AI Materials Design and Discovery I
FOCUS · A60 · ID: 381698
Presentations
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Network Theory Meets Materials Science
Invited
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Presenters
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Christopher Wolverton
Northwestern University, Materials Science and Engineering, Northwestern University
Authors
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Christopher Wolverton
Northwestern University, Materials Science and Engineering, Northwestern University
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Neural network – assisted search for active site ensembles in dilute bimetallic nanoparticle catalysts
ORAL
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Presenters
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Nicholas Marcella
Materials Science and Chemical Engineering, Stony Brook University, material science and chemical engineering, Stony Brook University, Stony Brook University
Authors
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Nicholas Marcella
Materials Science and Chemical Engineering, Stony Brook University, material science and chemical engineering, Stony Brook University, Stony Brook University
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Steven Torrisi
Department of Physics, Harvard University, Physics, Harvard University, John A. Paulson School of Engineering and Applied Sciences, Harvard University, Harvard University
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Jin Soo Lim
Chemistry and Chemical Biology, Harvard University, Chemistry & Chemical Biology, Harvard University, John A. Paulson School of Engineering and Applied Sciences, Harvard University, Harvard University
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Boris Kozinsky
Harvard University, John A. Paulson School of Engineering and Applied Sciences, Harvard University, School of Engineering & Applied Sciences, Harvard University
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Anatoly Frenkel
Materials Science and Chemical Engineering, Stony Brook University, Stony Brook University
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Accelerating Finite-Temperature Kohn-Sham Density Functional Theory with Deep Neural Networks
ORAL
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Presenters
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Attila Cangi
CASUS, Helmholtz Zentrum Dresden-Rossendorf, Center for Advanced Systems Understanding (CASUS), Helmholtz Zentrum Dresden-Rossendorf, Center for Advanced Systems Understanding (CASUS), Helmholtz Zentrum Dresden-Rossendorf
Authors
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Attila Cangi
CASUS, Helmholtz Zentrum Dresden-Rossendorf, Center for Advanced Systems Understanding (CASUS), Helmholtz Zentrum Dresden-Rossendorf, Center for Advanced Systems Understanding (CASUS), Helmholtz Zentrum Dresden-Rossendorf
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J. A. Ellis
Sandia National Laboratories
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Normand Arthur Modine
Sandia National Laboratories
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J. Adam Stephens
Sandia National Laboratories
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Aidan Thompson
Sandia National Laboratories
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Sivasankaran Rajamanickam
Sandia National Laboratories
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Graph Neural Network for Metal Organic Framework Potential Energy Approximation: Energy Landscape Database and Rigidity
ORAL
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Presenters
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Christopher Owen
Binghamton University
Authors
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Christopher Owen
Binghamton University
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Shehtab Zaman
Binghamton University
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Symmetry incorporated graph convolutional neural networks for solid-state materials
ORAL
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Presenters
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Weiyi Gong
Physics, Temple University
Authors
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Weiyi Gong
Physics, Temple University
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Hexin Bai
Computer Science, Temple University
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Peng Chu
Computer Science, Temple University
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Haibin Ling
Computer Science, Stony Brook University
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Qimin Yan
Temple University, Physics, Temple University
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CCDCGAN: Inverse design of crystal structures
ORAL
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Presenters
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Teng Long
Technische Universitat Darmstadt
Authors
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Teng Long
Technische Universitat Darmstadt
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Nuno Fortunato
Institute of Materials Science, Technische Universitat Darmstadt, Technische Universitat Darmstadt
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Yixuan Zhang
Technische Universitat Darmstadt
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Chen Shen
Institute of Materials Science, Technische Universitat Darmstadt, Technische Universitat Darmstadt
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Oliver Gutfleisch
Technische Universitat Darmstadt
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Hongbin Zhang
Institute of Materials Science, Technische Universitat Darmstadt, Department of Materials and Earth Sciences, Theory of Magnetic Materials, Technical University of Darmstadt, Darmstadt, Germany, Technische Universitat Darmstadt
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Network-based representation and analysis of materials space
ORAL
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Presenters
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Alexander Veremyev
1Department of Industrial Engineering and Management Systems, University of Central Florida
Authors
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Alexander Veremyev
1Department of Industrial Engineering and Management Systems, University of Central Florida
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Laalitha Liyanage
University of North Texas
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Marco Fornari
Physics, Department of Physics and Science of Advanced Materials Program, Central Michigan University, Mt. Pleasant, MI, USA, Physics, Central Michigan Univ, Physics and Astronomy, Central Michigan University, Physics, Central Michigan University
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Vladimir Boginski
1Department of Industrial Engineering and Management Systems, University of Central Florida
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Stefano Curtarolo
Mechanical Engineering and Materials Science, Duke University
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Sergiy Butenko
Department of Industrial and Systems Engineering, Texas A&M University
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Marco Buongiorno Nardelli
Physics, University of North Texas, Denton, TX, USA, University of North Texas
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Uncovering the Relationship Between Thermal Conductivity and Anharmonicity with Symbolic Regression
ORAL
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Presenters
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Thomas Alexander Reichmanis Purcell
NOMAD Laboratory, Fritz Haber Institute of the Max Planck Society, Fritz Haber Institute, Fritz-Haber Institute
Authors
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Thomas Alexander Reichmanis Purcell
NOMAD Laboratory, Fritz Haber Institute of the Max Planck Society, Fritz Haber Institute, Fritz-Haber Institute
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Matthias Scheffler
NOMAD Laboratory, Fritz Haber Institute of the Max Planck Society, Berlin, NOMAD Laboratory, Fritz Haber Institute of the Max Planck Society, Fritz-Haber-Institut der MPG, 14195 Berlin, DE, Fritz-Haber-Institut der Max-Planck-Gesellschaft, Fritz Haber Institute, Fritz Haber Institute Berlin, Fritz Haber Institute of the Max Planck Society, Berlin, Germany, Fritz-Haber Institute
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Luca M. Ghiringhelli
NOMAD Laboratory, Fritz Haber Institute of the Max Planck Society, Berlin, NOMAD Laboratory, Fritz Haber Institute of the Max Planck Society, NOMAD Laboratory, Fritz-Haber Institute of Max-Planck Society, Fritz-Haber-Institut der Max-Planck-Gesellschaft, Fritz Haber Institute, Fritz-Haber Institute
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Christian Carbogno
NOMAD Laboratory, Fritz Haber Institute of the Max Planck Society, Fritz-Haber Institute
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Enhanced Machine Learning Models for Structure-Property Mapping with Principal Covariates Regression
ORAL
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Presenters
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Rose K. Cersonsky
Ecole Polytechnique Federale de Lausanne
Authors
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Rose K. Cersonsky
Ecole Polytechnique Federale de Lausanne
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Benjamin A. Helfrecht
Ecole Polytechnique Federale de Lausanne
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Guillaume Fraux
Ecole Polytechnique Federale de Lausanne
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Edgar Engel
Trinity College, University of Cambridge
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Michele Ceriotti
Ecole polytechnique federale de Lausanne, Ecole Polytechnique Federale de Lausanne, Institute of Materials, Swiss Federal Institute of Technology in Lausanne (EPFL), Switzerland, École Polytechnique Federale de Lausanne, Laboratory of Computational Science and Modeling, Institut des Matériaux, École Polytechnique Fédérale de Lausanne
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Graph Neural Network for Metal-Organic Framework Potential Energy Approximation
ORAL
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Presenters
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Shehtab Zaman
Binghamton University
Authors
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Shehtab Zaman
Binghamton University
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Christopher Owen
Binghamton University
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Kenneth Chiu
Binghamton University
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Michael Lawler
Physics, Cornell University, Department of Physics, Applied Physics, and Astronomy, Binghamton University, Cornell University, Binghamton University
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Towards Inverse Design of Metal-Organic Frameworks to Maximize Hydrogen Storage using Deep Learning
ORAL
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Presenters
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Kevin Phillips
Binghamton University
Authors
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Kevin Phillips
Binghamton University
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Shehtab Zaman
Binghamton University
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Kenneth Chiu
Binghamton University
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Michael Lawler
Physics, Cornell University, Department of Physics, Applied Physics, and Astronomy, Binghamton University, Cornell University, Binghamton University
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Predicting geometric properties of metal-organic frameworks by fusing 3D and graph convolutional neural networks
ORAL
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Presenters
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Jacob Barkovitch
Binghamton University
Authors
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Jacob Barkovitch
Binghamton University
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Musen Zhou
University of California, Riverside
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Shehtab Zaman
Binghamton University
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Kenneth Chiu
Binghamton University
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Michael Lawler
Physics, Cornell University, Department of Physics, Applied Physics, and Astronomy, Binghamton University, Cornell University, Binghamton University
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Jianzhong Wu
University of California, Riverside, Chemical Engineering, University of California
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Generating Multiscale Amorphous Molecular Structures Using Deep Learning: A Study in 2D
ORAL
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Presenters
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Lena Simine
McGill Univ
Authors
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Lena Simine
McGill Univ
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Michael Kilgour
McGill Univ
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Nicolas Gastellu
McGill Univ
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David Yu-Tung Hui
Montreal Institute for Learning Algorithms
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Yoshua Bengio
Montreal Institute for Learning Algorithms
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