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Computational Design and Discovery of Novel Materials: Graphene and 2D Materials

FOCUS · R56 · ID: 381723

Presentations

  • Machine Learning-Enabled Design of Point Defects in 2D Materials

    ORAL

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    Presenters

    • Nathan C Frey

      University of Pennsylvania

    Authors

    • Nathan C Frey

      University of Pennsylvania

    • Deji Akinwande

      University of Texas at Austin, Microelectronics Research Center, The University of Texas

    • Deep M Jariwala

      University of Pennsylvania

    • Vivek b Shenoy

      University of Pennsylvania

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  • Stability, Electronic, Magnetic and Piezoelectric Properties of Two Dimensional Transition Metal Silicates

    ORAL

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    Presenters

    • Kayahan Saritas

      Yale University, Department of Applied Physics, Yale University, Applied Physics, Yale University

    Authors

    • Kayahan Saritas

      Yale University, Department of Applied Physics, Yale University, Applied Physics, Yale University

    • Nassar Doudin

      Yale University

    • Eric I. Altman

      Yale University

    • Sohrab Ismail-Beigi

      Department of Mechanical Engineering & Materials Science, Yale University, Yale University

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  • Piecewise Hamiltonian construction of a metal (NbS<sub>2</sub>)/semiconductor(WSe<sub>2</sub>) two-dimensional (2D) hybrid heterojunction.

    ORAL

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    Presenters

    • Poonam Kumari

      CNR-ICCOM, Consiglio Nazionale delle Ricerche, via G. Moruzzi 1, 56124, Pisa, S N Bose National Center for Basic Science

    Authors

    • Poonam Kumari

      CNR-ICCOM, Consiglio Nazionale delle Ricerche, via G. Moruzzi 1, 56124, Pisa, S N Bose National Center for Basic Science

    • Luca Sementa

      IPCF, Consiglio Nazionale delle Ricerche, via G. Moruzzi 1, 56124, Pisa

    • Alessandro Fortunelli

      CNR-ICCOM, Consiglio Nazionale delle Ricerche, via G. Moruzzi 1, 56124, Pisa

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  • Resonant tunneling and the transmission over a non-square barrier in α-T<sub>3</sub> lattice

    ORAL

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    Presenters

    • Nicholas Weekes

      Physics and Computer Science, Medgar Evers college, CUNY

    Authors

    • Nicholas Weekes

      Physics and Computer Science, Medgar Evers college, CUNY

    • Andrii Iurov

      Medgar Evers College, Physics and Computer Science, Medgar Evers college, CUNY, Physics and Astronomy, Medgars Evers college,City University of New York, Department of Physics and Computer Science, Medgar Evers College of City University of New York, Physics and Computer Science, Medgar Evers College

    • Liubov Zhemchuzhna

      Medgar Evers College, Physics and Computer Science, Medgar Evers college, CUNY, Department of Physics and Astronomy, Hunter College of the City University of New York

    • Godfrey Anthony Gumbs

      Hunter College, Physics and Astronomy, Hunter College, Physics and Astronomy, Hunter college, CUNY, Physics, Hunter College of CUNY, Physics and Astronomy, Hunter college, City University of New York, Department of Physics and Astronomy, Hunter College of the City University of New York

    • Danhong Huang

      US Air Force Research Lab (AFRL/RVSU), Air force research lab, Space Vehicles Directorate, US Air Force Research Laboratory, Air Force Research Lab - Kirtland, Center for High Technology Materials, University of New Mexico, US Air Force Research Laboratory

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  • Air-Stable Monolayer Cu<sub>2</sub>Se Exhibits a Purely Thermal Structural Phase Transition

    ORAL

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    Presenters

    • Yang Song

      Institute of Physics, Chinese Academy of Sciences

    Authors

    • Yang Song

      Institute of Physics, Chinese Academy of Sciences

    • Kai Qian

      Institute of Physics, Chinese Academy of Sciences

    • Lei Gao

      Institute of Physics, Chinese Academy of Sciences

    • Xiya Chen

      Institute of Physics, Chinese Academy of Sciences

    • Yu-Yang Zhang

      Chinese Academy of Sciences,Institute of Physics, University of Chinese Academy of Sciences, Institute of Physics and University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing 100190, China, School of physical sciences, Institute of Physics and University of Chinese Academy of Sciences, Institute of Physics, Chinese Academy of Sciences, Institute of Physics & University of Chinese Academy of Sciences, Chinese Academy of Sciences

    • Xiao Lin

      Institute of Physics, Chinese Academy of Sciences

    • Shixuan Du

      Chinese Academy of Sciences,Institute of Physics, Institute of Physics and University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing 100190, China, School of physical sciences, Institute of Physics and University of Chinese Academy of Sciences, Institute of Physics, Chinese Academy of Sciences, Chinese Academy of Science, Chinese Academy of Sciences, Institute of Physics, Institute of Physics & University of Chinese Academy of Sciences, Chinese Academy of Sciences

    • Min Ouyang

      Institute of High Energy Physics, Chinese Academy of Sciences, University of Maryland

    • Sokrates T Pantelides

      Department of Physics and Engineering, Vanderbilt University, Department of Physics and Astronomy, Vanderbilt Univ, Department of Physics and Astronomy, Vanderbilt University, Vanderbilt Univ, Department of Physics and Astronomy, Vanderbilt University, Nashville, TN 37235, USA, Institute of Physics, Chinese Academy of Sciences, Department of Physics and Astronomy & Department of Electrical Engineering and Computer Science, Vanderbilt University, Department of Physics and Astronomy and Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, Department of Electrical Engineering and Computer Science, Vanderbilt University, Department of Physics and Astronomy and Department of Electrical Engineering and Computer Science, Vanderbilt University, Vanderbilt University

    • Hongjun Gao

      Chinese Academy of Sciences,Institute of Physics, Institute of Physics, Chinese Academy of Sciences, Chinese Academy of Sciences, Institute of Physics

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  • A machine learning approach to predict the magnetic property of metal-doped graphene

    ORAL

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    Presenters

    • Eric Inclan

      Department of Aerospace Engineering, Georgia Institute of Technology

    Authors

    • Eric Inclan

      Department of Aerospace Engineering, Georgia Institute of Technology

    • Jack Lasseter

      Department of Materials Science and Engineering, University of Tennessee

    • Lizhi Zhang

      Department of Physics and Astronomy, University of Tennessee

    • Mina Yoon

      Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge National Laboratory, USA, Oak Ridge National Lab, CNMS, Oak Ridge National Lab

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  • Computational design and phase prediction of transition metal dichalcogenides using machine learning techniques

    ORAL

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    Presenters

    • Pratibha Dev

      Howard University, Physics, Howard University, Physics and Astronomy, Howard University

    Authors

    • Pankaj Kumar

      Howard University

    • Vinit Sharma

      University of Tennessee, Knoxville, TN, University of Tennessee

    • Pratibha Dev

      Howard University, Physics, Howard University, Physics and Astronomy, Howard University

    View abstract →