Mesoscale Phenomena in Functional Polycrystals and Their Nanostructures: Poster Session
Sponsored by: ACerS Electronics Division
Program Organizers: Serge Nakhmanson, University of Connecticut; Edward Gorzkowski, Naval Research Laboratory; James Wollmershauser, U.S. Naval Research Laboratory; Seungbum Hong, KAIST; Javier Garay, University of California, San Diego; Pierre-Eymeric Janolin, CentraleSupélec
Monday 5:00 PM
October 10, 2022
Room: Ballroom BC
Location: David L. Lawrence Convention Center
D-20: Asymmetric Tribology of Symmetric Polarization: Seongwoo Cho1; Iaroslav Gaponenko2; Kumara Cordero-Edwards2; Jordi Barceló-Mercader3; Irene Arias3; Jiwon Yeom1; Loïc Musy2; Céline Lichtensteiger2; Gustau Catalan4; Patrycja Paruch2; Seungbum Hong1; 1KAIST; 2University of Geneva; 3Universitat Politècnica de Catalunya; 4ICN2
We investigated asymmetric friction and wear of up and down oriented polarization domains in ferroelectric single crystals and thin films using scanning probe microscopy. Lateral force microscopy was used to visualize the local friction coefficient and topography modification following nanoscale wear in a controlled environment. Our study indicates that ferroelectric up domains have both a higher friction coefficient and faster wear rate than the down domains. We relate these nanotribological asymmetries to the asymmetric contribution of flexoelectric polarization in the up and down domains under a tip contact force. Exploiting the wear asymmetry combined with the switchable polar nature of ferroelectrics, we developed a resist/chemical/mask-free lithography technique which can be harnessed for potential electronics applications including optical devices, transistors, sensors, and energy harvesters.
D-21: Machine-learned Large-scale Model for Layered Amorphous Graphene: A Study of Its Structure and Thermodynamics: Chinonso Ugwumadu1; Rajendra Thapa1; Kishor Nepal1; David Drabold1; Jason Trembly1; 1Ohio University
The microscopic thermodynamical properties and atomistic structure of layered amorphous graphene (LAG) using Machine learning (ML) based interatomic potential (GAP) is discussed herein. ML-based potentials are opening new frontiers to understanding atomistic large-scale phenomena with near-first-principle properties. Fast empirical interatomic potentials like EDIP and REBO make large-scale molecular dynamics simulations possible but remain empirical and overestimate sp3 bonds in amorphous Carbon(aC). On the other hand, tight-binding schemes, including ab-initio methods like DFT give more accurate predictions but becomes computationally expensive with system size; limited to a few hundred atoms. The GAP ML interatomic potential for aC provides new insights into the transition of aC to LAG at canonical and isobaric-isothermal ensemble for large system sizes (~ 1000 atoms) while still reproducing DFT obtained results at small system size (~ 160 atoms). The thermal conductivity of LAG is also discussed with results being a direct consequence of large system scaling.
D-22: Mesoscale Modeling of Domain Wall Behavior in Perovskite Ferroelectrics: Charles Schwarz1; Ashok Gurung1; John Mangeri2; Serge Nakhmanson1; 1University of Connecticut; 2Luxembourg Institute of Science and Technology
We utilized a highly scalable real-space finite-element-method (FEM) based approach, implemented as an open-source module for the MOOSE (Multiphysics Object-Oriented Simulation Environment) FEM framework and combined with Ginzburg-Landau-Devonshire phenomenological theory, to simulate the behavior and properties of domain walls in generic perovskite ferroelectrics, such as BaTiO3 and PbTiO3. Domain wall thickness profiles were evaluated as functions of temperature for a variety of different wall types and material phases, and compared with results of previous phenomenological studies that employed a Fourier transformation approach in periodic systems. Behavior of some domain wall types under an applied harmonically varying electric field was also probed as a function of the driving field frequency, elucidating the contribution of domain wall motion to complex dielectric response of the material.