2021 MRS Spring Meeting

The program is updated daily throughout the Meeting week.

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All times listed are Eastern Daylight Time.

Symposium CT05 : Artificial Intelligence and Automation for Materials Design

2021-04-17   Show All Abstracts

Symposium Organizers

Amanda Barnard, Australian National University
Bronwyn Fox, Swinburne University of Technology
Manyalibo Matthews, Lawrence Livermore National Laboratory
Krishna Rajan, University at Buffalo, The State University of New York

Symposium Support

Silver
Army Research Office
Tutorial CT05: Computational Materials Discovery using the Automatic FLOW (AFLOW) Software
Session Chairs
Marco Esters
David Hicks
Manyalibo Matthews
Corey Oses
Cormac Toher
Saturday PM, April 17, 2021
CT05

10:00 AM - *
Introduction + AFLOW Installation Help

Marco Esters1

Duke University1

Show Abstract

10:45 AM - *
Materials Database Access—AFLOW.org and AFLUX

Marco Esters1

Duke University1

Show Abstract

12:15 PM - CT05.00
BREAK


12:30 PM - *
Structural Analysis and Generation of Materials—AFLOW-SYM, AFLOW Prototype Encyclopedia, and AFLOW-XtalFinder

David Hicks1

Duke University1

Show Abstract

2:00 PM - CT05.00
BREAK


3:00 PM - *
Thermodynamics—AFLOW-CHULL and CCE

Cormac Toher1

Duke University1

Show Abstract

4:30 PM - CT05.00
BREAK


4:45 PM - *
Disorder—AFLOW-POCC

Corey Oses1

Duke University1

Show Abstract

6:15 PM - CT05.00
Q&A


Show Abstract

2021-04-18   Show All Abstracts

Symposium Organizers

Amanda Barnard, Australian National University
Bronwyn Fox, Swinburne University of Technology
Manyalibo Matthews, Lawrence Livermore National Laboratory
Krishna Rajan, University at Buffalo, The State University of New York

Symposium Support

Silver
Army Research Office
CT05.01: Machine Learning I
Session Chairs
Thomas Hammerschmidt
Krishna Rajan
Sunday AM, April 18, 2021
CT05

8:00 AM - *CT05.01.01
Network Theory Meets Materials Science

Christopher Wolverton1

Northwestern University1

Show Abstract

8:25 AM - CT05.01.02
Late News: Optimizing Complex Geometries with Feed Forward Control and Machine Learning

Clara Druzgalski1,Gabe Guss1,Ava Ashby1,Simon Lapointe1,Aiden Martin1,Maria Strantza1,Zachary Reese1,Manyalibo Matthews1

Lawrence Livermore National Laboratory1

Show Abstract

8:40 AM - *CT05.01.03
Natural Language Processing for Materials Design—What Can We Extract From the Research Literature?

Anubhav Jain1

Lawrence Berkeley National Laboratory1

Show Abstract

9:05 AM - CT05.01.04
Natural Language Processing for Insensitivity Classification of Energetic Materials

Gaurav Kumar1,Allen Garcia1,Connor O'Ryan1,Peter Chung1

University of Maryland1

Show Abstract

9:20 AM - *CT05.01.05
Active Materials Exploration and Characterization with Bayesian Optimization

Patrick Rinke1

Aalto University1

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CT05.02: Automation and High Throughput I
Session Chairs
Nicholas Kotov
Prahalada Rao
Sunday PM, April 18, 2021
CT05

10:30 AM - *CT05.02.01
Materials Informatics and Manufacturing Scalability and Sustainability

Elsa Olivetti1

Massachusetts Institute of Technology1

Show Abstract

10:55 AM - *CT05.02.02
Automated Multimodal Manufacturing Optimization

Brian Giera1,Adam Jaycox1,Kyle DeVlugt1,Joseph Nicolino1,Brian Au1,Sam Ludwig1

Lawrence Livermore National Laboratory1

Show Abstract

11:20 AM - *CT05.02.03
Autonomous End-to-End Systems for Materials Discovery

Muratahan Aykol1,Joseph Montoya1

Toyota Research Institute1

Show Abstract

11:45 AM - CT05.02.04
Robotics-Enabled Exploration of Multicomponent Lead Halide Perovskites via Machine Learning

Kate Higgins1,Sai Valleti2,Maxim Ziatdinov3,Sergei Kalinin2,3,Mahshid Ahmadi1

Joint Institute for Advanced Materials1,University of Tennessee2,Oak Ridge National Laboratory3

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CT05.03: Applications I
Session Chairs
Sanket Deshmukh
Steven Torrisi
Sunday PM, April 18, 2021
CT05

1:00 PM - *CT05.03.01
Machine Learning for the Modeling of Complex Energy Materials

Nongnuch Artrith1

Columbia University1

Show Abstract

1:25 PM - CT05.03.02
Automated In Silico Screening of Nanoporous Materials for Enhanced CO2 Capture

Rodrigo Neumann1,Fausto Martelli1,Binquan Luan1,Tonia Elengikal1,Anshul Gupta1,Guojing Cong1,Mathias Steiner1,Thomas Peters2,Flor Siperstein3,Breanndan O Conchuir1

IBM Research1,University of Connecticut2,University of Manchester3

Show Abstract

1:40 PM - CT05.03.03
Late News: Machine Learning with Persistent Homology and Chemical Word Embeddings Improves Predictive Accuracy and Interpretability in Metal-Organic Frameworks

Joseph Montoya3,Aditi Krishnapriyan1,2,Maciej Haranczyk4,Jens Hummelshoej3,Dmitriy Morozov1

Lawrence Berkeley National Laboratory1,University of California, Berkeley2,Toyota Research Institute3,IMDEA Materials Institute4

Show Abstract

1:55 PM - *CT05.03.04
Defect Detection and Uncertainty Quantification in Property Prediction with Machine Learning

Dane Morgan1,Mingren Shen1,Ryan Jacobs1,Glenn Palmer1,Kevin Field2

University of Wisconsin–Madison1,University of Michigan–Ann Arbor2

Show Abstract

2:20 PM - CT05.03.05
Machine Learning the Quantum-Chemical Properties of Metal–Organic Frameworks for Accelerated Materials Discovery with a New Electronic Structure Database

Andrew Rosen1,Shaelyn Iyer1,Debmalya Ray2,Zhenpeng Yao3,Alan Aspuru-Guzik4,Laura Gagliardi5,Justin Notestein1,Randall Snurr1

Northwestern University1,University of Minnesota Twin Cities2,Harvard University3,University of Toronto4,The University of Chicago5

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CT05.04: Material Informatics I
Session Chairs
Mathieu Bauchy
Wujie Wang
Sunday PM, April 18, 2021
CT05

4:00 PM - *CT05.04.01
Understanding and Visualizing Hyperspectral ToF-SIMS Data Sets Using Machine Learning

Paul Pigram1,Wil Gardner1,2,3,David Winkler2,4,5,Davide Ballabio6,Benjamin Muir3

La Trobe University1,La Trobe Institute for Molecular Science, La Trobe University2,CSIRO Manufacturing3,Monash Institute of Pharmaceutical Sciences, Monash University4,School of Pharmacy, University of Nottingham5,Milano Chemometrics and QSAR Research Group, Department of Earth and Environmental Sciences, University of Milano-Bicocca6

Show Abstract

4:25 PM - CT05.04.02
Charting the Low-Loss Region in Electron Energy Loss Spectroscopy with Machine Learning

Juan Rojo2,Laurien Roest1,Sabrya van Heijst1,Jaco ter Hoeve2,Louis Maduro1,Isabel Postmes1,2,Sonia Conesa-Boj1

Kavli Institute of Nanoscience Delft1,VU Amsterdam & Nikhef2

Show Abstract

4:40 PM - CT05.04.03
Discovery of Interpretable X-Ray Absorption Spectroscopy Signatures via Random Forest Machine Learning Models

Steven Torrisi1,2,Matthew Carbone3,Brian Rohr2,Joseph Montoya2,Yang Ha4,Junko Yano4,Santosh Suram2,Linda Hung2

Harvard University1,Toyota Research Institute2,Columbia University3,Lawrence Berkeley National Laboratory4

Show Abstract

4:55 PM - CT05.04.04
Late News: Machine Learning Force Fields for Understanding the Thermodynamics of Li-Ion Cathodes

Joshua Gabriel1,Juan Garcia1,Noah Paulson1,John Low1,Marius Stan1,Hakim Iddir1

Argonne National Laboratory1

Show Abstract

5:00 PM - CT05.04.05
Improvement of Adhesion Between NiTi Alloy and Diamond-Like Carbon Film by Bayesian Optimization

Masafumi Toyonaga1,Terumitsu Hasebe1,2,Shunto Maegawa2,Tomohiro Matsumoto1,2,Atsushi Hotta1,Tetsuya Suzuki1

Keio University1,Tokai University Hachioji Hospital2

Show Abstract

5:05 PM - CT05.04.06
High-Throughput Electrochemical Screening of Deep Eutectic Solvent for Use in Redox Flow Batteries

Maria Politi1,Jaime Rodriguez1

University of Washington1

Show Abstract

5:10 PM - CT05.04.07
Late News: A Materials-Informatics Based Study of Solid Electrolytes and Protective Coatings for Li Batteries

Shreyas Honrao1,2,Xin Yang3,Balachandran Radhakrishnan1,3,Shigemasa Kuwata3,Hideyuki Komatsu4,Atsushi Ohma4,John Lawson1

NASA Ames Research Center1,KBRR Wyle2,Nissan North America3,Nissan Motor Company4

Show Abstract

5:25 PM - CT05.04.08
Late News: Prediction of Bulk and Grain Boundary Ionic Conductivities for Solid-State Li-Ion Conductors by Machine Learning

Yen-Ju Wu1,Takhiro Tanaka1,Tomoyuki Komori2,Mikiya Fujii2,Hiroshi Mizuno2,Satoshi Itoh1,Tadanobu Takada1,Erina Fujita1,Yibin Xu1

National Institute for Materials Science1,Panasonic Corporation2

Show Abstract

CT05.05: Machine Learning II
Session Chairs
Krishna Rajan
Sunday PM, April 18, 2021
CT05

6:30 PM - *CT05.05.01
End-to-End Differentiability and Tensor Processing Unit Computing to Accelerate Materials’ Inverse Design

Mathieu Bauchy1,Han Liu1,Yuhan Liu1

University of California, Los Angeles1

Show Abstract

6:55 PM - CT05.05.02
Solving Inverse Problems with Differentiable Molecular Dynamics

Wujie Wang1,Simon Axelrod1,Rafael Gomez-Bombarelli1

Massachusetts Institute of Technology1

Show Abstract

7:10 PM - CT05.05.03
Graphical Model Parameters for Formation of 3D Nanomolecular Complexes

Minjeong Cha1,Emine Turali-Emre1,Xiongye Xiao2,Paul Bogdan2,Nicholas Kotov1

University of Michigan1,University of Southern California2

Show Abstract

7:25 PM - CT05.05.04
Graph Theory for Design of Complex Biomimetic Nanostructures

Nicholas Kotov1

University of Michigan1

Show Abstract

7:40 PM - CT05.05.05
Symmetry Incorporated Graph Convolutional Neural Networks for Solid-State Materials

Weiyi Gong1,Hexin Bai1,Peng Chu1,Haibin Ling2,Qimin Yan1

Temple University1,Stony Brook University, The State University of New York2

Show Abstract

2021-04-19   Show All Abstracts

Symposium Organizers

Amanda Barnard, Australian National University
Bronwyn Fox, Swinburne University of Technology
Manyalibo Matthews, Lawrence Livermore National Laboratory
Krishna Rajan, University at Buffalo, The State University of New York

Symposium Support

Silver
Army Research Office
CT05.06: Materials Informatics II
Session Chairs
Stefano Curtarolo
Amanda Parker
Monday AM, April 19, 2021
CT05

8:00 AM - *CT05.06.01
Artificial Intelligence Towards Materials Maps

Matthias Scheffler2,1,Claudia Draxl1,2

Humboldt-Universität zu Berlin1,Fritz Haber Institute of the Max Planck Society2

Show Abstract

8:25 AM - CT05.06.02
The Search for New Materials

Joe Pitfield1,Steven Hepplestone1

University of Exeter1

Show Abstract

8:40 AM - CT05.06
Break


8:55 AM - *CT05.06.04
Digital Infrastructures for Materials Research and Discovery

Nicola Marzari1

École Polytechnique Fédérale de Lausanne1

Show Abstract

9:20 AM - CT05.06.05
Automated Microstructural Feature Extraction for Accelerated Materials Discovery

Olga Wodo3,Baskar Ganapathysubramanian1,Daniel Wheeler2,Jaroslaw Zola3

Iowa State University of Science and Technology1,National Institute of Standards and Technology2,University at Buffalo, The State University of New York3

Show Abstract

9:35 AM - CT05.06.06
MPDD: Material-Property-Descriptor Database

Adam Krajewski1,ShunLi Shang1,Yi Wang1,Zi-Kui Liu1

The Pennsylvania State University1

Show Abstract

CT05.07: Data-Driven Chemistry I
Session Chairs
Casey Brock
Monday PM, April 19, 2021
CT05

10:30 AM - CT05.07.01
Inverse Design of Self-Reporting Redox-Active Materials Using Quantum Chemistry Guided Active Learning

Garvit Agarwal1,Hieu Doan1,Lily Robertson1,Lu Zhang1,Rajeev Surendran Assary1

Argonne National Laboratory1

Show Abstract

10:45 AM - CT05.07.02
Accelerated Prediction of Atomically Precise Cluster Structures Using On-the-Fly Active Learning

Yunzhe Wang1,Shanping Liu1,Sam Norwood1,Peter Lile1,Tim Mueller1

Johns Hopkins University1

Show Abstract

11:00 AM - CT05.07.03
Screening and Understanding Li Adsorption on Two-Dimensional Metallic Materials by Learning Physics

Sheng Gong1,Shuo Wang2,Taishan Zhu1,Jeffrey Grossman1

Massachusetts Institute of Technology1,University of Maryland2

Show Abstract

11:15 AM - CT05.07.04
Multi-Fidelity Information Fusion DFT Study of Doped-Graphene Single Atom Catalysts

Hud Wahab1,Gaurav Raj1,Patrick Johnson1,Lars Kotthoff1,Dilpuneet Aidhy1

University of Wyoming1

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CT05.08: Applications II
Session Chairs
Patrick Parkinson
Andrew Rosen
Monday PM, April 19, 2021
CT05

1:00 PM - *CT05.08.01
Investigating the Shapes of Bottlebrush Polymers Using Machine Learning

Sanket Deshmukh1

Virginia Tech1

Show Abstract

1:25 PM - *CT05.08.02
Searching Order within Disorder with AI-Automation

Stefano Curtarolo1

Duke University1

Show Abstract

1:50 PM - CT05.08.03
A Phase Mapping Algorithm to Accelerate High Throughput Experiments

Ming-Chiang Chang1,Sebastian Ament1,Maximillian Amsler1,2,Duncan Sutherland1,Carla Gomes1,R. Bruce van Dover1,Michael Thompson1

Cornell University1,University of Bern2

Show Abstract

2:05 PM - CT05.08.04
High Dimensional Model Representation - Gaussian Process Regression—A Powerful Tool to Learn Multivariae Functions from Sparse Data

Sergei Manzhos1,Mohamed Boussaidi1,Owen Ren1,2,Dmitry Voytsekhovsky2

INRS1,Purefacts Inc2

Show Abstract

2:20 PM - CT05.08.05
Comprehensive Comparison of Modern Sequential Design Approaches for Material Optimization—Application to Metal-Organic Frameworks

Giovanni Trezza1,Luca Bergamasco1,Matteo Fasano1,Eliodoro Chiavazzo1

Politecnico di Torino1

Show Abstract

2:35 PM - CT05.08.06
Machine Learning Tools to Accelerate Scalable Perovskite PV Manufacturing

Nicholas Rolston1,Zhe Liu2,Austin Flick1,Thomas Colburn1,Zekun Ren2,Justin Chen1,Tonio Buonassisi2,Reinhold Dauskardt1

Stanford University1,Massachusetts Institute of Technology2

Show Abstract

CT05.09: Materials Informatics III
Session Chairs
Muratahan Aykol
Bin Ouyang
Monday PM, April 19, 2021
CT05

4:00 PM - *CT05.09.01
Towards Small-Data-Driven Materials Science

Luca Ghiringhelli1

Fritz Haber Institute of the Max Planck Society1

Show Abstract

4:25 PM - CT05.09.02
Data-Driven Quantum Dot Synthesis Development in Flow

Milad Abolhasani1

North Carolina State University1

Show Abstract

4:40 PM - CT05.09.03
Machine Learning Prediction of Creep Rupture Behavior for Metal Alloys

Reihaneh Jamshidi1

University of Hartford1

Show Abstract

4:45 PM - CT05.09.04
Development of an Artificial Intelligence (AI) Based Image Processing Tool to Detect Microstructural Variations in AM Ti-6Al-4V

Rohan Casukhela1,Sriram Vijayan1,Meiyue Shao1,Matthew Jacobsen2,Joerg Jinschek1

The Ohio State University1,Air Force Research Laboratory2

Show Abstract

4:50 PM - *CT05.09.05
Coupling Machine Learning and Physics-Based Simulations to Accelerate Materials Design

Bryce Meredig1

Citrine Informatics1

Show Abstract

5:15 PM - CT05.09.06
Predicting Fracture Stress of Defective Graphene Samples Using Artificial Neural Networks

Nuwan Dewapriya1,2,Nimal Rajapakse1,3,Priyan Dias4,Ronald Miller2

Simon Fraser University1,Carleton University2,Sri Lanka Institute of Information Technology3,University of Moratuwa4

Show Abstract

5:30 PM - CT05.09.07
Explaining Neural Network Predictions of Material Strength

Terrell Mundhenk1,Ian Palmer2,Brian Gallagher1,Barry Chen1,Gerald Friedland3,Yong Han1

Lawrence Livermore National Laboratory1,Massachusetts Institute of Technology2,University of California, Berkeley3

Show Abstract

CT05.10: Deep Learning and Computer Vision
Session Chairs
Paul Pigram
Olga Wodo
Tuesday AM, April 20, 2021
CT05

8:10 PM - CT05.10.02
Using Deep Learning to Find High Performance Phase-Change Switchable Metasurface Reflectors

Jonathan Thompson1,2,Matthew Mills2

Azimuth Corporation1,Air Force Research Laboratory2

Show Abstract

8:25 PM - CT05.10.03
Late News: Automatic Characterization of Single-Walled Carbon Nanotube Film Morphologies Using Computer Vision

Phillip Williams1,Nicole Rice1,Benoit Lessard1

University of Ottawa1

Show Abstract

8:40 PM - CT05.10.04
Image Deconvolution and Resolution Enhancement in Scanning Probe Microscopy Using Deep Learning

Lalith Krishna Samanth Bonagiri1,Harry Feldman1,Yingjie Zhang1

University of Illinois at Urbana-Champaign1

Show Abstract

8:55 PM - CT05.10
Break


9:10 PM - CT05.10.05
Rapid and Flexible Classification of Scanning Transmission Electron Microscopy Data Using Few Shot Learning

Sarah Akers1,Elizabeth Kautz1,Bethany Matthews1,Le Wang1,Yingge Du1,Steven Spurgeon1

Pacific Northwest National Laboratory1

Show Abstract

9:25 PM - CT05.10.06
Machine Learning to Reveal Nanoparticle Dynamics from Liquid-Phase TEM Videos

Lehan Yao1,Zihao Ou1,Binbin Luo1,Cong Xu1,Qian Chen1

University of Illinois at Urbana-Champaign1

Show Abstract

9:30 PM - CT05.10.07
Deep Learning for Super-Resolved Atomistic Predictions from Atom Probe Tomography

Aditi Sonal1,Jith Sarker1,Baishakhi Mazumder1,Kristofer Reyes1

University at Buffalo, The State University of New York1

Show Abstract

9:45 PM - CT05.10.08
Late News: Advances in Image Driven Machine Learning for Microstructure Recognition and Characterization

Arun Baskaran1,Elizabeth Kautz2,Wufei Ma1,Aritra Chowdhury3,Bulent Yener1,Daniel Lewis1

Rensselaer Polytechnic Institute1,Pacific Northwest National Laboratory2,GE Global Research3

Show Abstract

10:00 PM - CT05.10.09
Leveraging Uncertainty from Deep Learning for Trustworthy Materials Discovery Workflows

Jize Zhang1,Bhavya Kailkhura1,Yong Han1

Lawrence Livermore National Laboratory1

Show Abstract

2021-04-20   Show All Abstracts

Symposium Organizers

Amanda Barnard, Australian National University
Bronwyn Fox, Swinburne University of Technology
Manyalibo Matthews, Lawrence Livermore National Laboratory
Krishna Rajan, University at Buffalo, The State University of New York

Symposium Support

Silver
Army Research Office
CT05.11: Applications III
Session Chairs
Manyalibo Matthews
Dane Morgan
Tuesday AM, April 20, 2021
CT05

8:00 AM - *CT05.11.01
Machine Learning Aided Discovery of Patterns in Crystal Chemistry

Krishna Rajan1

University at Buffalo, The State University of New York1

Show Abstract

8:25 AM - CT05.11.02
Discovering Relationships Between OSDAs and Zeolites Through Data Mining and Generative Neural Networks

Zachary Jensen1,Soonhyoung Kwon2,Daniel Schwable-Koda1,Rafael Gomez-Bombarelli1,Yuriy Roman-Leshkov2,Manuel Moliner3,Elsa Olivetti1

Massachusetts Institute of Technology1,Masdar Institute of Science and Technology2,Universitat Politècnica de València3

Show Abstract

8:40 AM - CT05.11.03
Graph-Based Deep Learning for Designing Stable Interfaces for Solid-State Batteries

Shubham Pandey1,Vladan Stevanovic1,2,Peter St. John2,Prashun Gorai1,2

Colorado School of Mines1,National Renewable Energy Laboratory2

Show Abstract

8:55 AM - CT05.11.04
Machine Learning Stability Rules for Complex Ionic Compounds and Its Application in the Discovery of New NASICON Materials

Bin Ouyang1,Jingyang Wang1,Tanjin He1,Christopher Bartel1,Haoyan Huo1,Yan Wang2,Valentina Lacivita2,Haegyeom Kim3,Gerbrand Ceder3

University of California, Berkeley1,Samsung Research America2,Lawrence Berkeley National Laboratory3

Show Abstract

9:10 AM - *CT05.11.05
Combining Machine Learning and Multiscale Modeling for Accelerated Battery Manufacturing Optimization

Alejandro Franco1,2,3

Université de Picardie Jules Verne1,Réseau du Stockage Electrochimique de l'Energie (RS2E)2,Institut Universitaire de France3

Show Abstract

9:35 AM - CT05.11.06
Calibration of Thermal Spray Microstructure Simulations to Experimental Data Using Bayesian Optimization

David Montes de Oca Zapiain1,Theron Rodgers1,Dan Bolintineanu1,Carianne Martinez1,Aaron Olson1,Nathan Moore1

Sandia National Laboratories1

Show Abstract

CT05.12: Data-Driven Chemistry II
Session Chairs
Alejandro Franco
Amanda Parker
Tuesday PM, April 20, 2021
CT05

11:45 AM - *CT05.12.01
Machine-Learning the Structural Stability of Intermetallic Phases with Domain Knowledge of the Interatomic Bond

Thomas Hammerschmidt1

Ruhr University Bochum1

Show Abstract

12:10 PM - CT05.12.02
Late News: Machine Learning Potentials for Copper Alloys

Angel Diaz Carral1,Xiang Xu2,Azade Yazdan Yar1,Siegfried Schmauder2,Maria Fyta1

Institute for Computational Physics, University of Stuttgart1,Institut für Materialprüfung, Werkstoffkunde und Festigkeitslehre (IMWF)2

Show Abstract

12:25 PM - CT05.12.03
Late News: Investigating Representations of Local Atomic Environments with Topology Optimization

Arindam Debnath1,Wesley Reinhart1

The Pennsylvania State University1

Show Abstract

12:40 PM - CT05.12.04
Late News: Machine Learning Prediction of the Hubbard U for Materials Containing Transition Metals

Casey Brock1,Anand Chandrasekaran1,Yuling An1,Shaun Kwak1,Mathew Halls1

Schrödinger, Inc.1

Show Abstract

12:55 PM - CT05.12.05
Automated Training of Many-Body Machine Learned Force Fields

Jonathan Vandermause1,Boris Kozinsky1

Harvard University1

Show Abstract

CT05.13: Automation and High Throughput II
Session Chairs
Brian Giera
Kate Higgins
Tuesday PM, April 20, 2021
CT05

2:15 PM - *CT05.13.01
Heterogeneous Sensing and Scientific Machine Learning for Quality Assurance in Laser Powder Bed Fusion

Prahalada Rao1,Aniruddha Gaikwad1,Brian Giera2,Gabe Guss2,Jean-Baptiste Forien2,Manyalibo Matthews2

University of Nebraska–Lincoln1,Lawrence Livermore National Laboratory2

Show Abstract

2:40 PM - CT05.13.02
High-Throughput Correlative Microscopy and Spectroscopy for Nano-Laser Development

Patrick Parkinson1,Ruqaiya Al-Abri1,Hoyeon Choi1

The University of Manchester1

Show Abstract

2:55 PM - CT05.13.03
Implementation of Benchtop NMR as an Online, High-Throughput Sensor in Automated Synthesis Systems

Anh Le-McClain1

Magritek Inc.1

Show Abstract

3:10 PM - CT05.13.04
High-Throughput and Data-Driven Strategies for the Design of Deep Eutectic Solvent Electrolytes

Jaime Rodriguez1,Maria Politi1,Lilo Pozzo1

University of Washington1

Show Abstract

3:25 PM - CT05.13.05
Machine Learning Modeling of Photodiode Signal for Selection of Laser Parameters in Laser Powder Bed Fusion Additive Manufacturing

Simon Lapointe1,Clara Druzgalski1,Gabe Guss1,Manyalibo Matthews1

Lawrence Livermore National Laboratory1

Show Abstract

3:40 PM - CT05.13.06
Decision Trees in Continuous Action Space for High-Throughput Exploration of Potential Energy Surface of Nanoclusters

Sukriti Manna1,Troy Loeffler1,Rohit Batra1,Suvo Banik1,Henry Chan1,Subramanian Sankaranarayanan1

Argonne National Laboratory1

Show Abstract

3:55 PM - CT05.13.07
Late News: High-Throughput Reaction Screening for Accelerated Materials Research

Thomas Mustard1

Schrodinger1

Show Abstract

CT05.14: Data-Driven Chemistry III
Session Chairs
Yen-Ju Wu
Wednesday AM, April 21, 2021
CT05

9:00 PM - *CT05.14.01
Active Learning for Avoiding Biases and Maximising Efficiency in Materials Design

Amanda Parker1,Amanda Barnard1

The Australian National University1

Show Abstract

9:25 PM - CT05.14.02
Unique Challenges on NNP Development and Ways to Overcome Them

Wonseok Jeong1,Sungwoo Kang1,Changho Hong1,Jeong Min Choi1,Seungwu Han1

Seoul National University1

Show Abstract

9:40 PM - CT05.14.03
Late News: Analysis on the Strengthening Mechanism of Aluminum Alloys with Bayesian Learning for Neural Networks

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

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

Show Abstract

9:55 PM - CT05.14.04
Accurate Band-Gap Database for Semiconducting Inorganic Materials—Implementation of Hybrid Functional

Sangtae Kim1,Miso Lee1,Changho Hong1,Youngchae Yoon1,Hyungmin An1,Dongheon Lee1,Wonseok Jeong1,Dongsun Yoo1,Youngho Kang2,Yong Youn1,Seungwu Han1

Seoul National University1,Incheon National University2

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10:00 PM - CT05.14.05
Developing Machine-Learning Potentials from Disordered Structures for Crystal Structure Prediction

Changho Hong1,Jeong Min Choi1,Wonseok Jeong1,Sungwoo Kang1,Suyeon Ju1,Kyeongpung Lee1,Jisu Jung1,Yong Youn2,Seungwu Han1

Seoul National University1,National Institute for Materials Science2

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10:05 PM - CT05.14.06
Efficient Sampling for Training Set of Machine Learning Potentials Using Metadynamics

Jisu Jung1,Dongsun Yoo1,Wonseok Jeong1,Seungwu Han1

Seoul National University1

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