1
Europe Raw Cotton Imports in 1858, 1864 and 1865 - Charles Joseph Minard - 1866
Language Communities of Twitter - Eric Fischer - 2012
2
Stream of Scientific Collaborations between World Cities - Olivier H. Beauchesne - 2012
The Structure of Science - Kevin Boyack, Richard Klavans - 2005
3
Maps of Science: Forecasting Large Trends in Science - Richard Klavans, Kevin Boyack - 2007
The Product Space - Cesar A. Hidalgo, Bailey Klinger, Albert-Laszlo Barabasi, Ricardo Hausmann - 2007
4
The Emergence of Nanoscience & Technology - Loet Leydesdorff - 2010
History of Science Fiction - Ward Shelley - 2011
5
Ingo Gunther's Worldprocessor globe design on display at the Giant Geo Cosmos OLED
Display at the Museum of Emerging Science and Innovation in Tokyo, Japan
Science Maps in “Expedition Zukunft” science train visiting 62 cities in 7 months, 12 coaches, 300 m long.
Opening was on April 23rd, 2009 by German Chancellor Merkel, http://www.expedition-zukunft.de
6
References
Börner, Katy, Chen, Chaomei, and Boyack, Kevin. (2003).
Visualizing Knowledge Domains. In Blaise Cronin (Ed.),
ARIST, Medford, NJ: Information Today, Volume 37, Chapter
5, pp. 179-255. http://ivl.slis.indiana.edu/km/pub/2003borner-arist.pdf
Shiffrin, Richard M. and Börner, Katy (Eds.) (2004). Mapping
Knowledge Domains. Proceedings of the National Academy
of Sciences of the United States of America, 101(Suppl_1).
http://www.pnas.org/content/vol101/suppl_1/
Börner, Katy (2010) Atlas of Science: Visualizing What We
Know. The MIT Press. http://scimaps.org/atlas
Scharnhorst, Andrea, Börner, Katy, van den Besselaar, Peter
(2012) Models of Science Dynamics. Springer Verlag.
Katy Börner, Michael Conlon, Jon Corson-Rikert, Cornell,
Ying Ding (2012) VIVO: A Semantic Approach to Scholarly
Networking and Discovery. Morgan & Claypool.
Katy Börner and David E Polley (2014) Visual Insights: A
Practical Guide to Making Sense of Data. The MIT Press.
Börner, Katy (2015) Atlas of Knowledge: Anyone Can Map.
The MIT Press. http://scimaps.org/atlas2
7
Billions and
Billions
of Molecules
Alán Aspuru-Guzik
Professor of
Chemistry and Chemical Biology
Harvard University
http://aspuru.chem.harvard.edu
Twitter: A_Aspuru_Guzik
aspuru@chemistry.harvard.edu
Exploring
Chemical Space
for Energy Materials
8
Some of the challenges of
the 21st century
Clean Energy
Advanced drugs
Water purification
Molecules and materials
1082 atoms in the
observable universe
9
1060 – 10180 medium-size
molecules
Molecular screening
How good is this molecule
as a solar cell material?
Quantum Mechanics
Machine Learning
10
Molecular simulation
“ A breakthrough in machine
learning would be worth ten
Microsofts”
11
Organic materials
in the larger context
Organic
Materials
Number of descriptors
Size of search space
Level of approximation
Large
Medium
Small
Shared Features
Timescale is important
Automated techniques
Data-driven discovery
Computational funnel
Inorganic
Materials
Organic
Pharmaceuticals
US Materials Genome Initiative
From 1060 to 106 to 10…
Initial library
Computational
screening
Synthesis
and testing
Computational
cost
Molecules most likely
to be of interest
12
My research group’s
explorations of chemical space
The Harvard Clean
Energy Project
Generating
renewable energy
Organic flow batteries
Storing renewable
energy
Blue Organic LED
For your next
gadget or TV
Origins of life
How life may have
come about?
The Harvard Clean Energy Project
The Harvard Clean
Energy Project
Generating
renewable energy
Organic flow batteries
Storing renewable
energy
Blue Organic LED
For your next
gadget or TV
Origins of life
How life may have
come about?
13
Power for 1.4 billion
Sheila Kennedy, MIT
How does an organic solar cell work?
14
Idle computers to the rescue!
30,000 CPU years
25,000 molecules /day
35 million conformers
500 million quantum
calculations
Largest quantum
chemistry survey
carried out to date
Sifting through 2.3 million molecules
10%
~35000 molecules
(1.5% of sample
space)
Energy and Environmental Science, 7, 698 (2014)
15
Clean Energy Project
Database
Organic Flow Batteries
The Harvard Clean
Energy Project
Generating
renewable energy
Organic flow batteries
Storing renewable
energy
Blue Organic LED
For your next
gadget or TV
Origins of life
How life may have
come about?
16
Renewables are intermittent
Wind supply
Solar
supply
Grid
demand
3 weeks
J. Rugolo and M.J. Aziz, Energy Environ. Sci. 5, 7151 (2012)
What is a flow battery?
Electrolytes
Electrochemical
cell
Flow
battery
Image source: Enervault
17
Vanadium flow battery
Metal free? Organic molecules?
18
Meet the quinones
Plastoquinone:
Electron shuttle in plants
Rhein from Rhubarb:
is a laxative
and antibacterial
Blattellaquinone: is a sex
pheromone female
cockroaches use to
attract males
Our metal-free aqueous flow battery
G
r
o
u
p
:6
G
r
o
u
p
:6
G
r
o
u
p
:5
G
r
o
u
p
:3
b
3
+ 2
+
V
/V
2
+ 3
+
V
O
/V
+
2
+
V
O
O
2/V
B
r
/B
r
2
1
,
5
-A
Q
2
,
3
-A
Q
2
,
6
-A
Q
1
,
7
-A
Q
2
,
9
-A
Q
1
,
1
0
-A
Q
1
,
2
-A
Q
1
,
4
-A
Q
9
,
1
0
-A
Q
2
,
3
-N
Q
2
,
6
-N
Q
1
,
7
-N
Q
Intense
design cycle
1
,
5
-N
Q
1
,
4
-N
Q
1
,
2
-N
Q
1
,
4
-B
Q
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
.4
.6
.8
.2
0.0
-0
-0
-0
-0
-1
.0
1
,
2
-B
Q
0
E
(
V
v
s
S
H
E
)
Computational screening of
10,000 quinone molecules
Synthesize molecules
Test in flow battery
Selected molecule
19
Theory-experiment
collaboration
Michael Aziz
Engineering
Roy Gordon
Chemistry
Alán Aspuru-Guzik
Chemistry
Nature, 505, 2014, p. 195
Lowering E0
Rank of ΔE0
17 COOCH3
CHO
CHO
COOCH3
COOCH3 COOCH3 COOCH3 COOCH3 COOH
16
CN
COOH
15
COOH
CN
14
CF3
13
CHO
PO3H2
12
Cl
CF3
11
F
Cl
10
SO3H
SO3H
9
PO3H2
F
8
OCH3
C2H3
7
C2H3
SiH3
6
SiH3
CH3
5
CH3
4
N(CH3)2
OCH3
SH
CH3
CH3
3
SH
SH
OH
OH
SH
2
NH2
OH
N(CH3)2
NH2
OH
1
OH
NH2
NH2
N(CH3)2
1,10-AQ
1,2-AQ
1,2-BQ
1,2-NQ
CN
COOH
COOH
COOCH3
CHO
CN
COOCH3
COOCH3 CHO
CN
CF3
CHO
COOCH3
COOCH3
CHO
Molecular Flow Battery Data View
COOH
COOCH3
N(CH3)2
CN
COOH
CN
CF3
COOH
COOH
CF3
CN
SO3H
CHO
CN
CN
CF3
COOCH3
CF3
COOH
CHO
CN
COOH
CN
SO3H
CN
CHO
CN
COOCH3
COOCH3 COOCH3 CN
CN
COOH COOH
COOCH3
CN
COOH
CF3
CHO
OCH3
SO3H
SO3H
PO3H2
CF3
CF3
CHO
SO3H
CF3
CF3
COOH
CF3
CF3
COOH
CF3
CF3
CF3
Cl
Cl
CHO
SO3H
Cl
CHO
SO3H
SO3H
PO3H2
COOH
PO3H2
SO3H
PO3H2
F
PO3H2
F
SO3H
PO3H2
Cl
PO3H2
Cl
PO3H2
PO3H2
Cl
PO3H2
Cl
PO3H2
Cl
Cl
Blue: Stable molecule
Red: Unstable molecule
Cl
CHO
F
Cl
F
F
F
Cl
Cl
F
Cl
F
Cl
SO3H
CHO
SiH3
PO3H2
CHO
F
PO3H2
SO3H
SiH3
F
F
SiH3
F
SO3H
F
F
N(CH3)2
F
OCH3
OCH3
OCH3
OCH3
SiH3
PO3H2
SiH3
SiH3
SO3H
SiH3
SiH3
SiH3
SiH3
C2H3
C2H3
C2H3
C2H3
SiH3
SiH3
OCH3
C2H3
C2H3
C2H3
C2H3
OCH3
C2H3
C2H3
OCH3
SO3H
X axis: Redox Potential
Y axis: Free energy of Solvation
~ 100,000 molecules shown
CH3
OCH3
SiH3
SH
C2H3
C2H3
CH3
CH3
CH3
SH
C2H3
SH
OCH3
C2H3
PO3H2
CH3
CH3
OCH3
OCH3
OCH3
OH
CH3
CH3
CH3
CH3
SiH3
SH
SH
N(CH3)2
SH
SH
SH
N(CH3)2
N(CH3)2
SH
N(CH3)2
OH
OH
OH
NH2
OH
OH
NH2
NH2
NH2
NH2
OH
NH2
NH2
1,4-AQ
1,4-BQ
1,4-NQ
1,5-AQ
1,5-NQ
1,7-AQ
1,7-NQ
SiH3
N(CH3)2
C2H3
CH3
N(CH3)2 N(CH3)2
CH3
SH
OCH3
SH
N(CH3)2
CH3
OCH3
OH
N(CH3)2
N(CH3)2
SH
SH
NH2
N(CH3)2
OH
OH
OH
OH
N(CH3)2
NH2
NH2
NH2
NH2
NH2
2,3-AQ
2,3-NQ
2,6-AQ
2,6-NQ
2,9-AQ 9,10-AQ
20
Molecular Flow Battery Data View
Filtering the data view
Molecular Flow Battery Data View
Baseball card view
21
Molecular Flow Battery Data View
Selecting molecules is
like dating.
Redox pathways view
22
Organic LED Screening
Synthetizability voting tool
To design something
really well you have to
get it. You have to
really grok what it’s all
about. It takes a
passionate
commitment to really
thoroughly understand
something. Chew it
up, not quickly
swallow it. Most
people don’t take
time to do that.
23
Aspuru-Guzik group, http://aspuru.chem.harvard.edu
References
Clean Energy Project
J. Phys. Chem. Lett. 2,
2241 (2011)
Energy Environ. Sci. 4,
4849 (2011)
Energy Environ Sci 7,
698 (2014)
Organic Flow Battery
Nature 505, 195 (2014)
Chemical Science.
Advance (2014)
Origins of life
J Comp
Theo Chem 10, 2097 (2014)
DOE, ARPA-E, NSF, Samsung, Sloan Foundation
Camille and Henry Dreyfus Foundation
Organic electronics
Nat. Comm.
2, 437
(2011)
Nature
480, 504
(2011)
24
Utilizing Visual Insights in Science
and Technology Policymaking
• Kei Koizumi
• AAAS Annual Meeting February 2015
• For the session Visualization Insights from Big Data:
Envisioning Science, Engineering, and Innovation
US Global Change Research Program
3000
Recovery Act
All Other
2500
NASA
2000
NIH
EPA
1500
Interior
Agriculture
1000
Commerce (NOAA, NIST)
500
NSF
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
0
Energy
in millions of constant FY 2015 dollars
FEBRUARY 2015 OSTP
FY 2009 figures include Recovery Act funding.
25
Trends in Federal Research by Discipline, FY 1970-2013
obligations in billions of constant FY 2014 dollars
$35
Life Scis.
$30
Engineering
$25
Physical Scis.
$20
Env. Scis.
$15
Math / Comp. Scis.
$10
Social Sciences
Source: NSF, Survey of Federal Funds for Research and Development, 2013. FY
2012 and 2013 data are preliminary. Constant-dollar conversions based on
OMB's GDP deflators. FY 2009 and 2010 include Recovery Act obligations.
DECEMBER 2013 OSTP
2010
2006
2002
1998
1994
1990
1986
1982
Other *
1978
$0
1974
Psychology
1970
$5
* - Other includes research
not classified
(includes basic research
and applied research;
excludes development and
R&D facilities)
26
Science Funding and Short-Term Economic Activity,
Bruce A. Weinberg, Jason Owen-Smith, Rebecca Rosen, Lou Schwarz, Barbara
McFadden Allen, Roy Weiss, Julia Lane. Published 4 April 2014, Science 343, 41 (2014)
NASA Earth Observatory, EOS Project Science Office, NASA Goddard Space Flight Center
Visualizing the 2012 Sea Ice Minimum
URL
http://earthobservatory.nasa.gov/IOTD/view.php?id=79256
2012
27
28
29
30
Thank you
Kei Koizumi
Disclaimer: The views expressed here are my own and do not represent
the views of the Office of Science and Technology Policy or any other
organization.
31
http://avl.ncsa.illinois.edu/what-we-do/services/media-downloads
32
http://avl.ncsa.illinois.edu/what-we-do/services/media-downloads
http://avl.ncsa.illinois.edu/what-we-do/services/media-downloads
33
Still from the new full
dome show “Solar
Superstorms.”
Visualization of scientific
numerical model reveals
a turbulent front
generated by a solar wind
interacting with Earth’s
magnetic field during a
powerful solar storm.
Large disturbances,
including high velocity
jets, can penetrate deep
inside the Earth’s
magneto-sphere
and result in space
weather effects such as
loss of communications
satellites and wide spread
blackouts.
Numerical simulation by Homa Karimabadi, Mahidhar Tatineni and Vadim Roytershteyn,
University of California, San Diego. Visualization by the Advanced Visualization Lab (Donna
Cox, Robert Patterson, Stuart Levy, AJ Christensen, Kalina Borkiewicz, Jeff Carpenter) at NCSA.
Funded in part by the National Science Foundation.
Q&A
34
35
Producer/Script Writer: Katy Börner, Designer/Artist: Ying-Fang Shen, Sound Artist: Norbert Herber, 2013.
http://cns.iu.edu/humanexus
36