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Symposium DS04—Recent Advances in Data-Driven Discovery of Materials for Energy Conversion and Storage

2022-05-08   Show All Abstracts

Times shown in HST (GMT-10:00)

Symposium Organizers

Jeffrey Lopez, Northwestern University
Chibueze Amanchukwu, University of Chicago
Rajeev Surendran Assary, Argonne National Laboratory
Tian Xie, Massachusetts Institute of Technology

Symposium Support

Bronze
Pacific Northwest National Laboratory
DS04.01: Accelerating Materials Discovery I
Session Chairs
Jeffrey Lopez
Sunday PM, May 8, 2022
Hawai'i Convention Center, Level 3, 313B

1:30 PM - DS04.01.07
Atomistic Modeling and AI-enabled Energy Storage Materials Discovery

Rajeev Surendran Assary1

Argonne National Laboratory1

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1:45 PM - DS04.01.01
Simmate—A Framework and Toolbox for Materials Discovery and Its Application in the High-Throughput Search of Fluoride-Ion Conductors

Jack Sundberg1,Lauren McRae1,Siona Benjamin1,Scott Warren1

University of North Carolina1

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2:00 PM - DS04.01.02
Autonomous Reinforcement Learning Approach for Development of Reactive Potentials for Energy Applications

Aditya Koneru1,2,Sukriti Manna1,2,Henry Chan1,2,Troy Loeffler1,2,Subramanian Sankaranarayanan1,2

University of Illinois at Chicago1,Argonne National Laboratory2

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2:15 PM - DS04.01.03
A Flexible and Scaleable Scheme for Combining Formation Energies Computed with Different Density Functionals

Ryan Kingsbury1,Andrew Rosen1,Ayush Gupta2,1,Jason Munro1,Shyue Ping Ong3,1,Anubhav Jain1,Shyam Dwaraknath1,Matthew Horton1,Kristin Persson1,2

Lawrence Berkeley National Laboratory1,University of California, Berkeley2,University of California, San Diego3

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2:30 PM - DS04.01.04
Equivariant Graph Network for Fast Charge Density Estimation of Molecules, Liquids and Solids

Peter Jørgernsen1,Arghya Bhowmik1

Technical University of Denmark1

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2:45 PM - DS04.01.05
High-Throughput Characterization of Mixed-Metal Salt Hydrates for Heat Storage via Density Functional Theory and Machine Learning

Steven Kiyabu1,Donald Siegel2

University of Michigan1,The University of Texas at Austin2

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3:00 PM - DS04.01.06
Machine-Learning Based Optimization of Sorbent Materials for Energy Storage—A Case Study on Metal Organic Frameworks–MOFs

Giovanni Trezza1,Luca Bergamasco1,Matteo Fasano1,Eliodoro Chiavazzo1

Politecnico di Torino1

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2022-05-09   Show All Abstracts

Times shown in HST (GMT-10:00)

Symposium Organizers

Jeffrey Lopez, Northwestern University
Chibueze Amanchukwu, University of Chicago
Rajeev Surendran Assary, Argonne National Laboratory
Tian Xie, Massachusetts Institute of Technology

Symposium Support

Bronze
Pacific Northwest National Laboratory
DS04.02: Data-Driven Advances in Energy Storage I
Session Chairs
Jeffrey Lopez
Nicola Molinari
Monday AM, May 9, 2022
Hawai'i Convention Center, Level 3, 313B

10:30 AM - *DS04.02.01
Leaning Governing Relations in Battery Electrodes—Hybridizing Physics- and Data-Driven Approaches

Vivek Lam1,William C. Chueh1

Stanford University1

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11:00 AM - DS04.02.03
Spectral Denoising for Accelerated Analysis of Correlated Ionic Transport

Nicola Molinari1,2,Yu Xie1,Ian Leifer1,Aris Marcolongo3,Mordechai Kornbluth2,Boris Kozinsky1,2

Harvard University1,Robert Bosch LLC2,University of Bern3

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11:15 AM - DS04.02.04
Materials Design Principles of Amorphous Cathode Coatings for Lithium-Ion Battery Applications

Jianli Cheng1,Kristin Persson1

Lawrence Berkeley National Laboratory1

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11:30 AM - DS04.02.02
Comprehensive Analytics for Massive and Diverse Li-Ion Battery Aging Datasets

Vivek Lam1,Bruis Vlijmen1,Xiao Cui1,Patrick Asinger2,Devi Ganapathi1,Dean Deng1,Natalie Geise1,Will Gent1,Patrick Herring3,Richard Braatz2,William C. Chueh1

Stanford University1,Massachusetts Institute of Technology2,Toyota Research Institute3

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DS04.03: Data-Driven Advances in Energy Storage II
Session Chairs
Shadow Huang
Rajeev Surendran Assary
Monday PM, May 9, 2022
Hawai'i Convention Center, Level 3, 313B

1:30 PM - *DS04.03.01
A Data-Driven Approach to Understanding and Predicting the Early Formation of the Solid-Liquid Electrolyte Interphase

Kristin Persson1,2

University of California, Berkeley1,Lawrence Berkeley National Laboratory2

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2:00 PM - DS04.03.02
High Dimensional and Low Sample Size Case Statistics for the Screening on Crystal Information of the Solid-State Electrolytes

Hirotaka Sakamoto1,Kazuyoshi Yata2,Hisatsugu Yamasaki1,Makoto Aoshima2

Toyota Motor Corporation1,University of Tsukuba2

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2:15 PM - DS04.03.03
Element Selection for Crystalline Inorganic Solid Discovery Guided by Unsupervised Machine Learning of Experimentally Explored Chemistry

Andrij Vasylenko1,Jacinthe Gamon1,Benjamin Duff1,Vladimir Gusev1,Luke Daniels1,Marko Zanella1,Felix Shin1,Paul Sharp1,Alexandra Morscher1,Ruiyong Chen1,Alex Neal1,Laurence Hardwick1,John Claridge1,Frederic Blanc1,Michael Gaultois1,Matthew Dyer1,Matthew Rosseinsky1

University of Liverpool1

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2:30 PM - DS04.03.04
WITHDRAWN 5/5/22 DS04.,03.04 Autonomous Development of a Reference Database and a Machine-Learned Interatomic Potential for Lithium-Intercalated Carbon

Sam Norwood1,Gábor Csányi2,Tejs Vegge1,Arghya Bhowmik1

Technical University of Denmark1,The University of Cambridge2

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2:45 PM - DS04.03
BREAK


3:15 PM - *DS04.03.05
The ElectroLab—An Integrated Platform for High-throughput Characterization of Redox-Active Materials

Oliver Rodriguez1,Charles Schroeder1,Michael Pence1,Hung Nguyen1,Edward Jira1,Inkyu Oh1,Joaquin Rodriguez-Lopez1

University of Illinois at Urbana-Champaign1

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3:45 PM - DS04.03.06
Data-Driven Approach to Design/Discover Intercalating Ions and Layered Materials for Metal-Ion Batteries

Shayani Parida1,Avanish Mishra1,Arthur Dobley2,Barry Carter1,3,Avinash Dongare1

University of Connecticut1,EaglePicher Technologies2,Sandia National Laboratories3

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4:00 PM - DS04.03.08
Computational Screening of Positive Electrode Materials for Ca-Ion Batteries

Sai Gautam Gopalakrishnan1,Ankit Kumar1,Dereje Tekliye1,Xie Weihang2,Pieremanuele Canepa2

Indian Institute of Science1,National University of Singapore2

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4:15 PM - DS04.03.09
In Silico Paradigm for Predicting Green Battery Material Phenomena

Shadow Huang1,Hongjiang Chen1

North Carolina State Univ1

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2022-05-10   Show All Abstracts

Times shown in HST (GMT-10:00)

Symposium Organizers

Jeffrey Lopez, Northwestern University
Chibueze Amanchukwu, University of Chicago
Rajeev Surendran Assary, Argonne National Laboratory
Tian Xie, Massachusetts Institute of Technology

Symposium Support

Bronze
Pacific Northwest National Laboratory
DS04.04: Accelerating Materials Discovery II
Session Chairs
Qizhi He
Tian Xie
Tuesday AM, May 10, 2022
Hawai'i Convention Center, Level 3, 313B

9:15 AM - DS04.04.01
Predicting and Understanding Perovskite Nanostructure Formation Through Machine Learning and Data-Driven Modelling of In Situ Spectroscopic Data

Jakob Dahl1,2,Emory Chan2,A. Paul Alivisatos1

University of California, Berkeley1,Lawrence Berkeley National Laboratory2

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9:30 AM - DS04.04.02
Physics-Constrained Deep Neural Network Method for Estimation and Simulation of Vanadium Redox Flow Battery

Qizhi He1,Panos Stinis2,Alexandre Tartakovsky3

University of Minnesota Twin Cities1,Pacific Northwest National Laboratory2,University of Illinois at Urbana-Champaign3

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9:45 AM - DS04.04.03
Remote and On-the-Fly—Artificial Intelligence Driven Science in Laboratories and Central Facilities

Phillip Maffettone1

Brookhaven National Laboratory1

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10:00 AM - DS04.04
BREAK


10:30 AM - *DS04.04.04
Controlling Polymorphism in Nanoporous Aluminosilicates from First Principles

Rafael Gomez-Bombarelli1

Massachusetts Institute of Technology1

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11:00 AM - DS04.04.05
Inorganic Synthesis Recommendation by Machine Learning the Similarity of Materials from Scientific Literature

Tanjin He1,2,Haoyan Huo1,2,Christopher Bartel1,2,Zheren Wang1,2,Kevin Cruse1,2,Gerbrand Ceder1,2

University of California, Berkeley1,Lawrence Berkeley National Laboratory2

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11:15 AM - DS04.04.06
Towards Materials "Synthesis by Design"—Assessing Selectivity of Solid-State Reactions Using Chemical Potential Differences at Interfaces

Matthew McDermott1,2,Brennan McBride3,James Neilson3,Kristin Persson1,2

Lawrence Berkeley National Laboratory1,University of California, Berkeley2,Colorado State University3

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11:30 AM - DS04.04.07
Research Data Infrastructure for Data-Driven Experimental Materials Science

Andriy Zakutayev1,Kevin Talley1,Robert White1,David Evenson1,William Tumas1,Kristin Munch1,Caleb Phillips1

National Renewable Energy Laboratory1

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11:45 AM - DS04.04.08
Graph Convolutional Neural Network Modeling of Vacancy Formation for Materials Discovery in Solar Thermochemical Water Splitting

Matthew Witman1,Anuj Goyal2,Tadashi Ogitsu3,Stephan Lany2,Anthony McDaniel1

Sandia National Laboratories1,National Renewable Energy Laboratory2,Lawrence Livermore National Laboratory3

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DS04.05: Data-Driven Advances in Energy Conversion
Session Chairs
Rachel Woods-Robinson
Tian Xie
Tuesday PM, May 10, 2022
Hawai'i Convention Center, Level 3, 313B

1:30 PM - DS04.05.01
Lessons Learned in Combining Computational and Experimental Materials Discovery—A P-Type Transparent Conductor Case Study

Rachel Woods-Robinson1,Andriy Zakutayev2,Kristin Persson1,3

Lawrence Berkeley National Laboratory1,National Renewable Energy Laboratory2,University of California, Berkeley3

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1:45 PM - DS04.05.02
A Machine Vision Tool for Facilitating the Optimization of Large-Area Perovskite Photovoltaics

Mathilde Fievez1,2,Nina Taherimakhsousi3,Benjamin MacLeod3,Edward Booker3,Emmanuelle Fayard1,Muriel Matheron1,Matthieu Manceau1,Stéphane Cros1,Solenn Berson1,Curtis Berlinguette3

CEA1,Stanford University2,The University of British Columbia3

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2:00 PM - DS04.05.03
WITHDRAWN 5/8/22 DS04.05.03 Identifying Materials Selection Criteria for 2D Capping Layer in Perovskite Solar Cells via Machine Learning

Zhe Liu1,Suo Wang1,Chongyang Zhi1,Zhen Li1

Northwestern Polytechnical University1

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2:15 PM - DS04.05.04
Using High-Throughput Calculations and Machine Learning to Understand Electronic Transport in Semiconductors

Alex Ganose1,Junsoo Park2,Anubhav Jain2

Imperial College London1,Lawrence Berkeley National Laboratory2

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2:30 PM - DS04.05
BREAK


3:00 PM - DS04.05.05
High-Throughput Discovery of Multiferroic Materials Based on Ab Initio Calculations

Francesco Ricci1,2,Ella Banyas1,Stephanie Mack1,2,Jeffrey Neaton1,2,3

Lawrence Berkeley National Laboratory1,University of California, Berkeley2,Kavli Energy NanoScience Institute3

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3:15 PM - DS04.05.06
Anisotropic Conductance Descriptor for Ab Initio Screening of Next-Generation Interconnect Metals

Sushant Kumar1,Christian Multunas1,Daniel Gall1,Ravishankar Sundararaman1

Rensselaer Polytechnic Institute1

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DS04.06: Poster Session: Recent Advances in Data-Driven Discovery of Materials for Energy Conversion and Storage
Session Chairs
Jeffrey Lopez
Tian Xie
Tuesday PM, May 10, 2022
Hawai'i Convention Center, Level 1, Kamehameha Exhibit Hall 2 & 3

5:00 PM - DS04.06.01
Using Neural Network Potential and Metadynamics to Investigate Oxygen Reduction at Gold-Water Interface

Xin Yang1,Arghya Bhowmik1,Tejs Vegge1,Heine Hansen1

Danmarks Tekniske Universitet1

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5:00 PM - DS04.06.03
Iterative Peak-Fitting of Frequency-Domain Data via Deep Convolution Neural Networks

Hyeongseon Park1,Seong-Heum Park1,Hyunbok Lee2,1,Heung-Sik Kim2,1

Institute for Accelerator Science, Kangwon National University1,Kangwon National University2

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2022-05-11   Show All Abstracts

Times shown in HST (GMT-10:00)

Symposium Organizers

Jeffrey Lopez, Northwestern University
Chibueze Amanchukwu, University of Chicago
Rajeev Surendran Assary, Argonne National Laboratory
Tian Xie, Massachusetts Institute of Technology

Symposium Support

Bronze
Pacific Northwest National Laboratory
DS04.07: Data-Driven Advances in Electrocatalysis
Session Chairs
Jeffrey Lopez
Rajeev Surendran Assary
Tian Xie
Wednesday AM, May 11, 2022
Hawai'i Convention Center, Level 3, 313B

8:00 AM - *DS04.07.01
Machine-Learning Assisted discovery of Catalytic Materials

Richard Tran1,Zachary Ulissi1,Duo Wang2,Jain Anubhav2,Ryan Kingsbury2

Carnegie Mellon University1,Lawrence Berkeley National Laboratory2

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8:30 AM - DS04.07.02
High Throughput Screening of Metal-Oxide Systems for Facile OER Kinetics in Electrochemical Mining

Jaclyn Lunger1,Naomi Luntz1,Yang Shao-Horn1

Massachusetts Institute of Technology1

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8:45 AM - DS04.07.03
High-Throughput Electrocatalyst Screening and Machine Learning for Feature Selection and Prediction of Alkaline Fuel Cell Catalysts

Jeremy Hitt1,Thomas Mallouk1

University of Pennsylvania1

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9:00 AM - DS04.07.04
Predicting Electronic and Photophysical Properties of Photocatalytically Active Metal-Organic Frameworks

Andres Ortega Guerrero1,Kevin Jablonka1,Berend Smit1

EPFL1

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9:15 AM - DS04.07.05
High-Throughput study of Tellurium-Containing Semiconductors for Photocatalysis

Martin Siron1,2,Oxana Andriuc1,2,Kristin Persson1,2

University of California, Berkeley1,Lawrence Berkeley National Laboratory2

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9:30 AM - DS04.07
BREAK


10:00 AM - DS04.07.07
Accelerated Materials Discovery Using Quantum-Inspired Optimizers

Hitarth Choubisa1,Jehad Abed1,Douglas Mendoza1,2,Alan Aspuru-Guzik1,3,Edward Sargent1

University of Toronto1,Harvard University2,Vector Institute for Artificial Intelligence3

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10:15 AM - DS04.07.08
An Automated Adsorption Workflow for Semiconductors

Oxana Andriuc1,2,Martin Siron2,1,3,Kristin Persson2,1

University of California, Berkeley1,Lawrence Berkeley National Lab2,Toyota Research Institute3

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10:30 AM - DS04.07.09
Analysis of Multi-Component Perovskites as Oxygen Evolution Reaction Catalysts through High-Throughput Simulations and Machine Learning

James Damewood1,Jessica Karaguesian1,Daniel Schwalbe-Koda1,Jaclyn Lunger1,Jiayu Peng1,Daniel Zheng1,Elton Pan1,Vineeth Venugopal1,Elsa Olivetti1,Yang Shao-Horn1,Rafael Gomez-Bombarelli1

Massachusetts Institute of Technology1

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10:45 AM - DS04.07.10
Ligation in Data-Driven Synthesis Studies of Nanoparticles—A Case Study of Phosphine-Stabilized Gold

Caitlin McCandler1,2,Kristin Persson1,2

Lawrence Berkeley National Laboratory1,University of California, Berkeley2

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11:00 AM - DS04.07.11
Multivariate Analysis of Peptide-Driven Nucleation and Growth of Au Nanoparticles

Kacper Lachowski1,Kiran Vaddi1,Lilo Pozzo1

University of Washington1

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2022-05-23   Show All Abstracts

Times shown in EDT (GMT-4:00)

Symposium Organizers

Jeffrey Lopez, Northwestern University
Chibueze Amanchukwu, University of Chicago
Rajeev Surendran Assary, Argonne National Laboratory
Tian Xie, Massachusetts Institute of Technology

Symposium Support

Bronze
Pacific Northwest National Laboratory
DS04.08: Recent Advances in Data-Driven Discovery of Materials for Energy Conversion and Storage I
Session Chairs
Chibueze Amanchukwu
Jeffrey Lopez
Monday AM, May 23, 2022
DS04-Virtual

8:00 AM - DS04.08.01
Predicting Quasiparticle and Excitonic Properties of Materials Using Machine Learning

Tathagata Biswas1,Sydney Olson1,Arunima Singh1

Arizona State University1

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8:15 AM - DS04.08.02
High-Throughput Screening of Li-Ion Solid Electrolytes with Experimental Evaluation

Joohwi Lee1,Nobuaki Suzuki1,Yumi Masuoka1,Shingo Ohta1,Tetsuro Kobayashi1,Ryoji Asahi1,2

Toyota Central R&D Labs., Inc.1,Present affiliation : Nagoya Univ.2

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8:30 AM - DS04.08.03
Identification of Electromagnetic Steel Sheets for Motors by Material Structure Characteristics

Hiroyuki Suzuki1,Qiang Dong2,Sayaka Tanimoto1

Hitachi, Ltd.1,Hitachi (China), Ltd.2

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8:45 AM - DS04.08.04
Toward Combinatorial Characterization of LLZO-Based Solid Electrolyte Thin Films

Euimin Cheong1,Dongwoo Lee1

SungKyunKwan University1

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9:00 AM - DS04.08.05
Data-Driven Improvement of ZT in SnSe-Based Thermoelectric Systems

Jino Im1,Yea-Lee Lee1,Hyungseok Lee2,Sejin Byun2,Seunghun Jang1,Hyunju Chang1,In Chung2

Korea Research Institute of Chemical Technology1,Seoul National University2

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9:15 AM - DS04.08.06
A Broad Structural Search of Binary Precipitates via Active Learning

Angel Diaz Carral1,Azade Yazdan Yar1,Maria Fyta1,Siegfried Schmauder1

University of Stuttgart1

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9:30 AM - *DS04.08.07
Auto-Generating Material and Device Databases on Batteries and Solar Cells for Data-Driven Materials Discovery

Jacqueline Cole1,2

University of Cambridge1,ISIS Pulsed Neutron and Muon Source2

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DS04.09: Recent Advances in Data-Driven Discovery of Materials for Energy Conversion and Storage II
Session Chairs
Chibueze Amanchukwu
Jeffrey Lopez
Monday AM, May 23, 2022
DS04-Virtual

10:30 AM - *DS04.09.01
On the Interplay of High Throughput Experiments and Data Science for Accelerated Materials Discovery

John Gregoire1,Joel Haber1,Dan Guevarra1,Lan Zhou1,Di Chen2,Shufeng Kong2,Lusann Yang3,Francesco Ricci4,Jeffrey Neaton4,Carla Gomes2

California Institute of Technology1,Cornell University2,Google Research3,Lawrence Berkeley National Laboratory4

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11:00 AM - *DS04.09.02
Accelerated Materials Discovery for Sustainable Energy Storage

Dmitry Zubarev1,Maxwell Giammona1,Young-Hye Na1

IBM Almaden Research Center1

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11:30 AM - DS04.09.03
Molecular Structure–Redox Potential Relationship for Organic Electrode Materials—Density Functional Theory–Machine Learning Approach

Omar Allam1,Robert Kuramshin1,Zlatomir Stoichev1,Byung Woo Cho1,Seung Woo Lee1,Seung Soon Jang1

Georgia Institute of Technology1

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11:45 AM - DS04.09.04
Physics-Informed XGBoost Model for Electrocaloric Temperature Change Predictions in Ceramics

Jie Gong1,Sharon Chu1,Rohan Mehta1,Alan McGaughey1

Carnegie Mellon University1

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12:00 PM - DS04.09.05
Design and Discovery of Novel OLED Materials via Active Learning

Hadi Abroshan1,Anand Chandrasekaran2,Paul Winget2,Yuling An2,H. Shaun Kwak1,Christopher Brown2,Mathew Halls2

Schrödinger Inc1,Schrödinger, Inc.2

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12:15 PM - DS04.09.06
Alcohol-Based Electrolytes—An Alternative Between Aqueous and Nonaqueous for Increased Voltage and High-Rate Lithium-Ion Batteries

Hewei Xu1

Institute of Condensed Matter and Nanosciences, Molecular Chemistry, Materials and Catalysis, Université catholique de Louvain1

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12:30 PM - *DS04.07.06
Natural Language Processing for Energy Technology Scalability

Elsa Olivetti1

Massachusetts Institute of Technology1

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Available on-demand   Show All Abstracts

Symposium Organizers

Jeffrey Lopez, Northwestern University
Chibueze Amanchukwu, University of Chicago
Rajeev Surendran Assary, Argonne National Laboratory
Tian Xie, Massachusetts Institute of Technology

Symposium Support

Bronze
Pacific Northwest National Laboratory
Tutorial DS04.00: MLOps for Materials Science—What Comes After Building a Machine Learning (ML) Model
Session Chairs
Available on-demand

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