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AI and Materials II

FOCUS · F53 · ID: 1067002

Presentations

  • Machine Learning Driven Automated Scanning Probe Microscopy for Material Discovery: Applications in Ferroelectric and Optoelectronic Materials

    ORAL · Invited

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    Publication: 1. Liu, Y., Kelley, K. P., Vasudevan, R. K., Funakubo, H., Ziatdinov, M. A., & Kalinin, S. V. (2022). Experimental discovery of structure–property relationships in ferroelectric materials via active learning. Nature Machine Intelligence, 4(4), 341-350.<br>2. Liu, Y., Kelley, K. P., Funakubo, H., Kalinin, S. V., & Ziatdinov, M. (2022). Exploring physics of ferroelectric domain walls in real time: deep learning enabled scanning probe microscopy. Advanced Science, 2203957.<br>3. Ziatdinov, M. A., Liu, Y., Morozovska, A. N., Eliseev, E. A., Zhang, X., Takeuchi, I., & Kalinin, S. V. (2022). Hypothesis learning in automated experiment: application to combinatorial materials libraries. Advanced Materials, 2201345.<br>4. Liu, Y., Morozovska, A., Eliseev, E., Kelley, K. P., Vasudevan, R., Ziatdinov, M., & Kalinin, S. V. (2022). Hypothesis-Driven Automated Experiment in Scanning Probe Microscopy: Exploring the Domain Growth Laws in Ferroelectric Materials. arXiv preprint arXiv:2202.01089.<br>5. Liu, Y., Kelley, K. P., Vasudevan, R. K., Zhu, W., Hayden, J., Maria, J. P., ... & Kalinin, S. V. (2022). Automated Experiments of Local Non-linear Behavior in Ferroelectric Materials. arXiv preprint arXiv:2206.15110.

    Presenters

    • Yongtao Liu

      Oak Ridge National Laboratory, Oak Ridge National Lab

    Authors

    • Yongtao Liu

      Oak Ridge National Laboratory, Oak Ridge National Lab

    • Kyle Kelley

      Oak Ridge National Lab, Oak Ridge National Laboratory

    • Rama K Vasudervan

      Oak Ridge National Laboratory, Oak Ridge National Lab

    • Maxim Ziatdinov

      Oak Ridge National Lab

    • Sergei V Kalinin

      University of Tennessee, University of Tennessee, Knoxville

    View abstract →

  • Accelerating the Search for High-Performance, Novel Materials with Active Learning - An Example: Thermal Insulators

    ORAL

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    Presenters

    • Thomas A Purcell

      The NOMAD Laboratory at the FHI-MPG and IRIS-Adlershof of HU, Berlin, Germany, The NOMAD Laboratory at the FHI of the MPG and IRIS-Adlershof of the Humboldt-Universität zu Berlin

    Authors

    • Thomas A Purcell

      The NOMAD Laboratory at the FHI-MPG and IRIS-Adlershof of HU, Berlin, Germany, The NOMAD Laboratory at the FHI of the MPG and IRIS-Adlershof of the Humboldt-Universität zu Berlin

    • Matthias Scheffler

      The NOMAD Laboratory at the FHI-MPG and IRIS-Adlershof of HU, Berlin, Germany, The NOMAD Laboratory at the Fritz Haber Institute of the MPG, The NOMAD Laboratory at the FHI of the Max-Planck-Gesellschaft and IRIS-Adlershof of the Humboldt-Universität zu Berlin, Germany

    • Christian Carbogno

      The NOMAD Laboratory at the FHI-MPG and IRIS-Adlershof of HU, Berlin, Germany, Fritz Haber Institute of the Max Planck Society, The NOMAD Laboratory at the FHI of the Max-Planck-Gesellschaft and IRIS-Adlershof of the Humboldt-Universität zu Berlin, Germany

    • Luca M Ghiringhelli

      1. The NOMAD Laboratory at the FHI-MPG and IRIS-Adlershof of HU, Berlin, Germany 2. Physics Department and IRIS-Adlershof of HU, Berlin, Germany, Physics Department and IRIS-Adlershof of HU, Berlin, Germany and The NOMAD Laboratory at the FHI-MPG and HU, Berlin, Germany, NOMAD Laboratory at the FHI of the Max-Planck-Gesellschaft and IRIS-Adlershof of the Humboldt-Universität (HU) zu Berlin; Physics Department and IRIS-Adlershof of HU zu Berlin

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  • In-silico discovery of HER/OER multi-metallic Alloy electrocatalysts through Density Functional theory calculations and active learning and machine learning

    ORAL

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    Presenters

    • Kwak Seung Jae

      Seoul National University, Seoul Natl Univ

    Authors

    • Kwak Seung Jae

      Seoul National University, Seoul Natl Univ

    • Minhee Park

      Seoul National Univ.

    • Won Bo Lee

      Seoul National University, Seoul National Univ.

    • YongJoo Kim

      Kookmin University, Kookmin Univ.

    View abstract →

  • Efficient Discovery of Air Separation Adsorbents via Multi-Fidelity Bayesian Optimization

    ORAL

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    Presenters

    • Eric Taw

      University of California, Berkeley

    Authors

    • Eric Taw

      University of California, Berkeley

    • Yuto Yabuuchi

      University of California, Berkeley

    • Kurtis M Carsch

      University of California, Berkeley

    • Rachel Rohde

      University of California, Berkeley

    • Jeffrey R Long

      University of California, Berkeley, University of California Berkeley

    • Jeffrey B Neaton

      Lawrence Berkeley National Laboratory, University of California, Berkeley, Department of Physics, University of California, Berkeley; Materials Sciences Division, Lawrence Berkeley National Laboratory; Kavli Energy NanoScience Institute at Berkeley

    View abstract →

  • Unveil the unseen: exploit information hidden in noise

    ORAL

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    Publication: https://link.springer.com/article/10.1007/s10489-022-04102-1<br>Manuscript about concrete design submitted to Data-Centric Engineering journal

    Presenters

    • Bahdan Zviazhynski

      University of Cambridge

    Authors

    • Bahdan Zviazhynski

      University of Cambridge

    • Jessica C Forsdyke

      University of Cambridge

    • Janet M Lees

      University of Cambridge

    • Gareth J Conduit

      University of Cambridge

    View abstract →

  • Prediction of Crystal Symmetry Groups for Binary and Ternary Materials from Chemical Compositions using Machine Learning

    ORAL

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    Presenters

    • Fahhad H Alharbi

      King Fahd Univ KFUPM, King Fahd Univ KFUPM, SDAIA-KFUPM Joint Research Center for Artificial Intelligence

    Authors

    • Mohammed Alghadeer

      University of California, Berkeley

    • Abdulmohsen A Alsaui

      Indian Institute of Technology Madras

    • Yousef A Alghofaili

      Xpedite Information Technology

    • Fahhad H Alharbi

      King Fahd Univ KFUPM, King Fahd Univ KFUPM, SDAIA-KFUPM Joint Research Center for Artificial Intelligence

    View abstract →

  • Machine Learning-Based Microstructure Prediction for Laser-Sintered Alumina

    ORAL

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    Publication: [1] Geng, X., Hong, Y., et al. (2021). Ultra-fast, selective, non-melting, laser sintering of alumina with anisotropic and size-suppressed grains. Journal of the American Ceramic Society, 104(5), 1997-2006.<br>[2] Tang, J., Geng, X., et al. (2021). Machine learning-based microstructure prediction during laser sintering of alumina. Scientific Reports, 11(1), 1-10.<br>[3] Geng, X., Tang, J., et al. (2022). Machine learning-based inverse prediction of alumina's microstructure from hardness. Manuscript in preparation.

    Presenters

    • Xiao Geng

      clemson university

    Authors

    • Xiao Geng

      clemson university

    • jianan tang

      Clemson Universisty, Department of Electrical and Computer Engineering, Clemson University

    • Jianhua Tong

      Department of Materials Science and Engineering, Clemson University

    • Dongsheng Li

      Advanced Manufacturing LLC

    • Hai Xiao

      Department of Electrical and Computer Engineering, Clemson University

    • Fei Peng

      Department of Materials Science and Engineering, Clemson University

    View abstract →

  • Causal relations in determining functionalities in perovskite oxides

    ORAL

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    Publication: A. Ghosh*, G. Palanichamy, D. P. Trujillo and S. Ghosh, "Insights into cation ordering of double perovskite oxides from machine learning and causal relations", Chem. Mater. 34, 16 (2022).

    Presenters

    • Ayana Ghosh

      Oak Ridge National Lab

    Authors

    • Ayana Ghosh

      Oak Ridge National Lab

    • Saurabh Ghosh

      SRM University, SRM Institute of Science and Technology KTR

    View abstract →

  • Curie temperature prediction models of magnetic Heusler alloys using machine learning methods based on first-principles data from ab-initio KKR-GF calculations

    ORAL

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    Publication: Planned paper: <br>There is a paper in preparation having the same working title as the talk.

    Presenters

    • Robin A Hilgers

      Peter Grünberg Institut and Institute for Advanced Simulation, Forschungszentrum Jülich and JARA, 52425 Jülich, Germany

    Authors

    • Robin A Hilgers

      Peter Grünberg Institut and Institute for Advanced Simulation, Forschungszentrum Jülich and JARA, 52425 Jülich, Germany

    • Roman Kovacik

      Peter Grünberg Institut and Institute for Advanced Simulation, Forschungszentrum Jülich and JARA, 52425 Jülich, Germany

    • Daniel Wortmann

      Forschungszentrum Jülich, Germany, Peter Grünberg Institut and Institute for Advanced Simulation, Forschungszentrum Jülich and JARA, 52425 Jülich, Germany

    • Stefan Blügel

      Forschungszentrum Jülich GmbH, Forschungszentrum Jülich, Peter Grünberg Institut and Institute for Advanced Simulation, Forschungszentrum Jülich and JARA, 52425 Jülich, Germany, Forschungszentrum Jülich GmBH

    View abstract →