BIOMEMS
Class I. Introduction: From MEMS to BIOMEMS/
Definitions
Winter 2011
Dr. Marc Madou
Aequorea victoria
Content
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From MEMS to BIOMEMS
BIOMEMS and analytical chemistry
Definition of sensors
Sensitivity
Cross-sensitivity and crosstalk
Signal-to-noise-ratio and drift
Resolution
Span or range and bandwidth
Dynamic range, gain and dynamic error
Selectivity
Hysteresis
Accuracy
Calibration
From MEMS to BIOMEMS
‘Miniaturization engineering’ is a more appropriate name than MEMS
(NEMS), but the name MEMS (NEMS) is more popular. It involves a
good understanding of scaling laws, different manufacturing methods
and materials. Initially it involved mostly Si and mechanical sensors
(e.g., pressure, acceleration, etc). Miniaturization engineering or
MEMS applied to biotechnology is called BIOMEMS. In BIOMEMS
the number of materials involved is much larger, modularity is often a
must (not integration as in ICs !), costs often need to be less than
what’s possible with Si and batch processes are not always the answer (
continuous manufacturing need !).
From MEMS
to BIOMEMS
Silicon Valley Micromachining
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1972 Foxboro/ICT
1972 Sensym/National Semiconductor (sold to Hawker Siddley in 1988)
1975 Endevco
1975 IBM Micromachining
1976 Cognition (sold to Rosemount in 1978)
1980 Lawrence Livermore Lab
1981 Microsensor Technology (sold to Tylan in 1986)
1982 Transensory Devices (sold to ICSensors in 1987)
1982 ICSensors (sold to EG&G in 1994)
1985 NovaSensor (sold to Lucas in 1990)
1986 Captor (sold to Dresser in 1991)
1988 Redwood Microstructures
1988 TiNi Alloys
1989 Teknekron Sensor Development Corporation (dissolved in 1993)
1990 Microflow
1991 Sentir
1992 Silicon Microstructures
1992 Rohm Micromachining
1993 Silicon Micromachines
1993 Fluid IC
1993 Next Sensors
1994 Berkeley Microstructures
1994 Piedmont Microactuators
1995 Caliper
1995 Cepheid
BIOMEMS as part of analytical chemistry
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BIOMEMS may often be seen as a type of analytical
technique used in many research areas :
– Chemistry
– Biochemistry
– Biology
– Geology
– Oceanography, etc.
Analytical techniques which are also used in many
industrial areas :
– Forensic science (e.g. O.J.’s DNA)
– Clinical diagnostics (e.g.glucose in blood)
– Product development (e.g. new drug)
– Quality control (e.g.pH of swimming pool)
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Both instruments and sensors (see next
viewgraph for definition) are used in
BIOMEMS both will be discussed in
this course- the distinction between the
two is rather vague (e.g. size,
complexity, parts of an instrument
might be called a sensor, etc.)
Definitions of sensors
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Chemical sensors are defined as measurement devices
Effector (magnetic, chemical, physical,
which utilize chemical or biological reactions to detect
etc.)
and quantify a specific analyte or event. They are
ususally a lot more difficult to make than physical
Active surface
sensors which measure physical parameters.
For the distinction between biosensors and chemical
sensors we define a biosensor as one which contains a
Transducer
biomolecule (such as an enzyme, antibody, or receptor),
Sensor
a cell or even tissue as the active detection component.
Integrated sensor
A sensor, a transducer, transmitter and detector or often
Smart sensor
used as synonyms. They are devices that convert one
form of energy into another and provide the user with a
usable energy output in response to a specific
Amplification/Filtering/A/D, etc
measurable input. In the chemical sensor area a
transducer plus an active surface is called a sensor.
Data storage and processing
Output
Control
Sensor
system
Sensitivity
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A sensor detects information input,
Iin, and then transduces or converts
it to a more convenient form, Iout i.e
Iout = F(Iin). So sensitivity is the
amount of change in a sensor’s
output in response to a change at a
sensor’s input over the sensor’s
entire range. NOT THE SAME AS
LOWER LIMIT OF DETECTION!
Very often sensitivity approximates
a constant; that is, the output is a
linear function of the input
Sensitivity may mathematically be
expressed as  = dIout
dI in
Germanium
Resistance
Thermometers
Sensitivity 35,000 Ohms/K @ 4.2 K
http://www.sciinst.com/sensors/grt.htm
Cross-sensitivity and crosstalk
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Cross-sensitivity: The influence of
one measurand on the sensitivity of
the sensor for another measurand
(e.g., OH- influences F- detection)
Crosstalk: Electromagnetic noise
transmitted between leads or
circuits in close proximity to each
other
Signal-to-noise-ratio-S/N and drift
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S/N: The ratio of the output signal with
an input signal to the output signal with
no input signal
Drift: Gradual departure of the
instrument output from the calibrated
output. An undesirable change of the
output signal.
Noise is normally measured "peak-to-peak": i.e., the distance from the top of one such
small peak to the bottom of the next, is measured vertically. Sometimes, noise is averaged
over a specified period of time. The practical significance of noise is the factor which
limits detector sensitivity. A practical limit for this is a 2 x signal-to-noise ratio.
Resolution
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The smallest increment of change in the
measured value that can be determined
from the instrument’s readout scale.
Span or range (also called bandwidth)
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Span or range: The difference
between the highest and lowest
scale values of an instrument
Bandwidth: The range of scale
values over which the measurement
system can operate within a
specified error range ( also used as
another word for span)
Dynamic range, gain and dynamic error
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Dynamic range: The ratio of the
largest to the smallest value of a
range, often expressed in
decibels (dB),
Gain:The ratio of the amplitude
of an output to input signal.
Dynamic error: The error that
occurs when the output does not
precisely follow the transient
response of the measured
quantity.
Selectivity
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Selectivity: The ability of a sensor to
measure only one parameter, in the
case of a chemical sensor, to measure
only one chemical species
Because of the lack of perfect
selectivity arrays are often
implemented (e.g., electronic nose and
tongue)
The electronic nose
The sensitivity of certain gas sensors to different gases
depends on the choice of catalytic sensor material and the
operating temperature. By combining several different gas
sensors into a sensor array, complex gas mixtures can be
analysed. Although the selectivity of the sensors is limited,
qualitative and quantitative gas analysis can be performed
using pattern-recognition techniques. The combination of
multiple gas sensors and signal analysis using patternrecognition techniques is the concept behind the electronic
nose and tongue. These instruments have been successfully
used in a number of applications, e.g., the quality estimation
of ground meat, the identification of different paper qualities,
the classification of grains with respect to microbial quality,
and the screening of irradiated tomatoes.
Hysteresis
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The difference in the output when a
specific input value is approached
first with an increaseing and then
with a decreasing input.
Piezoelectric ceramics display hysteretic behavior. Suppose we start at zero applied
voltage, gradually increase the voltage to some finite value,and then decrease the
voltage back to zero. If we plot the extension of the ceramic as a function of the
applied voltage, the descending curve does not retrace the ascending curve - it follows
a different path.
Accuracy
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The degree of correctness with which a
measuring system yields the “true
value” of a measured quantity (e.g.
bull’s eye) --see calibration
http://ull.chemistry.uakron.
edu/analytical/animations/
Precision
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QuickTime™ and a
Graphics decompressor
are needed to see this picture.
The difference between the instrument’s
reported values during repeated
measurements of the same quantity.
Typically determined by statistical analysis
of repeated measurements
http://ull.chemistry.uakron.
edu/analytical/animations/
Accuracy, precision and standard
deviation
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A measurement can be precise but may
not not be accurate
The standard deviation (s) is a statistical
measure of the precision in a series of
repetitive measurements (also often
given as  with N the number of data,
xi is each individual measurement, and
X
is the mean of all measurements. The
value
is called the residual for
X xi each measurement
QuickTime™ and a
Graphics decompressor
are needed to see this picture.
Calibration: standard curve
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A process of adapting a
sensor output to a know
physical or chemical quantity
to improve sensor output
accuracy i.e. remove bias
A working or standard curve
is obtained by measuring the
signal from a series of
standards of known
concentration. The working
curves are then used to
determine the concentration
of an unknown sample, or to
calibrate the linearity of an
analytical instrument-for
relatively simple solutions
What is Next?