DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Deep learning approaches for mining structure-property linkages in high contrast composites from simulation datasets

Authors:
; ; ; ; ; ;
Publication Date:
Sponsoring Org.:
USDOE
OSTI Identifier:
1548213
Grant/Contract Number:  
SC0014330; DESC0007456
Resource Type:
Publisher's Accepted Manuscript
Journal Name:
Computational Materials Science
Additional Journal Information:
Journal Name: Computational Materials Science Journal Volume: 151 Journal Issue: C; Journal ID: ISSN 0927-0256
Publisher:
Elsevier
Country of Publication:
Netherlands
Language:
English

Citation Formats

Yang, Zijiang, Yabansu, Yuksel C., Al-Bahrani, Reda, Liao, Wei-keng, Choudhary, Alok N., Kalidindi, Surya R., and Agrawal, Ankit. Deep learning approaches for mining structure-property linkages in high contrast composites from simulation datasets. Netherlands: N. p., 2018. Web. doi:10.1016/j.commatsci.2018.05.014.
Yang, Zijiang, Yabansu, Yuksel C., Al-Bahrani, Reda, Liao, Wei-keng, Choudhary, Alok N., Kalidindi, Surya R., & Agrawal, Ankit. Deep learning approaches for mining structure-property linkages in high contrast composites from simulation datasets. Netherlands. https://doi.org/10.1016/j.commatsci.2018.05.014
Yang, Zijiang, Yabansu, Yuksel C., Al-Bahrani, Reda, Liao, Wei-keng, Choudhary, Alok N., Kalidindi, Surya R., and Agrawal, Ankit. Wed . "Deep learning approaches for mining structure-property linkages in high contrast composites from simulation datasets". Netherlands. https://doi.org/10.1016/j.commatsci.2018.05.014.
@article{osti_1548213,
title = {Deep learning approaches for mining structure-property linkages in high contrast composites from simulation datasets},
author = {Yang, Zijiang and Yabansu, Yuksel C. and Al-Bahrani, Reda and Liao, Wei-keng and Choudhary, Alok N. and Kalidindi, Surya R. and Agrawal, Ankit},
abstractNote = {},
doi = {10.1016/j.commatsci.2018.05.014},
journal = {Computational Materials Science},
number = C,
volume = 151,
place = {Netherlands},
year = {Wed Aug 01 00:00:00 EDT 2018},
month = {Wed Aug 01 00:00:00 EDT 2018}
}

Journal Article:
Free Publicly Available Full Text

Citation Metrics:
Cited by: 143 works
Citation information provided by
Web of Science

Save / Share:

Works referenced in this record:

Perspective: Materials informatics and big data: Realization of the “fourth paradigm” of science in materials science
journal, April 2016

  • Agrawal, Ankit; Choudhary, Alok
  • APL Materials, Vol. 4, Issue 5
  • DOI: 10.1063/1.4946894

Materials discovery: Understanding polycrystals from large-scale electron patterns
conference, December 2016


Automated, high throughput exploration of process–structure–property relationships using the MapReduce paradigm
journal, January 2015


Statistical continuum theory for large plastic deformation of polycrystalline materials
journal, March 2001


A predictive machine learning approach for microstructure optimization and materials design
journal, June 2015

  • Liu, Ruoqian; Kumar, Abhishek; Chen, Zhengzhang
  • Scientific Reports, Vol. 5, Issue 1
  • DOI: 10.1038/srep11551

A Deep Adversarial Learning Methodology for Designing Microstructural Material Systems
conference, November 2018

  • Li, Xiaolin; Yang, Zijiang; Brinson, L. Catherine
  • ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Volume 2B: 44th Design Automation Conference
  • DOI: 10.1115/DETC2018-85633

A strong contrast homogenization formulation for multi-phase anisotropic materials
journal, June 2008

  • Fullwood, David T.; Adams, Brent L.; Kalidindi, Surya R.
  • Journal of the Mechanics and Physics of Solids, Vol. 56, Issue 6
  • DOI: 10.1016/j.jmps.2008.01.003

Vision for Data and Informatics in the Future Materials Innovation Ecosystem
journal, August 2016


Calibrated localization relationships for elastic response of polycrystalline aggregates
journal, December 2014


Including crystal structure attributes in machine learning models of formation energies via Voronoi tessellations
journal, July 2017


Microstructure of two‐phase random media. I. The n ‐point probability functions
journal, August 1982

  • Torquato, S.; Stell, G.
  • The Journal of Chemical Physics, Vol. 77, Issue 4
  • DOI: 10.1063/1.444011

Inverse methods for material design
journal, May 2014

  • Jain, Avni; Bollinger, Jonathan A.; Truskett, Thomas M.
  • AIChE Journal, Vol. 60, Issue 8
  • DOI: 10.1002/aic.14491

Modeling thermal conductivity of hemp insulation material: A multi-scale homogenization approach
journal, October 2016


Reduced-order structure-property linkages for polycrystalline microstructures based on 2-point statistics
journal, May 2017


Microstructural Materials Design Via Deep Adversarial Learning Methodology
journal, October 2018

  • Yang, Zijiang; Li, Xiaolin; Catherine Brinson, L.
  • Journal of Mechanical Design, Vol. 140, Issue 11
  • DOI: 10.1115/1.4041371

Deep Convolutional Neural Networks with transfer learning for computer vision-based data-driven pavement distress detection
journal, December 2017


Process–structure–property relationships for nugget and heat affected zone regions of AA2524–T351 friction stir welds
journal, December 2005

  • Yan, Junhui; Sutton, M. A.; Reynolds, A. P.
  • Science and Technology of Welding and Joining, Vol. 10, Issue 6
  • DOI: 10.1179/174329305X68778

Spectral representation of higher-order localization relationships for elastic behavior of polycrystalline cubic materials
journal, September 2008


Extraction of reduced-order process-structure linkages from phase-field simulations
journal, February 2017


Microstructure Representation and Reconstruction of Heterogeneous Materials Via Deep Belief Network for Computational Material Design
journal, May 2017

  • Cang, Ruijin; Xu, Yaopengxiao; Chen, Shaohua
  • Journal of Mechanical Design, Vol. 139, Issue 7
  • DOI: 10.1115/1.4036649

Data-driven reduced order models for effective yield strength and partitioning of strain in multiphase materials
journal, October 2017


Multi-scale modeling of elastic response of three-dimensional voxel-based microstructure datasets using novel DFT-based knowledge systems
journal, April 2010


Improved Scaling of Molecular Network Calculations: The Emergence of Molecular Domains
journal, January 2017

  • Gagorik, Adam G.; Savoie, Brett; Jackson, Nick
  • The Journal of Physical Chemistry Letters, Vol. 8, Issue 2
  • DOI: 10.1021/acs.jpclett.6b02921

Deep Residual Learning for Image Recognition
conference, June 2016

  • He, Kaiming; Zhang, Xiangyu; Ren, Shaoqing
  • 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
  • DOI: 10.1109/CVPR.2016.90

Key computational modeling issues in Integrated Computational Materials Engineering
journal, January 2013

  • Panchal, Jitesh H.; Kalidindi, Surya R.; McDowell, David L.
  • Computer-Aided Design, Vol. 45, Issue 1
  • DOI: 10.1016/j.cad.2012.06.006

3D Convolutional Neural Networks for Human Action Recognition
journal, January 2013

  • Ji, Shuiwang; Xu, Wei; Yang, Ming
  • IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 35, Issue 1
  • DOI: 10.1109/TPAMI.2012.59

Representation and calibration of elastic localization kernels for a broad class of cubic polycrystals
journal, August 2015


Perturbation-based stochastic multi-scale computational homogenization method for the determination of the effective properties of composite materials with random properties
journal, March 2016

  • Zhou, X. -Y.; Gosling, P. D.; Pearce, C. J.
  • Computer Methods in Applied Mechanics and Engineering, Vol. 300
  • DOI: 10.1016/j.cma.2015.10.020

Application of data science tools to quantify and distinguish between structures and models in molecular dynamics datasets
journal, August 2015


Computational Design of Hierarchically Structured Materials
journal, August 1997


Gradient-based learning applied to document recognition
journal, January 1998

  • Lecun, Y.; Bottou, L.; Bengio, Y.
  • Proceedings of the IEEE, Vol. 86, Issue 11
  • DOI: 10.1109/5.726791

Face recognition: a convolutional neural-network approach
journal, January 1997

  • Lawrence, S.; Giles, C. L.
  • IEEE Transactions on Neural Networks, Vol. 8, Issue 1
  • DOI: 10.1109/72.554195

Rethinking the Inception Architecture for Computer Vision
conference, June 2016

  • Szegedy, Christian; Vanhoucke, Vincent; Ioffe, Sergey
  • 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
  • DOI: 10.1109/CVPR.2016.308

Formulation and calibration of higher-order elastic localization relationships using the MKS approach
journal, June 2011


Bounds for effective elastic moduli of disordered materials
journal, April 1977


Knowledge discovery and data mining in pavement inverse analysis
journal, March 2013


Data science approaches for microstructure quantification and feature identification in porous membranes
journal, October 2017


Predictive analytics for crystalline materials: bulk modulus
journal, January 2016

  • Furmanchuk, Al'ona; Agrawal, Ankit; Choudhary, Alok
  • RSC Advances, Vol. 6, Issue 97
  • DOI: 10.1039/C6RA19284J

Combinatorial screening for new materials in unconstrained composition space with machine learning
journal, March 2014