April 7 - 11, 2025
Seattle, Washington
Symposium Supporters
2025 MRS Spring Meeting & Exhibit
QT03.02.03

New Theoretical Insights into Moiré Solids from Machine Learning Assisted First-Principles Calculations

When and Where

Apr 8, 2025
2:30pm - 3:00pm
Summit, Level 4, Room 441

Presenter(s)

Co-Author(s)

Ting Cao1

University of Washington1

Abstract

Ting Cao1

University of Washington1
This talk will show our recent theoretical and computational investigations into moiré superlattices. We start by demonstrating that a deep neural network guided by first-principles data can be used to examine moiré structural reconstruction in various homobilayers and heterobilayers of transition metal dichalcogenides. Going beyond the capacity of direct DFT calculations, our machine-learning enabled workflow discovers salient structural features and key topological characters controlled by twist angles, layer composition, and other tuning knobs. This knowledge can be used to predict new forms of moiré potential and moiré topology, which enable the study of novel excited states. We connect our theoretical discoveries to experimental results and explore potential applications.

Keywords

2D materials

Symposium Organizers

Jairo Velasco Jr., University of California, Santa Cruz
Giulia Pacchioni, Springer Nature
Matthew Yankowitz, University of Washington
Long Ju, Massachusetts Institute of Technology

Symposium Support

Gold
Gordon and Betty Moore Foundation

Silver
Bluefors

Bronze
QUANTUM DESIGN
Scienta Omicron, Inc.
Thouless Institute for Quantum Matter

Session Chairs

Long Ju
Yahui Zhang

In this Session