MURI MANAGING THE MOSAIC

OF MICROSTRUCTURE

3-year ReviewJune 22-23, 2015

BRICC, Arlington VA

AFOSR-FA9550-12-1-04581

OUTLINE• Our MURI team

• The Grand Challenges• Program and Research Highlights

• Selected Research Highlights• Impact• Publications• Education/Outreach

• Review Schedule

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THE CALL (BAA 11-026)

• Topic: Managing informational complexity in predictive materials science

• “This MURI is to establish mathematical approaches for a stochastic and statistical framework for multi-scale materials modeling that leads to discovery of new materials.”

• “The ultimate aim is to create a platform of new scientific enterprise to successfully resolve issues of complexity, variability across time and length scales, and allow for a dynamic integration and validation of mathematical predictions through new experimental methods that can enable rapid interrogation of structure and properties at different scales.”

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4

School co-PI(s) #GS/PD

CalTech Kaushik Bhattacharya 0/1

Minnesota Richard James 2/0

Northwestern Peter Voorhees, Alok Choudhary, Ankit Agrawal 2/1

Purdue Charles Bouman, Mary Comer 4/0

Michigan Veera Sundararaghavan 2/0

Georgia Tech Surya Kalidindi 1/0.5

Carnegie Mellon Marc De Graef 2/1

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Neetha Khan Michael Jackson

13/3.5

TEAM EXPERTISE

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MicrostructureCharacterization

Statistical & Probabilistic Signal

Processing

Data Mining Property/Microstructure Modeling

MathematicalTheory of

Microstructure

Repr

ese

ntation Quantification

Design

Mosaic of Microstructure

stress

strain

Microstructure-Property Stochastic

Models

Materials Informatics

MicrostructureEvolution

High PerformanceComputing

GRAND CHALLENGES• The main objectives of our research are:

• to establish a standardized methodology, grounded in sound mathematics, for acquiring, storing, analyzing, modeling, and querying “beyond 3-D” materials data, taking full account of the potential sparsity of such data as well as the associated uncertainties and variabilities;

• to employ advanced stochastic/probabilistic models that allow not only for the description of the “average” microstructure, but also for the inclusion of rare events (large deviations), and to set up the proper data structures to enable such a stochastic description;

• to employ advanced data mining approaches, constrained by accurate mathematical models and accounting for variability, to instantiate large numbers of digital microstructures to search for an optimal microstructure and its process path, to achieve a desired property combination.

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RESEARCH THRUST AREAS

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Repr

ese

ntation Quantification

Design

Mosaic of Microstructure

stress

strain

T1: Representation of structureand time evolution in microstructures:what can we measure and how can we compactly represent microstructure?

T2: Mathematical quantification of microstructures for bridging scales:what information about a micro-

structure is relevant for its properties?

T3: Multi-scale materials design using informatics:how can we use microstructure information for design?

Peter Voorhees Dick James

Surya Kalidindi

SCIENTIFIC ADVISORY PANEL

• Jeff Simmons (AFRL)

• Tresa Pollock (UCSB)

• Shlomo Ta’asan (CMU)

• David Furrer (PW)

• Peter Chung (UMD)

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provided extensive feedbackafter January 2014 review

OUTLINE• Our MURI team

• The Grand Challenges• Program and Research Highlights

• Selected Research Highlights• Impact• Publications• Education/Outreach

• Review Schedule

9

• Publications (as of 3/31):• 38 in archival journals (28 appeared, 10 accepted)

• 26 conference proceedings

• more than 40 papers in preparation

• Selected awards:• Kaushik Bhattacharya: 2015 Koiter lecturer (ASME)

• Charles Bouman: 2014 electronic imaging scientist of the year

• Surya Kalidindi: 2014 von Humboldt award for lifetime achievements, 2015 TMS Fellow

• Dick James: 2014 Theodore von Karman prize (SIAM)

• Peter Voorhees: 2014 Hillert-Cahn lecture, Phase Transformations in Materials Conference

• S. Venkatakrishnan: 2014 M&M Presidential Scholar Award

• Xian Chen: Lawrence E. Goodman Fellowship

• Abishek Kumar: 2014 Ivor K. McIvor Award

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ACCOMPLISHMENTS

• MURI website: http://muri.materials.cmu.edu/

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EDUCATION & OUTREACH

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• github-based e-collaboration platform: http://materials-informatics-lab.github.io/to support cross-disciplinary engagement of computer scientists on materials research problems

EDUCATION & OUTREACH

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EDUCATION & OUTREACH• source code distribution: http://www.openMBIR.org/, http://github.com/degraef

• DHS SBIR-phase I company: High-Performance Imaging

• Goal: developing high performance computing solutions for the implementation of MURI-developed algorithms and code, such as MBIR

• demonstrated 20x improvement on standard multi-core and GPU hardware

• HPI activities are synergistic with the MURI program by reducing the barriers to the use of the algorithms created by the team.

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EDUCATION & OUTREACH

• Team Summer meeting at Purdue Univ., August 14-15, 2014• Invited talk: “Understanding the mechanical properties of metallic glass matrix

composites”, K. Flores, E. Marquis, W. Windl

•Center of Excellence on Integrated Materials Modeling

• Joint MURI-CEIMM workshop on forward modeling algorithms for electron scattering based materials characterization tools (November 14, 2014)

• Plenary MURI overview presentation at CEIMM annual review (UCSB, May 12, 2015)

•ABC Stochastic Multi-resolution Theory for Microstructure Based Predictive Materials Science – Application to Multiphase Polymer Systems

• Invited talk (Cate Brinson) at August 2015 team meeting at CMU.

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OUTREACH TO OTHER AFOSR SPONSORED PROGRAMS

- July 8-10, 2015, in collaboration with the MURI program, Bluequartz Software, the Center for Multiscale Modeling for Engineering Materials (CM2EM), the Materials Science & Engineering Dept. and the Physics Dept.

- intended to provide researchers at all levels with tools and methods for reconstructing, analyzing and synthesizing 3D microstructures

- includes hands-on training sessions for DREAM.3D data analysis, and DREAM.3D plugin creation.

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CMU SUMMER SCHOOL ON 3D METHODS

• Jointly with and at the University of Antwerp, Belgium• Dates to be decided but likely late June, 2016• Workshop will bring together a group of internationally recognized

tomography experts from a number of disciplines (materials, signal processing, medical), with the goal of reviewing the state-of-the-art in 3D and 4D tomography, as well as producing a forward-looking plan for the next decade.

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INTERNATIONAL WORKSHOP ON TOMOGRAPHY

MS&T 2015 SHORT COURSE ON MATERIALS INFORMATICS

• Jointly with NIST• Introduction to open access - open source code repository PyMKS

PROGRAM & RESEARCH HIGHLIGHTS

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1. 4D Tomography of Time Evolving SamplesJ. Gibbs, A. Mohan, A. Shahani, A. Cecen, B. Gulsoy, C. Bouman,

S. Kalidindi, M. De Graef, X. Xiao*, P. Voorhees *  Advanced  Photon  Source,    Argonne  National  Laboratory

• Al-24wt%Cu Solidification experiment at APS-ANL

• Time-Interlaced Model-Based Iterative Reconstruction (TIMBIR) + HPC

• Novel sampling approach, increased temporal resolution, while maintainingspatial resolution

• IMPACT: Advanced Light Source (ALS) at the Lawrence Berkeley National Laboratory (LBNL) has made TIMBIR part of the pipeline of software available to ALS users

• Increased accuracy allows interesting large scale data analysis

Voorhees

Bouman

Voorhees/

Kalidindi

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Al-24wt%Cu; 2 mm diameter; 2°C/min

1.8s time steptip speed 60micron/s

PROGRAM & RESEARCH HIGHLIGHTS

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2. Improved EBSD Indexing through Forward ModelingS. Singh, M. Jackson (BlueQuartz), A. Hero (+ group at UM), S. Wright (EDAX/TSL), M. De Graef

θc

ζcW

pattern center

scintillator

∆L

pole piece

70°L

ND

RD

TDλ

P

Q

• Polycrystalline Ni test sample

• Dynamical real-time dictionary computation(EMsoft); GPU-based indexing

• Novel indexing approach, increased angular resolution

• IMPACT: EMsoft is currently being tested atOSU (S Niezgoda), BYU (D. Fullwood), and EDAX/TSL (S. Wright); release 3.0 early Fall.

De  Gra

ef

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2. Improved EBSD Indexing through Forward Modeling

• Current commercial indexing algorithms are based on detecting Kikuchi bands using variants of the Hough transform

• At low signal-to-noise ratios, these approaches fail; our new dictionary-based method manages to index even very noisy patterns.

PROGRAM & RESEARCH HIGHLIGHTS

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3. Algorithmic Materials Discovery R. James, K. Bhattacharya, M. DeGraef, M. Comer, E. Quandt; M. Chapman,

X. Chen, Y. Song, N. Tamura*,

• Theoretical study of the cofactor conditions and their implications for reversibility of phase transformations

• Measuring the Young measure and detailed experimental study of theseconditions

• IMPACT: a spectacular new alloy satisfying these conditions, designed using StrucTrans

• Algorithms are being integrated intoALS software; StrucTrans website

1. Y. Song, X. Chen, V. Dabade, T. W. Shield, R. D. James, Nature 502, 85-88 (2013). 2. R. D. James, Nature 521, 298-299 (2015). 3. C. Chluba, R. Miranda, J. Strobel, L. Kienle, E. Quandt, M. Wuttig, Science 348, 1004 (2015). 4. R. D. James, Science 348, 968-969 (2015).

austenite

martensite

James

James/DeGraef

Bhattacharya/Comer

PROGRAM & RESEARCH HIGHLIGHTS

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4. Quantification & Reconstruction of Microstructures

AL6XN microstructure (NRL)

Synthesized Location-specific microstructures

ExperimentSynthesized  3D  microstructures Novel microstructure representations

based on Markov random fields applied to

• 2D to 2D sampling• 2D to 3D sampling for

3D microstructure reconstruction• 3D to 3D sampling to generate

location specific microstructures

IMPACT: Methods used in DoE PRISMS center for DIC (2D) data conversion to 3D for CPFE calculations (U Michigan), for fiber composites (U Washington)

Sundar

aragha

van/  

Kalidin

di

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PROGRAM & RESEARCH HIGHLIGHTS5. Predictive Machine Learning for Materials Design

Single  crystal  property  data  (properties  measured  along  x-­‐axis)

• Novel approach for materials design using predictive machine learning

• Allows efficient sampling of complete microstructural space

• Ability to identify multiple solutions,

• IMPACT: Predicted extremal microstructures of Galfenol for sensor applications, 80% faster than traditional optimization methods

Sundar

aragha

van

Choudh

ary,  

Agrawa

l

PROGRAM & RESEARCH HIGHLIGHTS

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6. Microstructure Quantification Framework and the Computational Toolbox A. Cecen, T. Fast, Y. Yabansu, J. Gibbs, S. R. Kalidindi, P. Voorhees

• Statistical Description of Structure using 2-Point Spatial Correlations

• IMPACT: Structured and streamlined APIs in MATLAB and Python disseminated broadly to the community through GitHub (as a part of MATIN).

• Enhancements to accommodate missing data, uncertainty, continuous phases, different boundary assumptions, non-rectangular grids and domains.

• Application to large datasets and a broad range of local states.

Kalidin

di

Kalidin

di  /  Vo

orhees

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PROGRAM & RESEARCH HIGHLIGHTS7. Data-Driven Mining of Low-Dimensional Process-Structure-Property (PSP) Linkages

A. Cecen, A. Gupta, Y. Yabansu, R. Liu, A. Agrawal ,A. Choudhary, S. R. Kalidindi

• Transferable and robust templates for the establishment of PSP linkages exchanging high value information in both directions (i.e., Homogenization and Localization).

• Automated inline analytics for large scale computing and/or experimental programs.

• Harmonious blending of physics based theories with data science tools (e.g., Machine Learning) in synergistic ways.

• IMPACT: Foundational for accelerated, high throughput, exploration of large materials design spaces.

Function  Estimation Dataset  Preparation

 

Spatial  StatisticsFeature  Extraction

Kalidindi

Agrawal/

Choudhary/

Kalidindi

IMPROVING TEAM/PROGRAM COHERENCY• The MURI scientific advisory board suggested that “an overall problem statement

that would act as an attractor to a single focus” be considered, to “promote convergence” of the three thrust areas towards the end of the program.

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Coarsening of Si particles in a liquid. There is a clear loss of facets. Note that the Wulff shape is a fully facetted shape, so this structure is evolving AWAY from the energy minimizing Wulff shape during coarsening

single material system tracked by all three thrust areas

REVIEW SCHEDULE

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REVIEW SCHEDULE

Comer

Bouman

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REVIEW SCHEDULE

James