2019 MRS Fall Meeting & Exhibit

Symposium MT03 : Automated and Data-Driven Approaches to Materials Development—Bridging the Gap Between Theory and Industry

2019-12-02   Show All Abstracts

Symposium Organizers

Kedar Hippalgaonkar, Institute of Materials Research and Engineering
Tonio Buonassisi, Massachusetts Institute of Technology
Kristin Persson, Lawrence Berkeley National Laboratory
Edward Sargent, University of Toronto

Symposium Support

Bronze
Matter & Patterns | Cell Press
MT03.01/MT02.01: Joint Session: Autonomous Science I
Session Chairs
Tonio Buonassisi
Jason Hattrick-Simpers
Kedar Hippalgaonkar
Benji Maruyama
Monday AM, December 02, 2019
Hynes, Level 2, Room 210

8:00 AM - MT03.01.01/MT02.01.01
Autonomous Research Systems for Materials Development—2019 Workshop Summary

Benji Maruyama1,Eric Stach2,Gilad Kusne3,Jason Hattrick-Simpers3,Brian DeCost3

Air Force Research Laboratory1,University of Pennsylvania2,National Institute of Standards and Technology3

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8:30 AM - MT03.01.02/MT02.01.02
Self-Driving Laboratories for Accelerating Discovery of Thin-Film Materials

Curtis Berlinguette1,Jason Hein1,Alan Aspuru-Guzik2,3,Benjamin MacLeod1,Fraser Parlane1,Brian Lam1

The University of British Columbia1,Canadian Institute for Advanced Research (CIFAR)2,The University of Toronto3

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9:00 AM - MT03.01.03/MT02.01.03
An Inter-Laboratory High Throughput Experimental and Open Materials Data Study of Sn-Zn-Ti-O

Jason Hattrick-Simpers1,Andriy Zakutayev2,Sara Barron1,Zachary Trautt1,Nam Nguyen1,Kamal Choudhary1,John Perkins2,Caleb Phillips2,Gilad Kusne1,Feng Yi1,Apurva Mehta3,Martin Green1

National Institute of Standards and Technology1,National Renewable Energy Laboratory2,SLAC National Accelerator Laboratory3

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9:15 AM - MT03.01.04/MT02.01.04
Automatic Microcrack Inspection in Photovoltaics Silicon Wafers by Unsupervised Anomaly Detection via Variational Auto-Encoder

Zhe Liu1,Felipe Oviedo1,Emanuel Sachs1,Tonio Buonassisi1

Massachusetts Institute of Technology1

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9:30 AM - MT03.01.05/MT02.01.05
Screening of High-Capacity Oxygen Storage Materials with Machine Learning Approach

Nobuko Ohba1,Takuro Yokoya2,Seiji Kajita1,Kensuke Takechi1

Toyota Central R&D Laboratories, Inc.1,Toyota Motor Corporation2

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9:45 AM -
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10:15 AM - MT03.01.06/MT02.01.06
The Metaphysics of Chemical Reactivity and Materials Discovery

Lee Cronin1

University of Glasgow1

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10:45 AM - MT03.01.07/MT02.01.07
Robot-Accelerated Perovskite Investigation and Discovery (RAPID)—A High-throughput Approach Towards Metal Halide Perovskite Single Crystal Discovery

Zhi Li1,Mansoor Ani Nellikkal2,Liana Alves2,Peter Parrilla2,Ian Pendleton2,Matthias Zeller3,Joshua Schrier4,Alexander Norquist2,Emory Chan1

Lawrence Berkeley National Lab1,Haverford College2,Purdue University3,Fordham University4

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11:00 AM - MT03.01.08/MT02.01.08
Optimizing Hole Transport Materials with a Self-Driving Thin-Film Laboratory

Benjamin MacLeod1,Curtis Berlinguette1

University of British Columbia1

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11:15 AM - MT03.01.09/MT02.01.09
Convergence of Microfluidics, Colloidal Synthesis and Machine Learning—Real-Time Optimization of Halide Exchange Reactions of Colloidal Inorganic Perovskites Quantum Dots

Robert Epps1,Michael Bowen1,Kameel Abdel-Latif1,Milad Abolhasani1

North Carolina State University1

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11:30 AM - MT03.01.10/MT02.01.10
Autonomously Optimizing Thin Film Morphologies Using Machine Vision

Fraser Parlane1,Benjamin MacLeod1,Nina Taherimakhsousi1,Alan Aspuru-Guzik2,Jason Hein1,Curtis Berlinguette1

The University of British Columbia1,University of Toronto2

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MT03.02/MT02.02: Joint Session: Autonomous Science II
Session Chairs
Gilad Kusne
Markus Reiher
Aleksandra Vojvodic
Monday PM, December 02, 2019
Hynes, Level 2, Room 210

1:30 PM - MT03.02.01/MT02.02.01
Quantum Machine Learning in Chemical Space

Anatole von Lilienfeld1

University of Basel1

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2:00 PM - MT03.02.02/MT02.02.02
AI for Automating Materials Discovery

Carla Gomes1

Cornell University1

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2:30 PM - MT03.02.03/MT02.02.03
Machine Learning Methodologies to Enhance Automated Synthesis of New Materials

Gaurav Chopra1,Jonathan Fine1,Armen Beck1

Purdue University1

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2:45 PM - MT03.02.04/MT02.02.04
Autonomous Research Systems—Phase Mapping & Materials Optimization

Gilad Kusne1

National Institute of Standards and Technology1

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3:00 PM -
BREAK


3:30 PM - MT03.02.05/MT02.02.05
Information Extraction and Learning by Large-Scale Text-Mining of the Scientific Literature

Gerbrand Ceder1

University of California, Berkeley1

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4:00 PM - MT03.02.06/MT02.02.06
Autonomous Scanning Droplet Cell for On-Demand Alloy Electrodeposition and Characterization

Brian DeCost1,Howie Joress1,Trevor Braun1,Zachary Trautt1,Gilad Kusne1,Jason Hattrick-Simpers1

National Institute of Standards and Technology1

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4:30 PM - MT03.02.07/MT02.02.07
Autonomous Electrolyte Discovery for Batteries with Experimentally Informed Bayesian Optimization

Adarsh Dave1,Sven Burke1,Jared Mitchell1,Kirthevasan Kandasamy1,Biswajit Paria1,Barnabas Poczos1,Venkatasubramanian Viswanathan1,Jay Whitacre1

Carnegie Mellon University1

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MT03.03: Poster Session I: Autonomous Science
Session Chairs
Tonio Buonassisi
Kedar Hippalgaonkar
Kristin Persson
Monday PM, December 02, 2019
Hynes, Level 1, Hall B

8:00 PM - MT03.03.01
A Comparative Study of Experiments and Simulations on Grain-Boundary Formation of Polycrystalline Ba122 Phase Iron-Based Superconductors

Yuki Okada1,Shinnosuke Tokuta1,Yusuke Shimada2,Akimitsu Ishii1,Akinori Yamanaka1,Akiyasu Yamamoto1

Tokyo University of Agriculture and Technology1,Tohoku University2

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8:00 PM - MT03.03.02
Raman Mapping of Graphene-Based Materials—A Statistical Guide to Significance

Stuart Goldie1,Karl Coleman1

Durham University1

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8:00 PM - MT03.03.03
High-Throughput Screening of p-Type Transparent Oxide Semiconductors

Miso Lee1,Yong Youn1,Kanghoon Yim2,Seungwu Han1

Seoul National University1,Korea Institute of Energy Research2

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8:00 PM - MT03.03.04
Deep Learning Based Automatic Defect Analysis System for Static and Dynamic Electron Microscopy Data

Mingren Shen1,Guanzhao Li1,Dongxia Wu1,Jack Haley2,Wei Li3,Hima Adusumilli4,Jacob Greaves1,Wei Hao4,Nathaniel Krakauer4,Leah Krudy5,Yuhan Liu4,Jacob Perez4,Varun Sreenivasan4,Bryan Sanchez6,Oigimer Torres6,Kevin Field7,Dane Morgan1

University of Wisconsin-Madison1,University of Oxford2,Google3,University of Wisconsin–Madison4,Hope College5,University of Puerto Rico at Mayagüez6,Oak Ridge National Laboratory7

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8:00 PM - MT03.03.05
Spectrum Adapted Expectation-Maximization Algorithm for High-Throughput Peak Shift Analysis in Synchrotron X-Ray Operando Spectromicroscopy

Naoka Nagamura1,2,Tarojiro Matsumura3,Shotaro Akaho3,Kenji Nagata1,2,Yasunobu Ando3

National Institute for Materials Science1,Japan Science and Technology Agency, PRESTO2,National Institute of Advanced Industrial Science and Technology3

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8:00 PM - MT03.03.06
Fabrication of Composition Gradient Polymer Films at Elevated Temperatures for High-Throughput Characterization

Aaron Liu1,Ezgi Dogan-Guner1,Michael McBride1,Zihao Qu1,Martha Grover1,J Meredith1,Elsa Reichmanis1,Jun Amano2,Karsten Bruening2

Georgia Institute of Technology1,Konica Minolta Laboratory USA2

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8:00 PM - MT03.03.07
Enabling Correlative Spatially-Resolved Non-Uniformity Analysis of Perovskite Degradation via Machine Learning

Zhe Liu1,Shijing Sun1,Noor Titan Putri Hartono1,Armi Tiihonen1,Janak Thapa1,Felipe Oviedo1,Tonio Buonassisi1

Massachusetts Institute of Technology1

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8:00 PM - MT03.03.08
Data-Driven Sliding Mode Control for Pulses of Fluorescence in STED Microscopy Based on Förster Resonance Energy Transfer Pairs

Maison Clouatre1,Makhin Thitsa1

Mercer University1

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8:00 PM - MT03.03.09
Realizing Bulk, Stable Low Work Function Materials

Lin Lin1,Ryan Jacobs1,Dane Morgan1,John Booske1

University of Wisconsin--Madison1

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8:00 PM - MT03.03.10
OpenKIM—Reliable Interatomic Models for Multiscale Simulations

Ryan Elliott1,Ellad Tadmor1

University of Minnesota1

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8:00 PM - MT03.03.11
Density Functional Theory Simulation on Material Science—Bridging the Gap Between Theory and Experiment

ChunYu Lu1,Srinivasa Tamalampudi1,Nitul Rajput1,Boulos Alfakes1,Tuza Olukan1,Matteo Chiesa1

Khalifa University1

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8:00 PM - MT03.03.12
Transfer Learning—A Next Key Driver of Accelerating Materials Discovery with Machine Learning

Chang Liu1,Hironao Yamada2,Stephen Wu1,3,Yukinori Koyama4,Shenghong Ju5,Junichiro Shiomi5,4,Junko Morikawa6,4,Ryo Yoshida1,3,4

The Institute of Statistical Mathematics1,Tokyo University of Pharmacy and Life Sciences2,The Graduate University for Advanced Studies3,National Institute for Materials Science4,The University of Tokyo5,Tokyo Institute of Technology6

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8:00 PM - MT03.03.13
Data Acquisition and Prediction of Processing Parameter of Casting Process

DongEung Kim1,Moon-Jo Kim1

Korea Institute of Industrial Technology1

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8:00 PM - MT03.03.14
Origin and Design of Disorder Tolerance in Piezoelectric Materials

Handong Ling1,Shyam Dwaraknath2,Kristin Persson2,1

University of California, Berkeley1,Lawrence Berkeley National Laboratory2

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8:00 PM - MT03.03.15
Process Planning of Laser Aided Additive Manufacturing by Machine Learning Integrated Finite Element Modelling

Kai Ren1,Youxiang Chew1,Guijun Bi1

Singapore Institute of Manufacturing Technology1

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8:00 PM - MT03.03.18
Classifying and Predicting the Electron Affinity of Hydrocarbons Using Machine Learning

Dooman Akbarian1,Behzad Damirchi1,Hunter Woodward2,Jonathan Moore2,Adri van Duin1

The Pennsylvania State University1,The Dow Chemical Company2

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2019-12-03   Show All Abstracts

Symposium Organizers

Kedar Hippalgaonkar, Institute of Materials Research and Engineering
Tonio Buonassisi, Massachusetts Institute of Technology
Kristin Persson, Lawrence Berkeley National Laboratory
Edward Sargent, University of Toronto

Symposium Support

Bronze
Matter & Patterns | Cell Press
MT03.04: Cognitive Materials Discovery
Session Chairs
Sergey Barabash
Jason Hattrick-Simpers
Tuesday AM, December 03, 2019
Hynes, Level 2, Room 208

8:00 AM - MT03.04.01
Accelerated Materials Discovery Using Theory, Computation, Optimization and Natural Language Processing

Anubhav Jain1

Lawrence Berkeley National Laboratory1

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8:30 AM - MT03.04.02
Machine Learning of Reaction Pathways in Chemical Vapor Deposition for Directed Synthesis of Two-Dimensional Chalcogenides

Aravind Krishnamoorthy1,Pankaj Rajak1,2,Sungwook Hong1,Ken-ichi Nomura1,Aiichiro Nakano1,Rajiv Kalia1,Priya Vashishta1

University of Southern California1,Argonne National Laboratory2

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8:45 AM - MT03.04.03
Cooperative, Heterogeneous and Adaptive Robots for Materials Discovery

Yue Wu1,David Marquez-Gamez1,2,Andrew Cooper1,2

University of Liverpool1,Leverhulme Research Centre for Functional Materials Design2

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9:00 AM - MT03.04.04
High-Throughput Design of Organic Friction Reducers in Engine Oils

Jing Yang1,Jon Paul Janet1,Fang Liu1,Heather Kulik1

Massachusetts Institute of Technology1

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9:15 AM - MT03.04.05
High-Throughput Computational Discovery of In2Mn2O7 as a High Curie Temperature Ferromagnetic Semiconductor for Spintronics

Geoffroy Hautier1,Wei Chen1,Janine George1,Joel Varley2,Gian-Marco Rignanese1

Université catholique de Louvain1,Lawrence Livermore National Laboratory2

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9:30 AM - MT03.04.06
Cognitive Materials Discovery and Onset of the New Discovery Paradigm

Dmitry Zubarev1

IBM Almaden Research Center1

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10:00 AM -
BREAK


MT03.05: Machine Learning Augmented High Throughput Characterization I
Session Chairs
Dmitry Zubarev
Tuesday AM, December 03, 2019
Hynes, Level 2, Room 208

10:30 AM - MT03.05.01
Bridging the Electronic, Atomistic and Mesoscopic Scales Using Machine Learning

Subramanian Sankaranarayanan1,2

Argonne National Laboratory1,University of Illinois at Chicago2

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11:00 AM - MT03.05.02
Accelerating Development of Materials for Industrial and High-Tech Applications with Data-Driven Analysis and Simulations

Sergey Barabash1

Intermolecular Inc1

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11:30 AM - MT03.05.03
Exploring Large Scale ToF-SIMS Data Matrices Using Artificial Neural Networks: Polymers and Biointerfaces

Paul Pigram1,Robert Madiona1,2,Wil Gardner1,2,Nicholas Welch2,David Winkler1,2,3,Benjamin Muir2

La Trobe University1,CSIRO Manufacturing2,University of Nottingham3

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11:45 AM - MT03.05.04
Integrate Machine Learning in Describing Radiation-Assisted Microstructural Evolution

Miaomiao Jin1,2,Penghui Cao3,Michael Short1

Massachusetts Institute of Technology1,Idaho National Laboratory2,University of California Irvine3

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MT03.06: Machine Learning Augmented High Throughput Characterization II
Session Chairs
Apurva Mehta
Joshua Schrier
Tuesday PM, December 03, 2019
Hynes, Level 2, Room 208

1:30 PM - MT03.06.01
Towards Automated Information Extraction from High Resolution Transmission Electron Microscopy Images

Mary Scott1,2

University of California, Berkeley1,Lawrence Berkeley National Laboratory2

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2:00 PM - MT03.06.02
Automated Image Segmentation in Materials Microscopy with Deep Learning Methods

Bo Lei1,Elizabeth Holm1

Carnegie Mellon University1

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2:15 PM - MT03.06.03
Feature Extraction from SEM Images to Predict Materials Performance Using Computer Vision and Deep Learning Methods

T. Yong-Jin Han1

Lawrence Livermore National Laboratory1

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2:30 PM - MT03.06.04
Multi-Class Inclusion Identification Using Supervised Learning and Unsupervised Learning

Nan Gao1,Mohammad Abdulsalam1,Bryan Webler1,Elizabeth Holm1

Carnegie Mellon University1

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2:45 PM - MT03.06.05
High Throughput Transmission Electron Microscopy—Closing the High Throughout Material Discovery Paradigm

Catherine Groschner1,Mary Scott1,2

University of California, Berkeley1,Lawrence Berkeley National Laboratory2

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3:00 PM -
BREAK


MT03.07: Towards Lab Automation
Session Chairs
Mary Scott
Shijing Sun
Tuesday PM, December 03, 2019
Hynes, Level 2, Room 208

3:30 PM - MT03.07.01
How Do We ESCALATE Lab Automation and Data Collection for RAPID Discovery of Perovskites?

Joshua Schrier1

Fordham University1

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4:00 PM - MT03.07.02
AI–Based Learning Machines to Accelerate Discovery of New Materials

Apurva Mehta1

Stanford Synchrotron Radiation Lightsource1

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4:30 PM - MT03.07.03
Accurate and Explainable Machine Learning of Chemical Reactivity in Transition Metal Complexes

Pascal Friederich1,2,Gabriel dos Passos Gomes1,Riccardo De Bin3,David Balcells3,Alan Aspuru-Guzik1,4

University of Toronto1,Karlsruhe Institute of Technology2,University of Oslo3,Vector Institute for Artificial Intelligence4

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4:45 PM - MT03.07.04
Reliability Prediction and Diagnosis of Next-Generation Photovoltaics Using Sparse Datasets and Semi-Supervised Machine Learning

Felipe Oviedo1,Hansong Xue2,Jose Perea1,3,Thomas Heumüller3,Zekun Ren2,Zhe Liu1,Shijing Sun1,John Fisher1,Christoph Brabec3,Tonio Buonassisi1

Massachusetts Institute of Technology1,Solar Energy Research Institute of Singapore (SERIS)2,Institute of Materials for Electronics and Energy Technology (i-MEET), Friedrich-Alexander University Erlangen-Nürnberg3

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2019-12-04   Show All Abstracts

Symposium Organizers

Kedar Hippalgaonkar, Institute of Materials Research and Engineering
Tonio Buonassisi, Massachusetts Institute of Technology
Kristin Persson, Lawrence Berkeley National Laboratory
Edward Sargent, University of Toronto

Symposium Support

Bronze
Matter & Patterns | Cell Press
MT03.08/MT02.07: Joint Session: Machine Learning Augmented High-Thoughput Experimentation I
Session Chairs
Jason Hattrick-Simpers
Bruce van Dover
Wednesday AM, December 04, 2019
Hynes, Level 2, Room 210

8:00 AM - MT03.08.01/MT02.07.01
Automating Experiments and Data Interpretation in Solar Fuels and Catalysis Research

John Gregoire1

California Institute of Technology1

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8:30 AM - MT03.08.02/MT02.07.02
Cooperative Learning for Materials Systems

Valentin Stanev1

University of Maryland, College Park1

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8:45 AM - MT03.08.03/MT02.07.03
Exploring Catalyst Chemistries beyond Scaling Laws using Statistical Learning

Scott Broderick1,Aparajita Dasgupta1,Thaicia Stona1,Krishna Rajan1

University at Buffalo1

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9:00 AM - MT03.08.04/MT02.07.04
Graph Theory and Machine Learning Uncover Zeolite Transformation Pathways

Daniel Schwalbe Koda1,Wujie Wang1,Rafael Gomez-Bombarelli1

Massachusetts Institute of Technology1

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9:15 AM - MT03.08.05/MT02.07.05
Automatic Processing of the Scientific Literature to Accelerate Nanomaterials Design and Discovery

Anna Hiszpanski1,Brian Gallagher1,Karthik Chellappan1,Peggy Pk Li1,Shusen Liu1,Hyojin Kim1,Jinkyu Han1,Bhavya Kailkhura1,David Buttler1,T. Yong-Jin Han1

Lawrence Livermore National Laboratory1

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9:30 AM -
BREAK


10:00 AM - MT03.08.07/MT02.07.07
High Throughput Experimental Materials Research Methods at NREL

Andriy Zakutayev1

National Renewable Energy Laboratory1

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10:30 AM - MT03.08.08/MT02.07.08
Machine Learning-Assisted High Throughput Synthesis and Characterization of Hybrid Polymer-Carbon Nanotubes Composites for Thermoelectric Application

Daniil Bash1,2,Anas Abutaha2,Yang Xu2,Yee Fun Lim2,Vijila Chellappan2,Zekun Ren3,Isaac Tian3,1,Pawan Kumar2,Swee Liang Wong2,Jose Recatala Gomez2,4,Jayce Cheng2,Tonio Buonassisi5,3,Kedar Hippalgaonkar2

National University of Singapore1,Institute of Materials Research and Engineering2,Singapore-MIT Alliance for Research and Technology (SMART)3,University of Southampton4,Massachusetts Institute of Technology5

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10:45 AM - MT03.08.09/MT02.07.09
Data-driven Materials Design of Halide Perovskites for Photovoltaic Applications

Shijing Sun1,Noor Titan Putri Hartono1,Felipe Oviedo1,Zekun Ren1,Janak Thapa1,Zhe Liu1,Armi Tiihonen1,Ian Marius Peters1,Juan Pablo Correa Baena2,Tonio Buonassisi1,Savitha Ramasamy3

Massachusetts Institute of Technology1,Georgia Institute of Technology2,Institute of Infocomm Research3

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11:00 AM - MT03.08.10/MT02.07.10
Application of Variational Autoencoders to Create Thin Film Structure Zone Diagrams

Lars Banko1,Yury Lysogorskiy1,Ralf Drautz1,Alfred Ludwig1

Ruhr-Universität Bochum1

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11:15 AM - MT03.08.11/MT02.07.11
Generative Adversarial Networks with Molecular Graph Convolution for Learning Secondary Structures of Functional Biomolecules

Siddharth Rath1,Oliver Nakano-Baker1,Jonathan Francis-Landau1,Ximing Lu1,Kevin Jamieson1,Burak Ustundag1,2,Mehmet Sarikaya1

University of Washington1,Istanbul Teknik Universitesi2

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MT03.09/MT02.08: Joint Session: Machine Learning Augmented High-Thoughput Experimentation II
Session Chairs
Ichiro Takeuchi
Andriy Zakutayev
Wednesday PM, December 04, 2019
Hynes, Level 2, Room 210

1:30 PM - MT03.09.01/MT02.08.01
Prediction Interpretability in Data-Driven Materials Development

Julia Ling1,Astha Garg1,James Peerless1,Erin Antono1,Edward Kim1,Yoolhee Kim1,Nils Persson1,Malcolm Davidson1

Citrine Informatics1

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2:00 PM - MT03.09.02/MT02.08.02
Network Theory Meets Materials Science

Christopher Wolverton1,Vinay Hegde1,Muratahan Aykol2

Northwestern University1,Toyota Research Institute2

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2:30 PM -
BREAK


3:30 PM - MT03.09.03/MT02.08.03
A Database to Enable the Discovery and Design of Atomically Precise Nanoclusters

Sukriti Manna1,Peter Lile1,Alberto Hernandez1,Tim Mueller1

Johns Hopkins University1

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3:45 PM - MT03.09.04/MT02.08.04
Data Driven Experimental Discovery of New Nitride Materials

Andriy Zakutayev1,Sage Bauers1,Elisabetta Arca1,Wenhao Sun2,Chris Bartel3,John Perkins1,Aaron Holder3,Stephan Lany1,Gerbrand Ceder2

National Renewable Energy Laboratory1,University of California, Berkeley2,University of Colorado Boulder3

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4:00 PM - MT03.09.05/MT02.08.05
Active Learning for Nanophotonic Design via Multi-Fidelity Physical Models

Harry Atwater1,Jialin Song1,Yury Tokpanov1,Yuxin Chen1,Dagny Fleischman1,Katherine Fountaine2,Yisong Yue1

California Institute of Technology1,Northrop Grumman Corporation2

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4:30 PM - MT03.09.06/MT02.08.06
Accelerating Materials Discovery through Rapid Construction of Processing Phase Diagrams

Duncan Sutherland1,Aine Connolly1,Sebastian Ament1,Michael Thompson1,Carla Gomes1,Bruce van Dover1

Cornell University1

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4:45 PM - MT03.09.07/MT02.08.07
High-Throughput Screening of Perovskite-Inspire Materials Using Steady-State Photoconductivity and Bayesian Optimization

Jose Perea1,Felipe Oviedo1,Han Yin1,Janak Thapa1,Armi Tiihonen1,Zhe Liu1,Ian Marius Peters1,Shijing Sun1,Rafael Jaramillo1,Tonio Buonassisi1

Massachusetts Institute of Technology1

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MT03.10: Poster Session II: Machine Learning Augmented High-Throughput Experimentation
Session Chairs
Tonio Buonassisi
Kedar Hippalgaonkar
Kristin Persson
Edward Sargent
Wednesday PM, December 04, 2019
Hynes, Level 1, Hall B

8:00 PM - MT03.10.01
Prediction of Physical Properties of Thermosetting Resin by Using Machine Learning and Structural Formulas of Raw Materials

Kokin Nakajin1,2,Takuya Minami1,Masaaki Kawata3,Toshio Fujita1,2,Katsumi Murofushi1,Hiroshi Uchida1,Kazuhiro Omori1,Yoshishige Okuno1

SHOWADENKO K. K.1,Research Association of High-Throughput Design and Development for Advanced Functional Materials2,National Institute of Advanced Industrial Science and Technology3

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8:00 PM - MT03.10.02
Development of Thermodynamically Grounded Deep Learning Method—Application to Predict Vapor-Liquid Equilibrium of Hydrocarbon mixtures

Wooyeon Kim1,Min Jae Ko1

Hanyang University1

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8:00 PM - MT03.10.03
Comprehensive Quantification of the Heterogeneous Structure of Mycelium

Eric Oliverio1,Thaicia Stona de Almeida1,Prathima Nalam1,Olga Wodo1,Jessie Bie-Kaplan2,Gavin McIntyre2

University at Buffalo, The State University of New York1,Ecovative Design2

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8:00 PM - MT03.10.04
Reinforcement Learning Based 3D Molecular Structure Prediction of Aromatic Hydrocarbon Family

Soo Kyung Kim1,Youngwoo Cho1,Piyush Karande1,Joanne Taery Kim1,Peggy Pk Li1,T. Yong-Jin Han1

Lawrence Livermore National Laboratory1

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8:00 PM - MT03.10.05
Comparison of Neural Networks Based Models and Molecular Fingerprints for the Accurate Density Prediction of Small Molecules

Donald Loveland1,Joanne Taery Kim1,Soo Kyung Kim1,Piyush Karande1,Peggy Pk Li1,Youngwoo Cho1,T. Yong-Jin Han1

Lawrence Livermore National Laboratory1

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8:00 PM - MT03.10.06
Predicting Accurate Adsorption Energies of Mono and Diatomic Gases on Transition Metal Surfaces Using Machine Learning

Sanjay Nayak1,Satadeep Bhattacharjee1,Seung Cheol Lee1

Indo-Korea Science and Technology Centre, Bengaluru1

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8:00 PM - MT03.10.07
Machine Learning-Directed Navigation of Synthetic Design Space—A Statistical Learning Approach to Controlling the Synthesis of Perovskite Halide Nanoplatelets in the Quantum-Confined Regime

Erick Braham1

Texas A&M University1

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8:00 PM - MT03.10.08
Computational Design of Iron-Based Amorphous Magnetocaloric Alloys and Exploration of Vast Material Search Spaces

Adam Krajewski1,2,Matthew Willard1

Case Western Reserve University1,The Pennsylvania State University2

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8:00 PM - MT03.10.09
Modeling Transport Current in Polycrystalline Superconducting Materials

Akiyasu Yamamoto1,Takuya Obara1

Tokyo University of Agriculture and Technology1

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8:00 PM - MT03.10.10
High-Throughput Computation and Evaluation of Raman Spectra

Qiaohao Liang1,Shyam Dwaraknath2,Kristin Persson1,2

University of California, Berkeley1,Lawrence Berkeley National Laboratory2

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8:00 PM - MT03.10.11
Alkyltin Keggin Clusters as Photoresist Material for Extreme Ultraviolet Lithography

Rebecca Stern1,Danielle Hutchison2,Morgan Olsen2,Lev Zakharov2,Kristin Persson1,3,May Nyman2

University of California, Berkeley1,Oregon State University2,Lawrence Berkeley National Laboratory3

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8:00 PM - MT03.10.12
Symmetry in Ab Initio Prediction of Metal Organic Frameworks

James Darby1,Mihails Arhangelskis2,Athanassios Katsenis2,Joseph Marrett2,Tomislav Friščić2,Andrew Morris3

University of Cambridge1,McGill University2,University of Birmingham3

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8:00 PM - MT03.10.13
Development of Machine Learning Potential for Sin Clusters

Seokmin Lim1,2,Minkyu Park1,Seungchul Kim1,2,Yong-Sung Kim3,2

Korea Institute of Science and Technology1,University of Science and Technology2,Korea Research Institute of Standards and Science3

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8:00 PM - MT03.10.14
Model-Based Optimization of Laser-reduced Graphene with Sparse Datasets

Hud Wahab1,Alexander Tyrrell1,Vivek Jain1,Lars Kotthoff1,Patrick Johnson1

University of Wyoming1

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8:00 PM - MT03.10.15
High-Throughput Data Generation and Analysis with the Signac Software Framework

Carl Simon Adorf1,Vyas Ramasubramani1,Bradley Dice1,Sharon Glotzer1

University of Michigan1

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8:00 PM - MT03.10.16
Autonomous Research Systems ARES™ for Materials Development

Benji Maruyama1,J. Daniel Berrigan1,Rahul Rao2,Ahmad Islam2,Jennifer Carpena2,Michael Susner2,Thomas Hardin2,Megan Creighton3,Kristofer Reyes4,Jay Myung5,Mark Pitt5

Air Force Research Laboratory1,UES Inc.2,National Research Council3,University at Buffalo, The State University of New York4,The Ohio State University5

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8:00 PM - MT03.10.17
A New Cure Kinetic Model of Polymeric Sealants and Its Application to Simulating their Mechanical Behaviour in Industrial Processes

Jae-Hyuk Choi1,Wonbo Shim1,Doyoung Kim1,Chul Hong Rhie2,Woong-Ryeol Yu1

Seoul National University1,Hyundai Motor Company2

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8:00 PM - MT03.11.18
PDPep: Protein-Derived-Peptides for Materials Science and Biomedical Device Applications—A Machine Learning Approach

Siddharth Rath1,Jonathan Francis-Landau1,Chris Pecunies1,Jacob Rodriguez1,Deniz Yucesoy1,Rene Overney1,Sami Dogan1,Mehmet Sarikaya1

University of Washington1

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8:00 PM - MT03.12.19
Computational Design of Solid-State Electrolytes for All-Solid-State Li Batteries

Wonseok Jeong1,Youngho Kang2,Seungwu Han1

Seoul National University1,Korea Institute of Materials Science2

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2019-12-05   Show All Abstracts

Symposium Organizers

Kedar Hippalgaonkar, Institute of Materials Research and Engineering
Tonio Buonassisi, Massachusetts Institute of Technology
Kristin Persson, Lawrence Berkeley National Laboratory
Edward Sargent, University of Toronto

Symposium Support

Bronze
Matter & Patterns | Cell Press
MT03.11: High Performance Computing and Screening of Materials
Session Chairs
Mohamed Eddaoudi
Yousung Jung
Thursday AM, December 05, 2019
Hynes, Level 2, Room 208

8:00 AM - MT03.11.01
Reproducibility of Materials Simulations and Accessibility to Data

Giulia Galli1

University of Chicago1

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8:30 AM - MT03.11.02
Niobium Oxide Dihalides NbOX2—A New Family of Two-Dimensional van der Waals Layered Materials with Intrinsic Ferroelectricity and Antiferroelectricity

Yinglu Jia1,2,Min Zhao1,Gaoyang Gou1,Xiao Zeng2,Ju Li3

Xi'an Jiaotong University1,University of Nebraska-Lincoln2,Massachusetts Institute of Technology3

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8:45 AM - MT03.11.03
Virtual High-Throughput Screening of Photoactive Quaternary Oxides

Daniel Davies1,Keith Butler2,Aron Walsh1

Imperial College London1,STFC2

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9:00 AM - MT03.11.04
Monte-Carlo Tree Search for Oil Molecules Driven by Ultra-Fast Molecular Dynamics Evaluations

Seiji Kajita1,Tomoyuki Kinjyo1,Tomoki Nishi1

Toyota Central R&D Labs.1

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9:15 AM - MT03.11.05
Determining the Nature of Electron and Hole Charge Carriers from First-Principles Calculation Data

Daniel Davies1,Christopher Savory2,David Scanlon2,Benjamin Morgan3,Aron Walsh1

Imperial College London1,University College London2,University of Bath3

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9:30 AM - MT03.11.06
What Does “Cheap” Materials Property Prediction Enable?

Shyue Ping Ong1,Chi Chen1,Xiangguo Li1,Zhi Deng1,Yunxing Zuo1

University of California, San Diego1

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10:00 AM -
BREAK


MT03.12: High Performance Computing, DFT with Machine Learning
Session Chairs
Giulia Galli
Shyue Ping Ong
Thursday AM, December 05, 2019
Hynes, Level 2, Room 208

10:30 AM - MT03.12.01
Solid State Materials Discovery Using Computational and Data-Driven Approaches

Yousung Jung1

KAIST1

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11:00 AM - MT03.12.02
Pawpyseed—Post-Processing Tools for PAW Wavefunctions

Kyle Bystrom1,Danny Broberg2,Shyam Dwaraknath1,Kristin Persson1,2,Mark Asta2,1

Lawrence Berkeley National Laboratory1,University of California, Berkeley2

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11:15 AM - MT03.12.03
ARTEMIS—Ab Initio Restructuring Tool Enabling the Modelling of Interface Structures

Ned Taylor1,Francis Davies1,Shane Davies1,Conor Price1,Steven Hepplestone1

University of Exeter1

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11:30 AM - MT03.12.04
Design Strategies for the Construction of Metal-Organic Frameworks

Mohamed Eddaoudi1

King Abdullah University of Science and Technology1

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MT03.13: Machine Learning Enabled Materials Descriptors
Session Chairs
Daniel Davies
Jatin Kumar
Zachary Ulissi
Aleksandra Vojvodic
Thursday PM, December 05, 2019
Hynes, Level 2, Room 208

1:30 PM - MT03.13.01
Activity and Stability—All Simultaneously Please

Aleksandra Vojvodic1

University of Pennsylvania1

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2:00 PM - MT03.13.02
Data-Driven Approach for Core-Loss Spectroscopy—Prediction of Spectra and Quantification of Properties

Shin Kiyohara1,Masashi Tsubaki2,Teruyasu Mizoguchi1

The University of Tokyo1,Artificial Intelligence Research Center2

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2:15 PM - MT03.13.03
Rapid Inference of Optical Constants and Thickness of Thin Films by Supervised Machine Learning

Siyu Tian1,2,Zhe Liu3,Vijila Chellappan4,Yee Fun Lim4,Felipe Oviedo3,Benjamin MacLeod5,Fraser Parlane5,Curtis Berlinguette5,Tonio Buonassisi3

Singapore-MIT Alliance for Research and Technology1,National University of Singapore2,Massachusetts Institute of Technology3,Agency for Science, Technology and Research4,The University of British Columbia5

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2:30 PM - MT03.13.04
Act Locally—Tuning PV Materials to Local Climate

Erin Looney1,Tonio Buonassisi1,Ian Marius Peters1

Massachusetts Institute of Technology1

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2:45 PM - MT03.13.05
Beyond-Expert-Level Prediction of Battery Performance by Feature-Engineering-Free Machine Learning

Xi Chen1,Xin Li1

Harvard University1

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3:00 PM -
BREAK


3:30 PM - MT03.13.06
Enabling Data Science Methods for Catalyst Design and Discovery

Zachary Ulissi1

Carnegie Mellon University1

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4:00 PM - MT03.13.07
Estimating Carrier Injection Barriers at Metal-Polymer Interfaces Using Multi-Fidelity Information-Fusion Method

Deepak Kamal1,Lihua Chen1,Rohit Batra1,Yifei Wang2,Zongze Li2,Yang Cao2,Rampi Ramprasad1

Georgia Institute of Technology1,University of Connecticut2

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4:15 PM - MT03.13.08
Data Mining of Layered Crystalline Perovskites—Structure, Energetic and Electronic Properties and a Comparison with the ABC3 Counterparts

Yaoding Lou1,Junkai Deng2,Zhe (Jefferson) Liu1

The University of Melbourne1,Xi’an Jiaotong University2

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4:30 PM - MT03.13.09
Automated Coarse Graining Procedure for Molecular Dynamics, Preserving Rare Events

Blake Duschatko1,Jonathan Vandermause1,Nicola Molinari1,Boris Kozinsky1

Harvard University1

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4:45 PM - MT03.13.10
Molecular Design Strategy of λ5σ6-Phosphorous Compounds for OLED Applications

Jonas Köhling1,Gerd-Volker Röschenthaler1,Veit Wagner1

Jacobs University Bremen1

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Symposium Support