The Materials Data Scientist

&THE SPACE IN BETWEEN

A PRESENTATION BY TONY FAST

STONE

AGE

IRON A

GE

COPPER

AGE

BRONZE AG

E

THREE-AGE SYSTEM

STEEL AGE

STEELALUMINUM

NANOTECHNOLOGYBIOMATERIALS

POLYMERSFIBER COMPOSITES

AMORPHOUS METALSSEMICONDUCTORS

MAGNETIC MATERIALSCERAMICS

PERFORMANCE

METERS10-9 10-3

HIERARCHICAL NATURE OF MATERIALS

PERFORMANCE

MOVIE TIME

@BrockDavis

OUT-GROUP HOMOGENEITYOBSERVED CULTURALLY

APPLICATION SPACE

MATERIALSSCIENCE

MATERIALS SCIENCE INFORMATION

PHYSICSBASED MODELS

RITCHIE GROUP, LLNL

HIGH TEMPERATURE IN SITU TENSILE TESTING OF SiC-SiC MINICOMPOSITES

RITCHIE GROUP, LLNL

HIGH TEMPERATURE IN SITU TENSILE TESTING OF C-SiC TEXTILES

VOORHEES GROUP, NORTHWESTERN

IN SITU VISUALIZATION OF SOLIDIFCATION INTERFACES IN AL-CU

16 TB

STITCHED ELECTRON BACKSCATTERED DIFFRACTION OF HEXAGONAL METALS

KALIDINDI GROUP, GATECH

ATOM PROBE MICRSCOPY

FINITE ELEMENT CRYSTAL PLASTICITY MODELS

MOLECULAR DYNAMICS SIMULATIONSOF ALUMINUM POTENTIALS

MOLECULAR DYNAMICS FOR POLYMERIC MATERIALS

JACOBS GROUP, GATECH

KALIDINDI GROUP, GATECH

EBSD detector

Sample

Indenter tip

SEM pole piece

Step 6

Step 1

Step 2

Step 3

Step 4

Step 5

KALIDINDI GROUP, GATECH

IN SITU NANOINDENTATION &BACKSCATTERED ELECTRON DIFFRACTION

MATERIALSSCIENCE DATA

HIGH DIMENSIONAL, MULTIOMODAL, SPATIOTEMPORAL, PARTIAL DATASETS

THE PAST ISN”T THE FUTURE

β-Titanium

REDUCED OUTPUT:Grain sizeGrain FacesNumber of GrainsMean CurvatureNearest Grain Analysis

ROWENHORST, LEWIS, SPANOS, ACTA MAT, 2010

DATA SCIENCE APPLICATIONSFOR STRUCTURAL MATERIALS

SCALABLE ALGORITHMS

FEATURE IDENTIFICATIONANOMOLY DETECTIONSTATISTICAL ANALYSISCOMPUTER VISIONIMAGE SEGMENTATIONBACKGROUND REMOVALSIGNAL DECONVOLUTIONCLASSIFICATIONREGRESSION

FFT BASED METHODS FOR SPATIAL STATISTICSA GENERALIZED FEATURE IDENTIFIER

FIBER SEGMENATION IN LOW CONTRAST IMAGES

DIMENSION REDUCTION, CLASSIFICATION, & COMPRESSION

HIGH DIMENSIONAL, MULTIOMODAL, SPATIOTEMPORAL, PARTIAL DATASETS

MODEL VERIFICATION & VALIDATION IN MOLECULAR DYNAMICS

CLASSIFICATION OF PROCESSING HISTORYIN TITANIUM ALLOYS

REGRESSION MODELS FOR FORWARD MODELS & PRIOR KNOWLEDGE

Localization

Homogenization

10-9 m

10-3 m

FORWARD REGRESSION MODELS FOR FUEL CELLS

MPL

GDL

Homogenization

FEMε=5e-4

LocalizationINVERTABLE MATERIALS KNOWLEDGE SYSTEMS

Localization

INPUT OUTPUTControl

Any M

odel

INVERTABLE MATERIALS KNOWLEDGE SYSTEMS

LocalizationINVERTABLE MATERIALS KNOWLEDGE SYSTEMS FOR COMPOSITES

SCALABLE, ACCURATE, INVERTIBLE METAMODELS

Structure-Processing MKS

Processing History

Structure-Property

Homogenization

Structure-Property

Localization

“Being able to manipulate text files at the command-line, understanding vectorized operations, thinking algorithmically; these are the hacking skills that make for a successful data hacker.”

DREW CONWAY’S PRIMARY COLORS OF DATA SCIENCE

TECHNICAL SKILLS USES DATA AS CURRENCY IS A SCIENTIST

NOT A PROGRAMMER

ADDRESSES OBJECTIVESNO PIPELINES

USES VERSION CONTROL CAPABLE IN SEVERAL

PROGRAMMING LANGUAGES

SOFT SKILLS SOCIAL INQUISITIVE POLYMATH CREATIVE PROBLEM

SOLVER

WHERE TO START

BY FIXING THIS