendricity, reveals something about heat treatment needed to grow
crystals) Sb also used as decolorant (to get rid of faint green of Fe).
Sn = opacifier used later than Sb (after 2nd century BC). (e.g. lead stannite crystals)
As = opacifier, used in 17th century
(devitrification in general can produce opacity)
MANY POTENTIAL SOURCES FOR EACH COLORANT. HOW DO YOU
IDENTIFY ACTUAL SOURCE?
by correlation with other elements often with Co in source (Cu, Ni, Fe, As, Zn, Pb, Mn)
(Correlation implies the export of Co-rich colorant from Islamic world to High Medieval
western Europe)
Glass making process:
1) selection/preparation of raw materials (such as sand, Na-mineral, plant ash,
limesource etc)
2) fritting (repeated heating/partial melting to drive off gases, CO2, S2 etc) (frit formed
of mixed ingredients)
3) further mixing, possibly adding colorants, melting
4) working the glass
5) annealing (affects structural properties, prevents deformation structures/stress,
brittleness, tone etc, but also used for crystallization-opaqueness)
Glasses:
Soda-Lime-Silica glasses (Na2O-CaO-SiO2)
High MgO (HMG) 1500-800BC (alkaline desert plant Na source)
Low MgO-High K2O (LMHK) (Europe) 1150-700BC (new raw materials)
Low MgO (LMG) 800BC-1000AD (Roman) (mineral Na source)
High Sb (antimony) 600BC-200BC (early “opacifier”)
High K2O-High BaO (Chinese Han Dynasty) 206BC – 221AD
High MgO (Early Islamic) 840 –1400 AD (various halophytic plants alters
amount of MgO)
High Al2O3 (India) 0-1000AD
And many others (depends on how picky you are in defining a glass as a new
group, but these represent significantly new source materials)
Lead-Silica glasses (PbO-SiO2)
Islamic 1000-1400AD
Important Glasses in History
Glass making flourished mid 2nd millennium BC, revived in Mesopotamia 9th century
BC.
2nd great flourishing during Roman era, centered in Syria –Palestine- Alexandria 3rd
century BC – 500 AD (Classical Greece had no contribution to glass).
Egyptian Cobalt blue (1600-1300BC)
(HMG)
Silica source was crushed quartz, not sand (how would you tell? …. low Al, no Fe, Ca
correlation with Si?) However, much of Ca source may have been sand, so this doesn’t
completely compute (conflict in my sources)
Co source had aluminum in it (how would you tell?……Al-Co correlation)
Glasses of period from various locations show large variations in Ca, Mg, K, Al – may
indicate wide variation in source/process, Some low Mg indicate mineral Na source.
variations in colorants (local) may indicate local industries. Variations also indicates
sophistication and complexity of glass industry by 14th century BC.
Variations (e.g. LMHK in vicinity of Po) can also indicate isolation from wider
technological society.
Lack of variation can indicate secretiveness and ritual in glass industry.
Not shown in figure, a cobalt blue Egyptian glass also found with low Mg.
Tell Brak (Syria)
Pella (Mesopotamia)
Tell el Armana (Egypt)
2 technologies: LMG and HMG
(can infer sources for mineral for LMG – Wadi el-Natrun in Egypt (name, Natrun
indicates Na mineral, implies trade, or centralized manufacture)
enameling: metal oxides used as colorants bond with metals, allow glass-metal bonding
if in sufficient concentration. (Tutankhamen funeral mask 1350BC enameled)
Roman Glasses:
(LMG)
Technological innovations:
Portland cup: overlay of softer Pb rich glass on LMG glass. Pb easier to cut, lower
melting T so stays soft at lower T. Glasses have to match thermal expansion properties
enough to not cause stress fractures etc.
Analysis of glass composition (blue body) 65.7%SiO2, 16.2%Na2O, 9.0%Na2O,
1.0%K2O typical of roman glasses once used to support it not being a forgery.
Lycurgus cup: Colloidal gold-silver alloy in suspension produces different reflection
color (pea green, due to reflection off silver of exact size) than transmitted color (wine
red, related to dispersion by gold particles of correct size). Size for this effect around 2070 nm Technology for creating dispersed particles of correct size still not known.
Discovery of glass blowing. around 30BC near Sidon?
Glass for windows
Cutting wheel.
Cased glass (see Portland cup as simple example, but 6 or more layers, cameo etc.)
Dichroism (see Lycurgus cup)
Reading Geochemical Fingerprints: LAB #2 EMP Analysis
Each person will schedule a time on the electron microprobe to analyze two
points for a single element (or one point for two elements) plus analyze a
chemical standard (or the standard analysis may be provided).
Each person will also acquire a Backscattered Electron image of a sample.
If you want to do your own sample, you must make arrangements to have
the sample polished and carbon coated at least 2 weeks prior to the lab.
For each analysis, calculate
The net counts per second per nanoamp (peak cnts/(seconds nanoamps) average background cnts/(seconds nanoamps))
Analysis 1 =
Analysis 2 =
Concentration of element in each analyzed point (must consider the standard
and what its net counts per second per nanoamp are as well as the
concentration in the standard. We won't consider "matrix" effects which
consider how different elements interact with each other. So concentration
will = concentration of standard times counts per second per nanoamp for
the unknown point divided by the counts per second per nanoamp for the
standard.
Analysis 1 =
Analysis 2 =
Calculate the uncertainty in the analysis. Remember that 1 uncertainty
from counting statistics is square root of counts. Percent uncertainty is
100% times square root counts/counts. Multiply the percent uncertainty
times the cnts/sec-nA for each of background and peak. Are the background
and peak signficantly different from each other? Total uncertainty taking
into account uncertainty in the background is square root of the uncertainty
in the background (done like uncertainty in the peak) squared plus the
uncertainty in the peak squared. Divide this value by the net counts times
100%--this give the percent uncertainty in the concentration. You can
multiply this times the concentration to get the uncertainty in the
concentration.
Analysis 1 =
Analysis 2 =
For each concentration, tell me whether it is significantly different from 0
(that is, is the analyzed element present at detectable levels)
Analysis 1?
Analysis 2?
And whether the two analyses differ significantly from each other.
Comparing 2 analyses.
Schedule:
November 13
8:00-9:00 am _______________________ ________________________
9:00-10:00 am _______________________ _______________________
10:00-11:00 am ______________________ _______________________
2:00-3:00 am ______________________ _______________________
Reading Geochemical Fingerprints: Alternate 2nd statistics LAB #2
The purpose of this lab is to think about and understand how various sources of materials
affect the composition of ceramic or glass materials, and how that can be interpreted with
statistical tools.
Set up a spread sheet to calculate the compositions of the matrix of composition
described below. Each composition is a mixture of material from three different sources,
only the proportions of each source change. The compositions are as follows:
MgO
Yb
Ni
Sr
Lu
Source 1
1
6
3
1
7
Source 2
2
1
3
5
6
Source 3
3
4
6
2
1
The attached sheet may help you set up this spread sheet.
Composition
comp 1
comp 2
comp 3
comp 4
comp 5
comp 6
comp 7
comp 8
comp 9
comp 10
comp 11
comp 12
Source 1
5%
5%
5%
5%
10%
10%
10%
15%
15%
15%
20%
20%
Source 2
5%
10%
15%
20%
5%
10%
15%
5%
10%
15%
5%
10%
Source 3
90%
85%
80%
75%
85%
80%
75%
80%
75%
70%
75%
70%
Now, consider the correlation between Yb and Ni. Graph Yb vs Ni (in the spread sheet
program). Are they correlated (using your eye-evaluation of the graph)?
Do a linear regression of Ni = A + B(Yb).
Are they correlated (using statistical tests)? (The R2 value is a measure of what fraction
of the total variation in Ni is explained by the correlation to Yb. You can also examine
the value of B, as well as the uncertainty in B, and ask if the value of B is significantly
different from 0. A value of 0 means that there is no correlation between Yb and Ni).
Actually, Yb and Ni ARE correlated, but that correlation is masked because Ni also
varies with MgO, hiding the correlation to Yb.
You can see this by doing a different regression. Do a regression to the expression
Ni = A + B(Yb) + C(MgO)
Again examine the value for R2 (which is now 1 because we have created a fake set of
data that must be exactly correlated, thus all of the variation in the data is explained by
the correlation). Also, examine the values for B and C and whether those values are
significantly different from 0 (that is, they are more than 2 sigma different from 0).
Now let’s consider a harder problem. We know that each composition is in reality a
mixture of three different compositions. But in the real world, if we find some pottery of
glass that is made of materials from three different sources, we may not know that, and
we certainly won’t automatically know what each of those sources are. How can we
extract information about the original sources if all that we have is the final mixtures?
A principle component analysis or a factor analysis allows you to extract from a set of
data what principle components or factors can explain the variation in the data. Thus, it
is well suited to figuring out something about the basic components that went into
making a piece of glass or pottery, even if the original component no longer exists as a
separate material. This technique uses the VARIATION in a set of samples (such as
glass or pottery) to INFER what the components used to make the pot were.
Using SAS, determine the principle components for the data set derived above. A sample
program is given here:
DATA GLASS SIMULATE;
INPUT SAMPLE $ MGO YB NI SR LU;
CARDS;
comp1 2.85
3.95
5.7
2.1
1.55
and the rest of your data.......
RUN;
PROC PRINCOMP DATA=SIMULATE;
VAR MGO YB NI SR LU;
RUN;
Part of your results should look like this:
Eigenvalues of the Correlation Matrix
PRIN1
PRIN2
PRIN3
PRIN4
PRIN5
Eigenvalue
Difference
Proportion
Cumulative
2.91650
2.08350
0.00000
0.00000
0.00000
0.83299
2.08350
0.00000
0.00000
.
0.583299
0.416701
0.000000
0.000000
0.000000
0.58330
1.00000
1.00000
1.00000
1.00000
Things to notice: ‘Proportion’ indicates the proportion of the variation in the observed
compositions that is ‘explained’ by that particular component. In this case, only the 1rst
2 components explain any significant part of the data. Although you know that your
compositions are really a mixture of 3 components, there are only 2 principle components
because the principle components are better thought of as a line (or a vector) between two
compositions. Therefore, the first principle component represents the difference between
the first of your physical components (source 1) and the most important of the other two
components (which is source 3; that source making up a larger fraction of your mixtures).
The second principle components represents the difference between source 1 and source
2.
Another part of your results should look like this:
Eigenvectors
MGO
YB
NI
SR
LU
PRIN1
PRIN2
PRIN3
PRIN4
PRIN5
0.551131
0.011401
0.581719
-.122396
-.585446
0.234045
-.692661
-.079192
0.677489
-.013489
0.401943
-.003292
0.418822
-.077125
0.810599
-.083347
0.652293
0.217916
0.721166
0.000000
0.687730
0.307562
-.657596
0.000000
0.000000
Since you already know that only the first 2 principle components explain a significant
part of your data, you only need to look at them. Positive values indicate that the primary
source provides more than average amount of that component (in keeping with thinking
of the components as being vectors). Negative values indicate that the primary
component provides less than average amount of that component. A value near 0
indicates that the main component provides an average amount of the component. Look
through your results and think about which physical components that the Principle
Components 1 and 2 correspond to. Remember, if you were doing this for real, you
wouldn’t already know what the physical components are, and you would have to infer
them from the principle components.
Report: I want you to turn in your graphs, regression results, and principle component
results, plus a paragraph explaining how your principle components correspond to the
actual sources.
A
B
C
D
E
MgO
F
Yb
G
H
I
Ni
Sr
Lu
source 1
1
6
3
1
7
source 2
2
1
3
5
6
source 3
3
4
6
2
1
proportions
source 1 source 2 source 3
1-A110.05
0.05B11
comp 1
0.05
0.1
0.85comp 2
0.05
0.15
0.8comp 3
0.05
0.2
0.75comp 4
0.1
0.05
0.85comp 5
0.1
0.1
0.8comp 6
0.75comp 7
0.1
0.15
0.15
0.05
0.8comp 8
0.15
0.1
0.75comp 9
0.15
0.15
0.7comp 10
0.2
0.05
0.75comp 11
0.2
0.1
0.7comp 12
+E$6*$A11+E$7*$B1 +F$6*$A11+F$7*$B11 +G$6*$A11+G$7*$B1 +H$6*$A11+H$7*$B1 +I$6*$A11+I$7*$B
1+E$8*$C11
+F$8*$C11
1+G$8*$C11
1+H$8*$C11
11+I$8*$C11
this is row 7, col. E
Ceramics
Earliest pottery (had to recognize plastic behavior of wetted clays, importance of adding
temper, and hardening effect of firing)
Japan 10750 BC, Turkey 8500-8000BC, Ecuador-S US, 2500-2000BC
Clays change to other minerals, but temper often remains identifiable, can tell location of
manufacture, can tell source. Also, chemical composition doesn’t change much even if
get new minerals (but volatile elements can be lost in firing, and temper and processing
of clay, possibly from multiple sources, makes direct compositional identification with a
source unlikely). But mineralogy can reveal the process of pottery making, such as
Temperature of firing and duration of firing, nature of material used (tells of availability
as well as technology).
raw matierials and considerations:
clay (provides plasticity and raw material for hardening during firing), temper (influences
plasticity and provides for decreased shrinkage during evaporation of water and may
participate in firing reactions although not usually)
Clays form by weathering of other minerals formed in igneous or metamorphic rocks.
Not stable in surface environment; conditions of acidity, T , and starting composition
affect weathering and the type of clay mineral derived.
Mineralogy of Clays:
Primary constituents match primary constituents of Earth’s crust: Si, Al, Mg, O
Oxygen (think negative charge, actually often covalent) + Cations (think positive charge)
Si tetrahedral,
Al and Mg Octahedra (note different charge, different number of octahedral sites filled)
Brucite (Mg(OH2)) and Gibbsite (Al(OH)3)
Layers of tetrahedral Si tetrahedral can alternate with layers of Brucite or Gibbsite.
Stacks of the layer combinations can then be held together by other cations (K+, Fe++,
Mg++, Ca++, etc)
Also, the layer can be EXPANDABLE, allowing water inbetween the layer stacks.
Called expandable clays. Less tightly bound than the chemically bound water (OH
molecules), but more tightly bound than simply “wet clay” that provides plasticity.
Kaolinite (name derives from corruption of Chinese Kauling, meaning high ridge, a place
where the clay was mined for porcelain near Jauchu Fa.)
2 layer sandwiches (TO).
High Al (makes refractory), derives from felsic (acidic) rocks. Also, form in more
tropical climates where acidic conditions leach Mg, Fe, etc from forming clays, or
hydrothermal conditions (hot, acidic). Provides white color
Smectite (Montmorillonite (Mg in Al slots), Beidellite (some Al in Si slots), Nontronite
(Some Al in Si slots and Fe3+ in octahedral slots)
Expandable clays, responsible for most water absorption, most of cation exchange
capacity (in soils), but means for pottery they are less “pure” have more Na, K etc and
can take on colorants, and responsible for most of expansion-shrinkage with wetting and
drying
Are TOT (three-layer) clays, like micas and Illites
Ca, Fe, Mg are primary cations: Derive from weathering of mafic (basic) igneous rocks
Illite
Some nomenclature problem, refers to hydrous micas. Like Mica but more K+ replaced
by Ca, Mg, Less Al for Si substitution on tetrahedral (~15% as compared to 25% in
muscovite), and contain more water in structure.
Unlike smectites, octahedral more strongly bonded, charge imbalance exists in tetrahedral
exterior to the “sandwiches”, so aren’t asexpandable (still can adsorb water between
layers and expand, just not as much.
Also are some Non-layered silicate clays
Plasticity affected by expandability of clays, but also by particle size. Small particles
more plastic (surface water higher per volume acts as a lubricant between plate-like
grains, and holds together by surface tension:
3 types of water, bound, expandable, surface of particle).
coarser clay is “stiffer”, less plastic (can test by biting, grittiness)
Temper can be added to improve shrinkage/thermal shock properties: straw, sand, shells
etc.
Shaping and considerations
pinching (shaping ball of clay), slab building (pressing slabs of clay together), coiling
(building shape with coils and pressing together), molding (pressing into molds), pottery
wheel, and further beating, cutting, shaping.
Firing and considerations:
T, duration, oxygen
reducing = organics not consumed, Fe = ferrous = dark color.
oxidizing = oxidized Fe, red, pink, orange
(note: cream, yellows require higher T and presence of Ca)
Terra cotta, earthenware ~900C, possible with wind-aided fire
loss of chemically bound water at lower T, mineral metamorphism, vitrification (strength,
loss of porosity)
Loss of pore water
loss of adsorbed water
volatilization of organics
loss of chemically bound water and breakdown of carbonates and sulfates and sulfides
all above with volume decrease
(below 900C, temperature of open fire)
New Minerals (metamorphism) (often with volume decrease)
Partial melting (vitrification)
Duration at Temperature affects extent of metamorphic change (extent reaction continues
to completion) and crystal size.
example of Kaolinite
with increasing T: Kaolinite metakaolin spinel mullite cristobalite(SiO2 with
new crystal form so new volume characteristics)
(refer to phase diagrams for ceramists)
Temperature of transitions depend on composition (impurities decrease transition T
often). Also, composition effects phases that you get (montmorillonites for example have
greater variation in composition and become different minerals).
So examination of mineralogy can yield info about firing process, both T and duration.
With increasing T, can get sintering (more or less solid-state alterations that fuse particles
together) and vitrification (liquid phase present, partial melting). This reduces volume
(elimination of pore space), increases strength.
Fluxes added can decrease melting T, decreasing T of vitrification. Temper can also act
as flux.
Temper changes with firing:
Quartz, goes through phase transition, with volume changes, may react chemically with
clays. alpha to beta at 573C (2% volume increase), Beta to tridymite at 867C, tridymite
to cristobalite at 1250C (slow kinetics, so indicates duration at T)
Feldspar: may act as flux (melt) dur to Na and K present, Ca feldspars higher melting
Calcite: loses CO2, volume change, Wollastonite formation at T above
1000C (a pyroxenoid), below this T, CaO (hydroscopic) absorbes water
over life of pot causing sharp volume increase and spalling of pot.
Phase diagrams for ceramists, 1964
Firing methods:
Glaze
Glazes appear in Egypt in 4000-3000BC time. Glazes used widely in Mesopotamia after
about 2000BC.
Lower melting T addition to exterior, producing glass finish.
may be 1 or 2 step, if 2, first firing called bisque firing, most of shrinkage occurs.
Simple glaze, just add salt, Na reduces melting T of exterior of pot.
Pb glazes, similar idea.
Key idea: thermal expansion properties relative to ceramic (can get crazing by
differential shrinkage of glass glaze (clay normally shrinks less than glass, remind of
volume-cooling diagram shown for glass).
Refractory Al can produce high-T glazes. Pb, Alkalis, lower T glazes.
In general, glazes have higher Al than glass. higher melting T (doesn’t run off pot),
matches composition of pot better (sticks to it),
According to book, chemistry not yet used a lot for evaluating ceramics, problems
include loss of volatile elements, multiple sources, mixed sources, etc. Although these
problems can be overcome and probably will be in the next few years. Also, chemistry of
glazes can reveal some significant changes with time and technology.
However, look at petrography clues for a couple of examples.
Glaze, lower melting T, different composition, glassy finish, provides colorants,
oxidation can effect color (e.g. spectroscopic analysis of glaze on pg 179 in book bluishgreen color more reducing, ginger yellow color more oxidizing due to more ferrous Fe is
correlated to Chinese dynasty). Glaze in this picture is Pb-rich, making bright in
backscatter (atomic-mass-dependent).
slip, wetter (thinner) clay added to smooth pot, better finish. often select finer fraction,
so smaller crystals. sharp boundary with body distinguishes this from finger-smoothing
such as with a potters wheel.
Body: melted areas rich in flux (Pb in this case, which makes brighter in Backscattered
electrons which reflects atomic mass). Voids, mineral grains mainly silica, compositions
including Mg, Ca, Al can reveal use of clays in addition to quartz.
see overhead. fig. 4.44
Temper used (identify mineral grains petrographically):
Get idea of trade, distance, correlate with political/social groupings. Note distance of
about 30 miles is consistent, as is the gradual, rather than sudden change in appearance of
mineral grains from a particular source. Gives clues to distance scale of trade, there is
trade (otherwise change in use would be sudden, not gradational), size of social/trade
units, and indication that trade is “down-the-line” exchange system for traded wares. (pg
153-154) Down the line from Renfrew 1975, pg 308 in book, transmission of goods from
one settlement to another in a linear fashion.
fig 4.23 in book.
Geochemistry Puzzle Assignment #4: Is it Ceramic or Stone puzzle
Basalt-like stones were used in 2nd millennium Mashkan-shapir in Mesopotamia for
construction and grinding grain. Were these vesicular gray-black stones quarried at some
unknown location and transported to the region, or were they somehow manufactured
locally from other materials?
(This puzzle comes from Stone et al, 1998, Science Vol 280 pg 2091.)
We will look at only 2 elements for this puzzle K and Fe, although more are reported in
the journal report. The way to begin is by plotting the ranges for natural and known
samples on a graph, and comparing those ranges to the value for the stone from
Mesopotamia.
What I want from you is the graph showing the results and four sentences explaining the
source of the building stone.
Typical ranges for Natural Rocks:
K
Hawaiian basalt
0.08-1.3
Shale/clay
1.33-2.81
Sandstone/sand
0.32-2.16
Granite
2.85-4.45
Limestone
0.04-0.61
Fe
7.42-10.7
1.04-8.56
1.4-4.2
1.54-2.46
0.3-1.46
Specific rock or sample values
K
Minnesota Basalt 0.71
Sandstone
1.10
Arkose sandstone 2.32
Shale
2.70.6
Fe
10.22 Miller, MN Geol Survy Guidebook 20
0.99 Pettijohn et al.
1.59 Pettijohn et al.
4.81.9 Beus
Mesopotamia
basalt
0.08-0.58
6.7-11.20 Stone et al.
Mesopotamia
building stone
1.34
5.10
Stone et al.
Silt from river
near
Mashkan-shapir
1.33
5.19
Stone et al.
Metals
Examples of ore-forming processes:
Cu
Fig 5.3.
Go through leaching oxidation/reduction concentration process, explain formation of
Gossan,
Native Cu from secondary reduction of oxidize Cu by hydrothermal or weathering
process.
Au (placer, explain density, differentiation)
PGE with Au often signal source of placer as Au occurs in quartz veins, pyrite deposits
(highly incompatible element, except in metals, must Au in core) (granites, hydrothermal
veins), but PGE don’t. However, PGE also concentrated in placer deposits due to
density.
Cu, Au, Fe occur as native metals (Fe in meteorites)
Others as oxides, sulfides, carbonates, chlorides (silicates don’t usually make good ores,
not sufficiently concentrated, too hard to get out).
Cu and Fe not used extensively until learned to smelt from oxides, sulfides, etc.
Properties of Metals:
Maleability and ductility (ability to spread into thin sheets, ability to put in thin strings)
brittleness.
Strength vs hardness (resistance to force, versus how easily scratched or how long
maintain an edge, also hardness sometimes refers to resistance to force).
Elastic, plastic, and work hardening.
note made when I am too tired to fix: stress and strain are reversed on the diagram.
illustrate how change in strength shows up on diagram.
Important Metals:
Cu: more easily reduced, why often native and why first to be smelted.
beads etc 7th millennium BC, smelting by at least 4500BC. By 3rd millennium BC
widespread smelting by slag process (molten slag, not solid). Cu usually as sulfides or
carbonates ores. Very striking blue and green colors make ores easily noticed.
Fe: used by ~2300BC, widespread by 1200BC (important in Philistine-Hebrew conflict).
Ores usually oxides, hydroxides, carbonates
Au: Less work-hardening than Cu, very malleable and ductile. Native Au, but not a lot
available, so have small objects.
Ag: 7th century BC, Ag from Pb ores often, separated by smelting and cupellation.
Pb: Low melting points so is easily smelted. Made PbS bracelets, not smelted, by 6th
millennium BC. Pb used to alter properties of other metals, and in glass etc. Increases
fluidity of Bronze, used ~2000BC. PbS, PbCO3. Very striking silver, dense ore makes
easily noticed.
Sn: Used with Cu (Bronze). 3000BC. Harder than Cu, more easily cast due to lower
melting T, degassing advantages. Ore is SnO2, cassiterite.
phase diagram
Zn: used in 1500’s for coins, but also as alloy with Cu (Brass) in first century BC.
yellower than Bronze, more like gold. Zn increases strength from pure Cu.
Processing of Metals:
Beneficiation (crushing and sorting)
can also include roasting (drive off CO2, SO2, Cl), and washing.
Smelting (melting and reduction)
heat to melting T (varies depending on metal, also want to melt silicates or other
materials),
reduce (charcoal)
e.g.
Fe3O4 +2C  3Fe +2CO2
may be multiple steps, oxidation followed by reduction.
e.g.
Cu2S + 2O2  2CuO + SO2
CuO + CO  Cu + CO2
or
2PbS + 3O2  2PbO + 2SO2
PbO + C  2Pb + CO
Silicates and other gangue melt to slag, metals partition into reduced metal, different
density liquids separate (early smelting involved gangue not completely melting).
gangue may be viscous (contains SiO2!), or not melt, and can add flux to decrease
melting T of gangue.
Cupellation:
done in cupels, small ceramic containers
e.g. Pb-Ag separation
smelting with Pb, reduced Ag partitions into Pb metal
oxidation of Pb
Pb and Cu, Zn, As, Sb (antimony), Bismuth partition into oxide
Au tends to go with Ag.
Cementation:
solid-state partitioning process
e.g. Au-Ag
Au-Ag alloy + NaCl  Au + AgCl (+Na as vapor?)
Iron and Steel:
Iron was soft, not necessarily improvement over Bronze. But steel transformed
technology. Steel depends on amount of C, which lowers melting T and increases
hardness.
Wrought iron
Steel
Cast iron
Phosphorous Fe
<0.08% C
0.2-2% C
2-5% C (and often 1-3% Si)
0.2-0.4% P (P doing work of C, used in Africa ~500BC)
Wrought iron: repeatedly hammered and annealed to remove the silicate slag (molten at
hammering temperatures). Also oxidizes carbon and lose significant iron to oxidation.
process changes crystal size and shape along with dislocation density, changing hardness
properties.
Steel: discovered prior to 1200BC. Heat iron with glowing charcoal (Was not realized
that C was the key alloying agent until 1800’s!)
Steel much harder, holds a sharp edge much better. Also stronger. Tempering the steel
hardens it further (generating dislocation in structures, and smaller crystal size which
disrupts slip planes). Steel would be annealed (heated to remove some of dislocations
and grow crystals) to decrease brittleness.
Methods of adding C: carburization (like the glowing charcoal method above), is a type
of cementation (solid state diffusional process). Also called case hardening. This
process developed soon after steel in late 2nd millennium. Crucible steel formed when
high C cast iron and low C iron melted together (fusion process, not solid state). This
process took place much later (1rst century AD?)
Cast iron: Higher C lowers melting T even further (good for casting). A key phase of
iron, austenite, never forms. Can get cementite, very hard and unworkable, by heating
can oxidize C and make more malleable. With more Si (grey cast iron rather than white
cast iron), get graphite which makes more workable.
Understanding steel:
Austenite, martensite, pearite, bainite, cementite,
To understand these aspects of steel, need to understand phase diagram (also, cooling rate
is a factor to talk about as go over phase diagram).
Go through some puzzles: What would you get if…….
Austenite: a crystal form of Fe+C that forms in the temperature range above 738C and
with less than 2% C, but that is unstable below that temperature.
ferrite: the crystal form of pure iron, or iron with less than 0.08% C in it.
cementite: a crystal that contains iron-C in the proportions Fe3C.
pearlite: an intergrown mixture of ferrite and cementite that forms when austenite cools
below 738C.
Bainite: an intergrown mixture of ferrite and cementite that forms when austenite cools
below 738C, but with faster cooling and more feathery crystals than pearlite.
martensite: rapid quench (faster than bainite) prevents diffusion and get a metastable
transformation of austenite to martensite. rapid quench results in needle-like crystals, or
plate-like. (hard and brittle)
Many different manufacturing processes can show up in textures seen under microscope.
Interesting language tidbit: The blob of smelted iron is called a bloom because the ironslag-charcoal blob was thought to resemble a flower.
Some Stories Told by Metal:
Composition and coinage.
politics and economics
Debasement of coinage repeated as economies struggle, costs of particular metals go up
(or availability lost due to changing alliances etc)
Identifying forgeries…..related to refining techniques available
Horrific story: in 1124 Henry I of England had all his miners castrated and right hand cut
off, accusing them of debasing coinage by reducing Ag. Modern analysis reveals there
was no significant change in Ag concentration from 1050-1125. Henry must have
wanted someone to blame for some economic difficulty.
Cu-Sn and the Liberty bell.
phase diagram, softness, and brittleness.
1751 Whitechapel Foundry of London commissioned to make Liberty Bell
Optimum known to be 77%Cu, 23%Sn
Broke on first ring
John Stow (local founder) asked to recast the bell
bought Cu and added to it. Too soft, the bell had an unpleasant sound
John Stow recast again, analysis reveals avg 67.1%Cu, 26.9% Sn and heterogeneous
(25.2-30.16%Sn). So added more Sn, but cast in batches because had no ability to make
such a large cast (he made horse bells and rivets). 1.4%Zn and 3.25%Pb suggest he may
have used scrap metal to adjust the Cu concentration.
Cracked again in 1835 after ~60 years.
Pb isotopes, and principle components.
correlated proportions of “real” chemical or isotopic components.
problem that no single source used, mixing, reuse, etc complicates sourcing
Pb isotopes a function of age of ore deposit, environment of ore formation, source of Pb
for ore, multiples sources for ores used, subsequent recycling (alloying, reuse).
Pb 204 nonradiogenic,
235
U, 238U, 232Th decay to different isotopes of Pb, 207Pb, 206Pb, 208Pb. Have different
half lives, so age affects proportions of Pb isotopes. But also, U and Th will be
differentiated in different Pb reservoirs, so each mine will be unique. This relationship
has incredible utility in geology, marine science, dating the earth, fingerprinting, finding
how long its been since the crust formed, archaeology, etc.
Principle Component Analysis
One component has a certain set of proportions of Pb isotopes. Another component has a
different set of proportions. Can identify mixtures with varying amounts of those
components, and, in fact, can identify the components even if don’t have a pure example
of either component.
Pb concentration in Greenland ice.
Reading Geochemical Fingerprints: LAB (extra)
Making Metallographic Polished Samples
Bring a piece of metal to polish. You need to know something about the metal (it’s
composition and what kind of metal it is). This should not be large (less than ½” in its
maximum dimension, although we may be able to cut larger pieces.)
For example: It would be nice to get samples of the three types of iron, wrought iron,
steel, and cast iron.
Step #1: Pot the sample in epoxy in a 1” bakelite round. Allow epoxy to harden
overnight.
Step #2: Expose the metal, and begin polishing it using a series of increasing finer gritsized corundum grinding papers (e.g. grind to 600 grit through 4 different grit sizes). Use
water as a lubricant. You can check the sample under a microscope to see if you are
getting rid of the larger scratches created in the previous larger grit size. In general, you
should polish using a rotating motion and keeping the sample perfectly flat. However,
for the last few seconds you can go in only one direction. This will create train-trackscratches that make it easier to spot unpolished scratches left over from the larger grit
size.
Step #3: Polish the metal further (to 1micron grit size) using 6micron and 1 micron
diamond paste on small polishing clothes. Polishing oil is used as lubricant. The
diamond paste is, of course, very expensive, so don’t waste it. With care, multiple uses
can be made of a single application of diamond paste. It is important to keep particles of
dust off of the polishing cloth because it may cause scratches.
Stone:
Source or provenance. Distance of migration/trade. Activity in particular quarries
through time.
Characterization through
color or general visual appearance
mineralogy (microscopy or XRD)
composition (XRF, INAA, etc)
Flint: sedimentary. mostly SiO2, so often distinguish by trace components, thus INAA a
good tool. organics give dark color (flint), slight iron gives white to yellow color (chert),
and more Fe give red color (jasper). But visual color influenced by weathering, and can
vary even from a single quarry.
Often formed by secondary (diagenic) processes in chalky limestone, forming nodules or
layers. Both original rock composition and diagenic process influence composition.
Obsidian: glassy (unlike chert). is volcanic, broader range in major element
compositions possible, but still best characterized by trace elements. Differentiated by
igneous partitioning processes. Often more limited # sources than chert. Great deal of
info, can easily distinguish different sources, including individual sites/quarries and
different sections of those quarries possibly corresponding to different phases of
excavation.
Key ideas from figure: two different types of trade zone, a zone where trade good
(obsidian at least) is thoroughly mixed, and zone farther away where trade is from one
settlement to next such that occurrence decreases exponentially with distance from
source. However, book indicates only preliminary work done, result may be influenced
by more sophisticated treatment of sources etc.
Volcanic, plutonic and other stone
Can distinguish different rock types on the basis of simple mineralogy (microscopy,
XRD) or chemical composition (XRF, INAA, etc).
Story of Stonehenge (first phase, no stone, 3000BC, 2nd phase late 3rd millennium BC.
3rd phase, stone settings 2620-2480BC, remodeling 2280-1930BC.
basaltic dolerite (bluestones from 240 km to the East (Preseli Hills). None on the
Salisbury plain. (based on petrography) (1923 H.H. Thomas…Colin Renfrew estimated
would have taken 30 million man hours). more careful examination recently: looking at
chemistry, ), identified some stones of rhyolite, other volcanics, and sandstone in addition
to dolerite, come from 7 different quarry sites in Preseli Hills, up to 30km apart, but
mostly much closer together. Thorpe and Thorpe (1990, 1992) reasoned that doesn’t
make sense they brought them so far but from different quarries. Ancient glaciation
(400000 years ago) may have brought erratics to the plain. On the other hand, proximity
of the 7 quarries isn’t consistent with being brought by glaciers such a distance.
soapstone (talc + other soft hydrated minerals, easily cut)
REE useful (INAA), normalization to chondritic values and look at pattern, reflects its
history of partitioning. Spider diagram.
Marble: made of CaCO3, so C and O isotopes very useful. Elegant study of Greek
Marble sculture sources, but further study of additional sources showed more overlap.
Need to use other compositional data as well. (use overheads)
Rock Varnish (bacteria that live on energy of oxidation of Mn and other metals), changes
appearance of surface (Mn oxides), and source of C14 for dating. Rate of formation
dependent on moistness.
provides exposure age.
Chlorine 36 also provides exposure age.
Plaster of Paris, slaked lime, and cement.
Plaster to 12000BC. As way to bind (cement) objects, and architecturally by 10300BC.
Architectural use expanded by 7500BC and began using for vessels, statues, etc.
Presaged the invention of pottery.
Plaster of Paris (Eastern Mediterranean in pre-pottery times)
CaSO2 2H2O heated to 150-200C  CaSO4½H2O +3/2H2O
Lime Plaster (Mesopotamia in pre-pottery times)
at 800-900C
CaCO3  CaO +CO2 (quicklime) (remember problem of CaO in pottery)
then adding water
CaO +H2O  Ca(OH)2 (slaked lime)
Over time, the slaked lime converts back to calcite.
Ca(OH)2 +CO2  CaCO3 + H2O
By adding inert filler (sand, etc) to make mortar.
By adding clay, volcanic ash, etc can get silicates forming in the reaction. This gave
greater strength, and set under water. Called cement. (e.g. in use in Roman empire)
Portland Cement heated to 1500-1600C, make silicates and aluminates, and
aluminosilicates which HYDRATE in solidification reaction. (Rediscovered cement
which technique was lost after the Roman Empire, in 1700’s).
Geochemistry Puzzle Assignment #5:
Geochemistry of stone building materials in Egyptian Colossi
Consider the data below from the paper Bowman et al 1984, Archaeometry 26, p218-229.
The authors used Fe and Eu to distinguish the sources for the various stones. I want you
to distinguish the sources on the basis of two elements other than Fe and Eu. Plot those
two elements on a two-element variation diagram (include error bars for standard
deviation).
80 points: It will grade this part of the assignment on the clarity of the graph, including
labels on it and error bars, and how clearly it distinguishes the sources and the excluded
sources for each of the blocks: Rear pedestal, main pedestal, and upper torso.
20 points: Prior to this study, the upper torso only was thought to have been restored by
the Roman emperor Septimius Severus. What do you think about this?
Soils:
Phosphate:
Living things made of C, O, S, P, N, H
Others fairly volatile and decomposition and bacterial action remove. P bonds with Fe,
Al, Mn to form insoluble compounds in soil.
Other elements in humans: Na, K, Ca. Na and K are soluble, leach away quickly. Ca
may persist but not as much as P.
prospection spatially (transect looking for past occupation) or temporally (vertical
stratigraphic transect looking for occupied horizons.
Elevated Ca may support P. Ca can also indicate other activities (e.g. plants don’t have
as much Ca as vertebrates or shells) Fe concentrations often affected by occupation (?
due to pH effects of Ca and P?, pH less acidic with occupation). effects magnetic
susceptibility of soils.
Elevated Mg may indicate stone working.
Human remains:
Carbon isotopes can reveal diet: C3 plants (woody plants) have less C13 compared to
C12 than C4 plants (grasses, grains). (differentiated by the different carbon processing
mechanisms of plants). Animals that eat woody plants (C3) have a higher C13 ratio than
the C3 plants themselves but still low. Grazers have significantly higher C13 ratio than
the C4 plants themselves.
Figure, increase in C13 corresponds to domestication of maize.
(C13 in human skeletal collagen from NA woodlands.)
Nitrogen isotopes also differentiated by different food sources, can help identify foods.
(N14 and N15)
Trace elements: Ba, Sr substitutes for Ca in bone (hydroxyapatite). Also reflect diet.
However, unlike isotopes, chemical processes after death (diagenesis) can alter trace
element concentrations in remnant bone.
Organics valuable in other settings also (organic chemistry not my long suit!)
Residue in pottery can survive thousands of years
Original materials like sugars, fats, oils, proteins no longer remain, but breakdown
products can act as fingerprint for original organic materials. Can reveal diet etc.
Can remove from containing material (such as pottery) by dissolving it out, or heating.
Then use Gas Chromotography to separate molecules, or Mass Spectrometry.
C and N isotopes from pottery:
Looking at molecules (rather than isotopes or elements) can yield information on sources
of original fats. Fatty acids ratios can distinguish if the fat source was plant or animal
(palmitic acid vs stearic acid), and if it was marine or terrestrial animal (oleic acid vs
vaccenic acid). Usage of pots as well as diet can be ascertained.
Dyes, pigments, inks, paints also often organic, although earliest body and painting
colorants were ochre (fe oxide), galena, malachite, etc.
Famous Mediterranean purple an organic molecule extracted from murex shells
(gastropod, mollusk). (Roman empire days on East Coast of Mediterranean).
Very similar in chemical structure to indigo, produced from plants in India. Both consist
of C-H rings, bonded to O , OH, and N The purple molecule is bonded additionally to
Br.
Individual Report Sign-up:
Date
Reading Geochemical Fingerprints
Review for final exam
III) Applications in Archaeology
A) Glass
Key things to Know: what glass is, compositional components and effect of each on
glass properties, colorants, approximate timing of various developments in glassmaking, fritting
and its purpose, annealing and its purpose, effect of Pb on glass. What is unique and innovative
about the Portland Cup? What is unique and innovative about the Lycurgus Cup?
Key things to be able to do: explain with graphs and words how one might distinguish
different Na sources, how one might distinguish different Si sources, what high Al in glass might
result from.
B) Ceramics
Key things to Know: key properties of ceramic clay (such as plasticity) and what
influences them. Importance of temper, and flux. What slip and glaze are and how they are
made. Mineralogy of raw materials for ceramics (be able to sketch structures), What happens to
clays and temper during firing.
Key things to be able to do: With reference to specific chemical reactions, explain
how one might determine to what temperature a pot was fired. Describe with illustrations the
development of kilns (open firing, firing pit, pit kiln, updraft kiln, downdraft kiln). Be able to
give one specific example, with graphs, of how knowledge of petrography of temper can yield
information of archaeological significance.
C) Metals
Key things to Know: meaning and differences among the terms malleable, ductile,
strength, hardness, stress, strain, elastic, plastic, and work-hardening. Know the ore material and
date of original use for some metals, Know the composition of important alloys (Bronze, Brass)
and how and why the alloy is superior to the pure metal. Know what beneficiation, smelting,
cupellation, and cementation are. Know the differences in composition, manufacturing process,
and key properties of wrought iron, steel, and cast iron. Know the differences among austenite,
martensite, pearlite, bainite, cementite, and ferrite.
Key things to be able to do: Explain with illustrations how Cu ore forms. Explain
with chemical reactions the smelting process for a specific metal, such as iron or copper. Explain
how cementation can produce steel from wrought iron. Be able to interpret an Fe-C phase
diagram in as it relates to early steel and iron manufacture.
D) Stone
Key things to Know: Nature and properties of important stones, including flint, chert,
jasper, obsidian, basalt, rhyolite, sandstone, limestone. Know how manufactured stones (such as
plaster of paris, lime plaster, and cement) work chemically (including manufacture, chemistry of
setting, and beneficial properties).
Key things to be able to do: Be able to give a specific example, with explanation and
graph, of the use of stone composition in archaeology.
E) Soil and Other Stuff
Key things to Know: How soil composition might be used to determine lateral (spatial)
or vertical (temporal) human occupation or activities. Know how C and N isotopes can be used
to infer diet.
Key things to be able to do: Be able to give a specific example of the use of skeletal
collagen C isotopes to infer timing of dietary changes.