Mapping the materials genome:

transforming data to knowledge for enabling

Materials-by-Design

Krishna Rajan Wilkinson Professor of Interdisciplinary Engineering Iowa State University

Brown University: March 29th 2012

Do we really need more data? Is informatics the same as managing databases? Is modeling the same as integrating computational materials engineering? Is high throughput data collection or computation the same as high throughput

scientific discovery?

Outline: Data Driven Materials-by-Design

Challenging the existing (affirmative) paradigms for materials-by design

Krishna Rajan: Iowa State University

Developing a “genomics” framework for materials-by design

Classifying materials design problems in terms of data characteristics: Volume, Velocity, Variety, Veracity (courtesy L. Haas –IBM)

Differentiating Data from Knowledge : Materials science examples New paradigms for information management

systems for the Materials Genome: Materials cartography Materials barcode

http://www.genengnews.com/

• Need to establish a genomics-proteomics-metabolomics etc. :Systems Biology approach

• What are the data management and sharing issues for a systems approach?

Data and Materials Genome

Krishna Rajan: Iowa State University

Functionality = F ( x1 , x2 , x3 , x4 , x5 , x6 , x7 , x8 ……)

Issues: • how many variables? • which variables are important? • classify behavior among variables • making quantitative predictions …relate functionality to variables …

• traditionally we describe them by empirical equations: •Quantitative Structure Activity Relationships (QSARs) are derived from data mining techniques not assuming a priori which physics is the most important

Need to build database with these variables

The 4 V’s of Materials Data: status report

VARIETY: data in many forms

Engineering design / materials insertion

Multiscale data

VOLUME: data at rest

Materials reference data Thermodynamic Crystallography Property

VELOCITY: data in motion Materials Characterization

in-situ materials dynamics ( x-ray, ..)

Time-of-flight data

VERACITY: data in doubt

Incomplete data, ambiguities, missing

data

Phase diagrams, Property maps

Krishna Rajan: Iowa State University

Modeling

http://iusti.polytech.univ-mrs.fr/MOLTEN_SALTS/

Data Volume : discovery from static data

Krishna Rajan: Iowa State University

Accelerated reference data discovery

Outlier detection

Classification detection

Krishna Rajan

Data Volume : discovery from static data: …discovering need for new data

Informatics Based Optimization of Crystallographic Descriptors for Framework Structures; A. Rajagopalan and K. Rajan in Combinatorial and High-Throughput Discovery and Optimization of Catalysts and Materials Editors: W.Maier and R. A. Potyrailo ( CRC press – 2005)

Statistical removing of outliers: • better models from same data •new design rationale for metal oxide frameworks

Krishna Rajan: Iowa State University

Data Volume: too much data?......Complexity – Uncertainty tradeoff

Petterson et.al. Mater. Manuf. Proc. (2009)

# networks

Predator-Prey models

Krishna Rajan: Iowa State University

Data Velocity: discovering catalyst chemistries

Maier- Saarbruken J. Comb. Chem., 2009, 11 (3), pp 385–392

Chemical bonding/molecular information

Elemental information

Imaging and structural information

Data Velocity: pushing materials characterization techniques to limits

Interrogation and analysis of fast and large data sets via scientific visualization

Bryden et.al (2012) Suram and Rajan (2009,2012)

Krishna Rajan: Iowa State University

Data Variety: data driven design of drug delivery polymers

Ideal vaccine will mimic the way in which a naturally occurring infection induces a robust immune response yet avoid the undesirable effects of disease

Ulery et.al (2012)

Krishna Rajan: Iowa State University

Data Veracity: shrinking the data ‘gap” with sparse, skewed and unscaled data

Closing the gap : developing a QSAR- a new figure of merit

Knowledge: a unified model of materials behavior

Information: the ‘tolerance factor’

Utility: accelerated discovery

Data: developing a descriptor database

Krishna Rajan: Iowa State University

Materials Cartography: information theoretic data system mapping data flow

DATA POINTS Phone-Call Cartography- CARLO RATTI

Kong and Rajan (2012)

Krishna Rajan: Iowa State University

Materials Barcode: a new genre of materials data libraries Crystal chemistry barcodes

Density of states barcode Combinatorial experimental barcodes

J. Comb. Chem., 2009, 11 (3), pp 385–392

Krishna Rajan: Iowa State University

veracity variety velocity volume :Designby Materials

Summary: “Closing the Gap” for Materials-by-Design…….harnessing the 4 ‘V’s’

Experiments and physical models

Informatics, statistical learning

Krishna Rajan: Iowa State University

To transform the “Materials Genome” from a concept to reality we need an information system that can enable and accelerate the Data to Knowledge transformation (the new paradigm for Materials-

by-Design) •Materials Barcode Project •Materials Cartography Atlas