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  • Sessions listed November 29 – December 2 will be held in-person in Boston.
  • Sessions listed December 6 – 8 will be offered virtually.
  • Sessions listed as available on-demand will be available on our virtual platform November 24 – January 15.

MRS is making frequent changes to the program, which is updated daily. Please check back for updates. Presenters: please refer to official email correspondence from MRS Meetings to confirm your presentation date and time.  Please contact meetings@mrs.org if there are discrepancies.

Symposium CH04—Accelerating Materials Characterization, Modeling, and Discovery by Physics-Informed Machine Learning

2021-11-29   Show All Abstracts

Symposium Organizers

Sebastian Schmitt, Helmholtz Zentrum Berlin
Maria Chan, Argonne National Laboratory
Kamal Choudhary, National Institute of Standards and Technology
Rama Vasudevan, Oak Ridge National Laboratory
Tutorial CH04: Machine Learning and AI Methods for Materials—Applications to Theory, Characterization, and Smart Experiments
Session Chairs
Sergei Kalinin
Sebastian Schmitt
Maxim A. Ziatdinov
Monday AM, November 29, 2021
Virtual

8:30 AM -
Machine Learning and AI Methods for Materials Science—Applications to Theory, Characterization, and Smart Experiments - Morning Session

Sergei Kalinin1,Maxim A. Ziatdinov1

Oak Ridge National Laboratory1

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12:30 PM - CH04.00
BREAK


1:00 PM -
Machine Learning and AI Methods for Materials Science—Applications to Theory, Characterization, and Smart Experiments - Afternoon session

Maxim A. Ziatdinov1,Sergei Kalinin1

Oak Ridge National Laboratory1

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2021-11-30   Show All Abstracts

Symposium Organizers

Sebastian Schmitt, Helmholtz Zentrum Berlin
Maria Chan, Argonne National Laboratory
Kamal Choudhary, National Institute of Standards and Technology
Rama Vasudevan, Oak Ridge National Laboratory
CH04.01: Accelerating Materials Science by Natural Language Processing, Machine Learning and High-Throughput Studies
Session Chairs
Hannah Barad
Tuesday AM, November 30, 2021
Hynes, Level 3, Room 303

10:30 AM - *CH04.01.01
Linking Text Extracted Data and Existing Resources Towards Predictive Models

Elsa Olivetti1

Massachusetts Institute of Technology1

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11:00 AM - CH04.01.03
Simultaneous Electrochemical Analysis of Material Libraries with Real Combinatorial High-Throughput Characterization

Hannah Barad1,Björn Miksch1,Peer Fischer1

Max Planck Institute for Intelligent Systems1

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11:15 AM - CH04.01.04
Machine Learning Assisted Metal-Insulator Compound Transition Discovery and Understanding—Database, New Features and Online Classifier Tool

Alexandru Georgescu1,Peiwen Ren1,Aubrey Toland2,Shengtong Zhang1,Kyle Miller1,Daniel Apley1,Elsa Olivetti3,Nicholas Wagner1,James Rondinelli1

Northwestern University1,Georgia Institute of Technology2,Massachusetts Institute of Technology3

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CH04.02: Physics-Assisted ML Methods for Knowledge Extraction I
Session Chairs
Elsa Olivetti
Tuesday PM, November 30, 2021
Hynes, Level 3, Room 303

1:30 PM - CH04.02.02
Decoding Reactive Structures in Dilute Alloy Catalysts

Jin Soo Lim2,Nicholas Marcella1,Anna Plonka1,George Yan3,Cameron Owen2,Jessi van der Hoeven2,Alexandre Foucher4,Hio Tong Ngan3,Steven Torrisi2,Nebojsa Marinkovic5,Eric Stach4,Jason Weaver6,Philippe Sautet3,Boris Kozinsky2,7,Anatoly Frenkel1,8

Stony Brook University, The State University of New York1,Harvard University2,University of California, Los Angeles3,University of Pennsylvania4,Columbia University5,University of Florida6,Robert Bosch LLC, Research and Technology Center7,Brookhaven National Laboratory8

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1:45 PM - CH04.02.04
Encoding Dynamical Information in Graph Representation Learning for Large-Scale Protein Function Prediction

Yuan Chiang1,Shu-Wei Chang1

National Taiwan University1

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2:00 PM - CH04.02.05
Ab Initio Modeling of Configurational Disorder in Complex Systems by Combining Machine Learning and Cluster Expansions

Julia Yang1,Gerbrand Ceder1,2

University of California, Berkeley1,Lawrence Berkeley National Laboratory2

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2:15 PM - CH04.02.03
Topology-Informed Machine Learning for Predicting Glasses’ Properties

Mathieu Bauchy1

University of California, Los Angeles1

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2:30 PM - CH04.02.06
Identifying High-Stability Motifs of Structural Patterns in Molecular Crystals

Rose Cersonsky1,Maria Pahknova1,Edgar Engel2,Michele Ceriotti1

École Polytechnique Fédérale de Lausanne1,University of Cambridge2

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2:45 PM - CH04.02.07
Spanning the 5D Space of Grain Boundaries—A Comprehensive Database of Grain Boundary Structures and Their Interface Energy

Eric Homer1,Gus Hart1,Derek Hensley1,Jay Spendlove1,Braxton Owens1,Lydia Serafin1

Brigham Young Univ1

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3:00 PM - CH04.02.08
Learning with Delayed Rewards—A Case Study on Inverse Defect Design in 2D Materials

Suvo Banik1,Troy Loeffler2,Rohit Batra2,Harpal Singh3,Mathew Cherukara2,Subramanian Sankaranarayanan2

University of Illinois at Chicago1,Argonne National Laboratory2,Sentient Science Corporation3

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3:15 PM - CH04.02.09
Predictive Computational Frameworks to Guide the Solid-State Synthesis of Novel Materials

Wenhao Sun1

University of Michigan1

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3:30 PM - CH04.02.10
Late News: Parsimonious Neural Networks Learn Interpretable Physical Laws

Alejandro Strachan1

Purdue University1

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2021-12-01   Show All Abstracts

Symposium Organizers

Sebastian Schmitt, Helmholtz Zentrum Berlin
Maria Chan, Argonne National Laboratory
Kamal Choudhary, National Institute of Standards and Technology
Rama Vasudevan, Oak Ridge National Laboratory
CH04.03: Image and Spectral Analysis by Computer Vision and Related Methods I
Session Chairs
Suvo Banik
Wednesday AM, December 1, 2021
Hynes, Level 3, Room 303

10:30 AM - CH04.03.01
Reconstructing the Exit Wave in High-Resolution Transmission Electron Microscopy Using Machine Learning

Jakob Schiotz1,Frederik Dahl1,Matthew Helmi Leth Larsen1,Christian Kisielowski2,Stig Helveg1,Ole Winther1,Thomas Hansen1

Technical University of Denmark1,Lawrence Berkeley National Laboratory2

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10:45 AM - CH04.03.02
Machine Learning for Information Extraction from Transmission Electron Microscopy Data

Xingzhi Wang1,2,Jie Li1,Chang Yan2,Justin Ondry3,Jakob Dahl1,2,Teresa Head-Gordon1,2,Peter Ercius2,A. Paul Alivisatos1,3

University of California, Berkeley1,Lawrence Berkeley National Laboratory2,The University of Chicago3

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11:00 AM - CH04.03.04
Convolutional Neural Networks for Recognizing Superconducting Phases in Powder X-Ray Diffraction

Nam Le1,Janna Domenico1,Eddie Gienger1,Timothy Montalbano1,Ian McCue1,Alexander New1,Christine Chung1,Elizabeth Pogue,2,Tyrel McQueen2,Christopher Stiles1

Johns Hopkins University Applied Physics Laboratory1,Johns Hopkins University2

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CH04.04: AI for Materials Design I
Session Chairs
Suvo Banik
Wednesday PM, December 1, 2021
Hynes, Level 3, Room 303

1:30 PM - *CH04.04.02
Materials Project and Data-Driven Materials Design

Kristin Persson1,2

UC Berkeley1,Lawrence Berkeley National Laboratory2

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2:00 PM - CH04.04.03
Enhancing Discovery and Characterization of Materials Far From Equilibrium with ML

Duncan Sutherland1,R. Van Dover1,Carla Gomes1,Michael Thompson1,Maximilian Amsler1,Aine Connolly1,Sebastian Ament1,John Gregoire2,Ming-Chiang Chang1

Cornell University1,California Institute of Technology2

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2:15 PM - CH04.04.04
CASTING—A Continuous Action Space Tree search for INverse desiGn

Suvo Banik1,Srilok Srinivasan2,Troy Loeffler2,Sukriti Manna1,Rohit Batra2,Henry Chan2,Pierre Darancet2,Subramanian Sankaranarayanan2,1

University of Illinois at Chicago1,Argonne National Laboratory2

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2:30 PM - CH04.04.05
Discovery of Novel Inorganic Crystal Structures via Generative Adversarial Networks.

Taylor Sparks1,Michael Alverson1,Ryan Murdock1

Univ of Utah1

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CH04.05: Poster Session: Accelerating Materials Characterization, Modeling and Discovery by Physics-Informed Machine Learning
Session Chairs
Wednesday PM, December 1, 2021
Hynes, Level 1, Hall B

8:00 PM - CH04.05.01
Late News: Development of Advanced Analysis Method Using Raman Imaging for Composite Materials

Carlos Morillo1,Kohei Tamura2,Sarina Mine2,Yuji Higuchi2,Ken-ichi Akao2

Jasco Incorporated1,Jasco Corporation2

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8:00 PM - CH04.05.02
Understanding Gold Nanorod Synthesis from Experiments and Literature Using Quantitative Analysis of Plasmonic Absorption Spectra

Samuel Gleason1,Jakob Dahl1,Mahmoud Elzouka2,Xingzhi Wang1,Sean Lubner2,Ravi Prasher2,A. Paul Alivisatos1

University of California, Berkeley1,Lawrence Berkeley National Laboratory2

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8:00 PM - CH04.05.03
Quantitative Evaluation of Uncertainty in Clustering of High Throughput Nanoindentation Data

Douglas Stauffer1,Bernie Becker1,Eric Hintsala1,Ben Stadnick1,Ude Hangen1

Bruker Nano Surfaces1

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8:00 PM - CH04.05.04
Real-Time 3D Analysis During Tomographic Experiments on tomviz

Jonathan Schwartz1,Chris Harris2,Jacob Pietryga1,Huihuo Zheng3,Prashant Kumar4,Anastasiia Visheratina4,Nicholas Kotov1,4,Yi Jiang3,Marcus Hanwell5,Robert Hovden1

University of Michigan1,Kitware2,Argonne National Laboratory3,University of Michigan–Ann Arbor4,Brookhaven National Laboratory5

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8:00 PM - CH04.05.05
Identifying Unknown Organic Molecules in Atomic Force Microscopy Images Through Deep Generative Models

Fabio Priante1,Niko Oinonen1,Fedor Urtev1,Adam Foster1,2

Aalto University1,Nano Life Science Institute (WPI-NanoLSI), Kanazawa University2

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2021-12-02   Show All Abstracts

Symposium Organizers

Sebastian Schmitt, Helmholtz Zentrum Berlin
Maria Chan, Argonne National Laboratory
Kamal Choudhary, National Institute of Standards and Technology
Rama Vasudevan, Oak Ridge National Laboratory
CH04.06: Machine Learning for Material Processing and Synthesis
Session Chairs
Jakob Dahl
Thursday AM, December 2, 2021
Hynes, Level 3, Room 303

10:30 AM - CH04.06.01
Elucidating the Weakly Reversible Cs–Pb–Br Perovskite Nanocrystal Reaction Network with High-Throughput Maps and Transformations

Jakob Dahl1,2,Xingzhi Wang1,2,Xiao Huang1,Emory Chan2,A. Paul Alivisatos1,2

University of California, Berkeley1,Lawrence Berkeley National Laboratory2

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10:45 AM - CH04.06.02
Predicting Synthesizability of Double Perovskite Halide via Machine Learning

Joonchul Kim1

Soongsil University1

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11:00 AM - CH04.06.03
“Big Data” Characterization of Material Properties and High Temperature Kinetics

James Horwath1,Peter Voorhees2,Eric Stach1

University of Pennsylvania1,Northwestern University2

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11:15 AM - CH04.06.04
Revealing Glass Forming Ability from the Structure of a Metallic Glass

Salena Huang1,Sebastian Kube1,Sungwoo Sohn1,Yanhui Liu2,Jan Schroers1

Yale University1,Chinese Academy of Sciences2

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11:30 AM - CH04.06.05
Reconstruction of Low-Index Au Surfaces Using Large-Scale Machine Learning Molecular Dynamics with Many-Body Bayesian Force Fields

Lixin Sun1,Cameron Owen1,Yu Xie1,Boris Kozinsky1

Harvard University1

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CH04.07: Advanced ML/AI Assisted Material Characterization I
Session Chairs
Adam Foster
Thursday PM, December 2, 2021
Hynes, Level 3, Room 303

1:30 PM - *CH04.07.01
Structure Discovery in Atomic Force Microscopy

Adam Foster1,2

Aalto University1,Kanazawa University2

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2:00 PM - CH04.07.03
Autonomous Identification of X-Ray Diffraction Spectra Using Probabilistic Deep Learning

Nathan Szymanski1,2,Christopher Bartel1,2,Yan Zeng2,Qingsong Tu2,Gerbrand Ceder1,2

University of California, Berkeley1,Lawrence Berkeley National Laboratory2

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2:15 PM - CH04.07.04
High-Fidelity Retrieval of Nanoscale Short-Range Order Distribution in GeSn Alloys Guided by Statistical Methods in Atom Probe Tomography

Shang Liu1,Alejandra Covian1,Cory Cline1,Jifeng Liu1

Dartmouth College1

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2:30 PM - CH04.07.05
Machine-Learning Prediction of Structural Transition Temperature in Multicaloric MTX Alloys with Model Interpretability Analysis

Timothy Hartnett1,Vaibhav Sharma2,Radhika Barua2,Prasanna Balachandran1

University of Virginia1,Virginia Commonwealth University2

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2:45 PM - CH04.07.06
Time-Resolved Phase Formation Studies Inform Machine Learning Algorithms During Autonomous Materials Discovery

Aine Connolly1,Ming-Chiang Chang1,Katie Gann1,Maximilian Amsler1,Duncan Sutherland1,Michael Thompson1,R. Van Dover1

Cornell University1

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3:00 PM - CH04.07.07
Late News: Analytical Methods to Characterize Dynamics of Individual Dislocations with DFXM

Leora Dresselhaus-Marais1

Stanford University1

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3:15 PM - CH04.03.03
Deep Learning-Based Analysis of Optical and Morphological Properties of Chiral Micron-Scale Helices

Anastasiia Visheratina1,Alexander Visheratin2,Prashant Kumar1,Nicholas Kotov1

University of Michigan–Ann Arbor1,Beehive AI2

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2021-12-06   Show All Abstracts

Symposium Organizers

Sebastian Schmitt, Helmholtz Zentrum Berlin
Maria Chan, Argonne National Laboratory
Kamal Choudhary, National Institute of Standards and Technology
Rama Vasudevan, Oak Ridge National Laboratory
CH04.08: Image and Spectral Analysis by Computer Vision and Related Methods II
Session Chairs
Monday AM, December 6, 2021
CH04-Virtual

8:00 AM - CH04.08.01
Low-Uncertainty Condensation Heat Transfer Characterization Using Intelligent Vision

Siavash Khodakarami1,Nenad Miljkovic1

University of Illinois at Urbana-Champaign1

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8:15 AM - CH04.08.02
Towards Automation of Particle Size Distribution Analysis of Catalyst Layers for Polymer Electrolyte Fuel Cells

André Colliard Granero1,2,Mohammad Javad Eslamibidgoli1,Mariah Batool3,Jasna Jankovic3,Michael Eikerling1,Kourosh Malek1

Forschungszentrum Jülich1,University of Cologne2,The University of British Columbia3

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8:30 AM - CH04.08.03
A Statistical Study of Corrosion Dynamics in Atomically-Thin Nanomaterials Utilising In Situ SEM

Ye Fan1,Ryo Mizuta1,Peter Voorhees2,Stephan Hofmann1

University of Cambridge1,Northwestern University2

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8:45 AM - CH04.08.04
Deep Learning for On-the-Fly Visualization of Large Datasets and Out-of-Distribution Data Detection

Lars Banko1,Phillip Maffettone2,Daniel Olds2,Alfred Ludwig1

Ruhr-Universität Bochum1,Brookhaven National Laboratory2

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9:00 AM - CH04.08.05
Decoding the Shift-Invariant Data—Applications for Band-Excitation Scanning Probe Microscopy

Yongtao Liu1,Rama Vasudevan1,Kyle Kelley1,Dohyung Kim2,Yogesh Sharma3,Mahshid Ahmadi2,Sergei Kalinin1,Maxim A. Ziatdinov1

Oak Ridge National Laboratory1,The University of Tennessee, Knoxville2,Los Alamos National Laboratory3

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9:15 AM - CH04.08.06
Autonomous Identification of Defects Based on Machine Learning

Jian-Min Zuo1,Renliang Yuan1

Univ of Illinois-Urbana-Champ1

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9:30 AM - CH04.08.07
Late News: Machine Learning Assisted Identification of Threading Dislocations

Bohdan Starosta1,Benjamin Hourahine1

University of Strathclyde1

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9:35 AM - CH04.08.08
A Physics-Based Model to Index Crystal Orientation Using Directional Reflectance Microscopy

Chenyang Zhu1,Matteo Seita1

Nanyang Technological University1

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9:40 AM - CH04.08.09
Late News: Machine Learning for Optimization of Optical Super-Resolution Microstructure Analysis

Alex Ulyanenkov1,Alexander Mikhalychev2,3,Konstantin Zhevno2,Svetlana Vlasenko3,Dmitri Mogilevtsev3

Atomicus LLC1,Atomicus OOO2,B.I.Stepanov Institute of Physics, NAS of Belarus3

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CH04.09: Machine Learning for Material Processing and Synthesis II
Session Chairs
Monday AM, December 6, 2021
CH04-Virtual

10:30 AM - CH04.09.01
Twinning Network Graph Analysis on Ingot-Scale Multicrystalline Structure

Takuto Kojima1,Kentaro Kutsukake2,Tetsuya Matsumoto1,Hiroaki Kudo1,Noritaka Usami1

Nagoya University1,RIKEN2

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10:45 AM - CH04.09.02
Quasi-Continuous Representation of Crystal Structure of Thin Films with Two-Dimensional X-Ray Diffraction and Non-Negative Matrix Factorization

Akihiro Yamashita1,2,Takahiro Nagata2,Shinjiro Yagyu2,Toru Asahi1,Toyohiro Chikyow2

Waseda University1,National Institute for Materials Science2

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11:00 AM - CH04.09.03
Late News: Modeling of Interdiffusion and Kirkendall Effect on the Base of Alternative Theory of Interdiffusion

Vladlena Makarova1,Andrei Nazarov1,2

National Research Nuclear University “MEPhI” (Moscow Engineering Physics Institute1,Institute for Theoretical and Experimental Physics named by A.I. Alikhanov of NRC "Kurchatov Institute"2

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11:05 AM - CH04.09.04
A Machine Learning Model to Predict Tensile Properties of Annealed Ti6Al4V Parts Prepared by Selective Laser Melting

Zhaotong Yang1,Mei Yang1,Richard Sisson1,Yanhua Li1,Jianyu Liang1

Worcester Polytechnic Institute1

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CH04.10: Bayesian and Related Optimization Methods for Materials
Session Chairs
Monday PM, December 6, 2021
CH04-Virtual

1:00 PM - CH04.10.01
Active Learning of Reactive Bayesian Force Fields—Application to Heterogeneous Catalysis Dynamics of H/Pt

Jonathan Vandermause1,Yu Xie1,Jin Soo Lim1,Cameron Owen1,Boris Kozinsky1

Harvard University1

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1:15 PM - CH04.10.02
Latent Gaussian Process Rietveld Model for High Throughput Quantitative X-Ray Diffraction Analysis

Brian DeCost1,Howie Joress1,Richard Ma1,2,Jason Hattrick-Simpers3

National Institute of Standards and Technology1,University of California, Berkeley2,University of Toronto3

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1:30 PM - CH04.10.03
Bayesian Inverse Design of High-Strength Aluminum Alloys at High Temperatures

Shimpei Takemoto1,Takeshi Kaneshita1,Kenji Nagata2,Yoshishige Okuno1,Junya Inoue3,Manabu Enoki3

Showa Denko K.K.1,National Institute for Materials Science2,The University of Tokyo3

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1:45 PM - CH04.10.04
Incorporating Physical Priors Into Probabilistic Models in Bayesian Framework

Ayana Ghosh1,Sergei Kalinin1,Maxim A. Ziatdinov1

Oak Ridge National Laboratory1

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2:00 PM - CH04.10.05
Physics-Informed CoKriging Model of a Redox Flow Battery

Amanda Howard1,Alexandre Tartakovsky1,2,Panagiotis Stinis1

Pacific Northwest National Laboratory1,University of Illinois at Urbana-Champaign2

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2:15 PM - CH04.10.06
A Facile Method to Extract a Constitutive Relation for Granular Materials Using Bayesian Optimization-Based Analysis

Kyuho Jang1,In-Suk Choi1

Seoul National University1

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2021-12-07   Show All Abstracts

Symposium Organizers

Sebastian Schmitt, Helmholtz Zentrum Berlin
Maria Chan, Argonne National Laboratory
Kamal Choudhary, National Institute of Standards and Technology
Rama Vasudevan, Oak Ridge National Laboratory
CH04.11: AI for Materials Design II
Session Chairs
Tuesday AM, December 7, 2021
CH04-Virtual

8:00 AM - CH04.11.01
Identifying the Activity Origin of a Cobalt Single-Atom Catalyst for Hydrogen Evolution Using Supervised Learning

Xinghui Liu1

Department of Chemistry, Sungkyunkwan University (SKKU), 2066 Seoburo, Jangan-Gu, Suwon 16419, Republic of Korea.1

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8:15 AM - CH04.11.02
ALIGNN—Atomistic Line Graph Neural Network for Improved Materials Property Predictions

Kamal Choudhary1,Brian DeCost1

National Institute of Standards and Technology1

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8:30 AM - CH04.11.03
Late News: Predicting the Heat Storage Properties of Salt Hydrates Using Density Functional Theory and Machine Learning

Steven Kiyabu1,Donald Siegel2

University of Michigan1,The University of Texas at Austin2

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8:45 AM - CH04.11.04
Uranium Compounds with High Thermal Conductivity Proposed by Machine Learning

Meigyoku Kin1,Masaya Kumagai1,2,3,Yuji Ohishi4,Ken Kurosaki1,5

Kyoto University1,SAKURA internet Inc.2,RIKEN3,Osaka University4,University of Fukui5

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9:00 AM - CH04.11.05
Predicting Effective Properties of Transition Metal Carbides from Electronic Structure Calculations

Katelyn Young1,Jenny Ziegler1,Zubaer Hossain1

University of Delaware1

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9:15 AM - CH04.11.06
Reinforcement Learning in Materials Science—Atomic Fabrication and Materials Design in Simulated Environments

Rama Vasudevan1,Ayana Ghosh1,Erick Orozco1,Maxim A. Ziatdinov1,Sergei Kalinin1

Oak Ridge National Laboratory1

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9:30 AM - CH04.11.07
Molecularly Resolved Segmentation of Non-Fullerene Acceptor Bulk Heterojunction—Lessons from Manifold Learning and Ensemble Clustering

Jochen Kammerer1,2,Wolfgang Köntges1,Pavlo Perkhun3,Christin Videlot-Ackermann3,Jörg Ackermann3,Rasmus Schröder1,Martin Pfannmöller1

Heidelberg University1,Karlsruhe Institute of Technology2,Aix-Marseille Université3

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9:45 AM - CH04.15.03
Late News: Accessing Negative Poisson`s Ratio of Graphene by Machine Learning Interatomic Potentials

Jing Wu1,E Zhou1,Zhenzhen Qin2,Xiaoliang Zhang3,Guangzhao Qin1

Hunan University1,Zhengzhou University2,Dalian3

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CH04.12: Advanced ML/AI Assisted Material Characterization II
Session Chairs
Tuesday AM, December 7, 2021
CH04-Virtual

10:30 AM - *CH04.12.01
To Mix or not to Mix? Settling the Matter of the Role of Vibrations in the Stability of High-Entropy Carbides

Stefano Curtarolo1

Duke University1

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11:00 AM - CH04.12.02
Can Machine Learning Help us to Understand Complex Materials and Phenomena?

Jan Schroers1,Sebastian Kube1,Guannan Liu1,Andrew Mertz1

Yale University1

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11:15 AM - CH04.12.03
Continuous Evaluation of Carrier Recombination Velocity of Grain Boundaries in Multicrystalline Si Using Machine Learning

Kentaro Kutsukake1,Kazuki Mitamura2,Takuto Kojima2,Noritaka Usami2

RIKEN1,Nagoya University2

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11:30 AM - CH04.12.04
Disentangling Ferroelectric Wall Dynamics and Identification of Pinning Mechanisms via Deep Learning

Yongtao Liu1,Roger Proksch2,Chun Yin Wong3,Maxim A. Ziatdinov1,Sergei Kalinin1

Oak Ridge National Laboratory1,Asylum Research, An Oxford Instruments Company2,The University of Tennessee, Knoxville3

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11:45 AM - CH04.12.05
Deep Learning Enables Crystallographic Information from Electron Diffraction Images

Joydeep Munshi1,Alexander Rakowski2,Benjamin Savitzky2,Colin Ophus2,Maria Chan1

Argonne National Laboratory1,Lawrence Berkeley National Laboratory2

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CH04.13: Accelerated Combinatorial and High Throughput Materials Science by ML/AI II
Session Chairs
Tuesday PM, December 7, 2021
CH04-Virtual

1:00 PM - CH04.13.01
Design of Features Based on X-ray Diffraction Patterns for Prediction of Mechanical Properties

Naoki Hato1,Masaya Kumagai1,2,3,Ken Kurosaki1,4

Kyoto University1,SAKURA internet Inc.2,RIKEN3,University of Fukui4

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1:15 PM - CH04.13.02
Combinatorial Synthesis of Heteroepitaxial, Functional Thin Films of Complex Materials with High-Throughput, In Situ, Chemical and Structural Characterization

Eun Ju Moon1,Amit Goyal1

University at Buffalo, The State University of New York1

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1:30 PM - CH04.13.03
Advanced Feature Extraction with Machine Learning and Combinatorial Methodologies for Thin-Film Photovoltaic Materials

Enric Tomas Grau-Luque1,Maxim Guc1,Fabien Atlan1,Andreas Zimmermann2,Sergio Giraldo1,Ignacio Becerril-Romero1,Alejandro Perez-Rodriguez1,3,Victor Izquierdo-Roca1

IREC1,Sunplugged GmbH2,Universitat de Barcelona3

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1:45 PM - CH04.13.04
signac—Data Management and Workflows for Computational Materials Discovery and Design

Bradley Dice1,Brandon Butler1,Sharon Glotzer1

University of Michigan1

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2:00 PM - CH04.13.05
Combining Crystal Structure Prediction and High-throughput Powder Pattern Refinement for Organic Solid Form Selection

Kiran Sasikumar1,Jacco van de Streek1,Marcus Neumann1

Avant-garde Materials Simulation GmbH1

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2:15 PM - *CH04.13.06
Similarity of Materials and Data-Quality Assessment by Unsupervised Learning

Claudia Draxl1,Simon Gabaj1,Martin Kuban1,Santiago Rigamonti1,Markus Scheidgen1

Humboldt-Universität zu Berlin1

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2:45 PM - CH04.13.07
High-Throughput Study of Antisolvents on the Stability of Multicomponent Metal Halide Perovskites Through Robotics-Based Synthesis and Machine Learning Approaches

Mahshid Ahmadi1,Kate Higgins1,Maxim A. Ziatdinov2,Sergei Kalinin2

University of Tennessee, Knoxville1,Oak Ridge National Laboratory2

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2021-12-08   Show All Abstracts

Symposium Organizers

Sebastian Schmitt, Helmholtz Zentrum Berlin
Maria Chan, Argonne National Laboratory
Kamal Choudhary, National Institute of Standards and Technology
Rama Vasudevan, Oak Ridge National Laboratory
CH04.14: Physics-Assisted ML Methods for Knowledge Extraction II
Session Chairs
Wednesday AM, December 8, 2021
CH04-Virtual

8:00 AM - *CH04.14.01
Physics-Informed Polymer Informatics

Ramamurthy Ramprasad1

Georgia Institute of Technology1

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8:30 AM - CH04.14.02
A Fundamental Training Paradigm for Graph Neural Networks to Characterize Complex Features in Atomic Microstructures

James Chapman1,Yu-Ting Hsu1,Penghao Xiao1,Xiao Chen1,Brandon Wood1

Lawrence Livermore National Laboratory1

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8:45 AM - CH04.14.03
Physics-Informed Machine Learning Enhances Predictive Design of Fluorescent DNA-Stabilized Silver Clusters

Stacy Copp1,Peter Mastracco1,Joshua Evans2,Anna Gonzalez-Rosell1,Petko Bogdanov3

University of California, Irvine1,Chaffey College2,University at Albany, State University of New York3

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9:00 AM - *CH04.14.04
Automating Data Interpretation with Deep Reasoning Networks

John Gregoire1,Di Chen2,Yiwei Bai2,Sebastian Ament2,Wenting Zhao2,Lan Zhou1,Bart Selman2,R. Van Dover2,Carla Gomes2,Dan Guevarra1

California Institute of Technology1,Cornell University2

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9:30 AM - CH04.14.05
Predicting Temperature-Dependent Oxide Redox Reactions with Machine-Learning Augmented First-Principles Calculations

Alexander Urban1,José Garrido Torres1,Vahe Gharakhanyan1,Tobias Hoffmann Eegholm1,Nongnuch Artrith1

Columbia University1

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9:45 AM - CH04.14.06
Developing Physics-Based Descriptors for Property Prediction in Oxide Glasses

Suresh Bishnoi1,Ravinder Ravinder1,N M Anoop Krishnan1

Indian Institute of Technology Delhi1

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9:50 AM - CH04.14.07
Machine Learning for Revealing Spatial Dependence Among Nanoparticles: Understanding Catalyst Film Dewetting via Gibbs Point Process Models

Mostafa Bedewy2,Ahmed Aziz Ezzat1

Rutgers, The State University of New Jersey1,University of Pittsburgh2

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9:55 AM - CH04.14.08
Defects Engineering to Design Tough Graphene

Chi Hua Yu1,2,Chang-Yan Wu1,Markus Buehler2

National Cheng Kung University1,Massachusetts Institute of Technology2

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CH04.15: Physics-Assisted ML Methods for Knowledge Extraction III
Session Chairs
Wednesday AM, December 8, 2021
CH04-Virtual

10:30 AM - *CH04.02.01
Realizing Physical Discovery in Imaging with Machine Learning

Sergei Kalinin1,Yongtao Liu1,Ayana Ghosh1,Kyle Kelley1,Kevin Roccapriore1,Maxim A. Ziatdinov1

Oak Ridge National Laboratory1

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11:00 AM - *CH04.15.01
Learning Rules for Materials Properties and Functions by Artificial Intelligence

Matthias Scheffler1

The NOMAD Laboratory at the FHI1

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11:30 AM - *CH04.04.01
Matrices, Graphs and Natural Language—Ways to Represent Materials for Machine Learning

Keith Butler1,2,Ricardo Grau-Crespo2,Luis Antunes2,Scott Midgley2,Jeyan Thiyagalingam1,Johannes Allotey3,Aron Walsh4,Alexander Moriarty4

Rutherford Appleton Laboratory1,University of Reading2,University of Bristol3,Imperial College London4

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12:00 PM - *CH04.15.02
Statistical Physics of Machine Learning

Bruno Loureiro1,Lenka Zdeborová1,Florent Krzakala1

École Polytechnique Fédérale de Lausanne1

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