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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 EQ04—Machine Learning on Experimental Data for Emergent Quantum Materials

2021-11-29   Show All Abstracts

Symposium Organizers

Mingda Li, Massachusetts Institute of Technology
Maciej Haranczyk, IMDEA Materials Institute
Christopher Rycroft, Harvard University
Tess Smidt, Massachusetts Institute of Technology
Tutorial EQ04: Symmetry-Aware Neural Networks for the Material Sciences
Session Chairs
Monday AM, November 29, 2021
Hynes, Level 2, Room 205

8:30 AM -
Euclidean Symmetry in Machine Learning for Materials Science

Tess Smidt1

Lawrence Berkeley National Laboratory1

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9:30 AM -
Group Theory, Irreducible Representations, and Tensor Products and How to Use them in e3nn to Build Euclidean Neural Networks

Mario Geiger1

EPFL1

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10:30 AM - EQ04.00
BREAK


11:00 AM -
Analyzing geometry and structure of atomic configurations with equivariant and invariant functions

Thomas Hardin1

Sandia National Laboratories1

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12:00 PM - EQ04.00
BREAK


1:30 PM -
Molecular dynamics with NequIP

Simon Batzner1

Harvard University1

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2:30 PM - EQ04.00
BREAK


3:00 PM -
Predicting Electron Densities with e3nn

Josh Rackers1

Sandia National Laboratories1

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4:00 PM -
Predicting Phonon Properties of Crystal Structures

Zhantao Chen1

Massachusetts Institute of Technology1

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2021-11-30   Show All Abstracts

Symposium Organizers

Mingda Li, Massachusetts Institute of Technology
Maciej Haranczyk, IMDEA Materials Institute
Christopher Rycroft, Harvard University
Tess Smidt, Massachusetts Institute of Technology
EQ04.01: Machine Learning for Spectroscopy
Session Chairs
Mingda Li
Tuesday AM, November 30, 2021
Hynes, Level 2, Room 205

10:30 AM - *EQ04.01.02
Time-Resolved RIXS Technique and Applications in Nonequilibrium Quantum Materials

Yao Wang1

Clemson University1

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11:00 AM - *EQ04.01.03
Using Complete, Symmetry Invariant Representations of Atomic Environments to Predict New Ionic Liquids from Experimental Data

Martin Uhrin1

EPFL1

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11:30 AM - *EQ04.01.04
Unravel the Frequency-dependent Phonon Transport with Scientific Machine Learning

Zhantao Chen1

Massachusetts Institute of Technology1

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EQ04.02: Unsupervised Learning and Data Mining for Materials Discovery
Session Chairs
Tess Smidt
Tuesday PM, November 30, 2021
Hynes, Level 2, Room 205

1:30 PM - *EQ04.02.01
Unsupervised Machine Learning and Band Topology

Robert-Jan Slager1

University of Cambridge1

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2:00 PM - *EQ04.02.02
Machine Learning Discovery of New Superhard Ternary and High-Entropy Borides

Cheng-Chien Chen1

University of Alabama at Birmingham1

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2:30 PM - EQ04.02.03
Machine Learning the Relationship Between Debye and Superconducting Transition Temperatures

Adam Smith1,Sumner Harris1,2,Renato Camata1,Cheng-Chien Chen1

University of Alabama at Birmingham1,Oak Ridge National Laboratory2

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2021-12-08   Show All Abstracts

Symposium Organizers

Mingda Li, Massachusetts Institute of Technology
Maciej Haranczyk, IMDEA Materials Institute
Christopher Rycroft, Harvard University
Tess Smidt, Massachusetts Institute of Technology
EQ04.03: Emerging Tools of Machine Learning for Materials Science I
Session Chairs
Maciej Haranczyk
David Tennant
Wednesday AM, December 8, 2021
EQ04-Virtual

8:00 AM - *EQ04.03.01
Data Integration for Accelerated Materials Design via Preference Learning

Koji Tsuda1

The University of Tokyo1

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8:30 AM - EQ04.03.02
Automated Processing and Characterisation of EELS Spectral Images with Machine Learning

Abel Brokkelkamp1,Isabel Postmes1,Jaco ter Hoeve2,3,Sabrya van Heijst1,Louis Maduro1,Juan Rojo2,3,Sonia Conesa-Boj1

TU Delft1,Vrije Universiteit Amsterdam2,Nikhef3

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8:45 AM - *EQ04.03.03
From Density Functional Theory to Machine Learning for Accurate Prediction of Materials Properties

Silvana Botti1

Friedrich Schiller University Jena1

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9:15 AM - EQ04.03.04
Unsupervised Machine Learning for Spatio-Temporal Characterization of Ultrafast Electron Microscopy Datasets

Arun Baskaran1,Faran Zhou1,Thomas Gage1,Haihua Liu1,Ilke Arslan1,Haidan Wen1,Maria Chan1

Argonne National Laboratory1

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9:30 AM - *EQ04.03.05
Progress Towards Leveraging Natural Language Processing for Collecting Experimental Data and Data Mining

Anubhav Jain1

Lawrence Berkeley National Laboratory1

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EQ04.04: Emerging Tools of Machine Learning for Materials Science II
Session Chairs
Christopher Rycroft
Wednesday AM, December 8, 2021
EQ04-Virtual

10:30 AM - *EQ04.04.01
Application of Machine Learning to Neutron Scattering from Magnets

David Tennant1,Anjana Samarakoon2

Oak Ridge National Laboratory1,Argonne National Laboratory2

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11:00 AM - EQ04.04.02
Prediction of Localized Plasmon Resonances in Complex Nanoparticle Assemblies Using Autoencoder Networks

Kevin Roccapriore1,Maxim A. Ziatdinov1,Shin-Hum Cho2,Delia Milliron3,Jordan Hachtel1,Sergei Kalinin1

Oak Ridge National Laboratory1,Samsung Semiconductor R&D2,The University of Texas at Austin3

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11:15 AM - EQ04.04.03
Mapping Polarization from STEM and STM Images

Ayana Ghosh1,Christopher Nelson1,Mark Oxley1,Xiaohang Zhang2,Maxim A. Ziatdinov1,Ichiro Takeuchi2,Sergei Kalinin1

Oak Ridge National Laboratory1,University of Maryland2

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11:30 AM - *EQ04.04.04
Detection of Topological Materials with Machine Learning

Nikolas Claussen1,Bogdan Bernevig2,Nicolas Regnault2,3

University of California, Santa Barbara1,Princeton University2,Ecole Normal Superieure3

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12:00 PM - *EQ04.04.05
Forward and Inverse Design of Spectral Emissivity Using Machine Learning Models

Sean Lubner1,Mahmoud Elzouka1,Charles Yang1,Minok Park1,Alok Singh1,Adrian Albert1,Vassilia Zorba1,Ravi Prasher1

Lawrence Berkeley National Lab1

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EQ04.05: Emerging Tools of Machine Learning for Materials Science III
Session Chairs
Wednesday PM, December 8, 2021
EQ04-Virtual

1:00 PM - *EQ04.01.01
Real-Time Physics-Constrained Machine Learning in Multimodal Spectroscopy

Joshua Agar1

Lehigh University1

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MRS publishes with Springer Nature

 

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