Exploring charge density waves in twisted bilayer NbSe2 with machine learning

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• Dr Zac Goodwin (Oxford)
• Wednesday 04 June 2025, 11:00-12:00
• Seminar Room 3, RDC.

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This is a joint seminar with the LJC .

Niobium diselenide has garnered significant attention over the past few decades because of the coexis tence of superconductivity and charge density waves (CDWs), observable down to the monolayer limit. Introducing relative twist angles between monolayers, in the field of twistronics, offers a new variable to tune these systems, yet a fundamental question remains: do CDWs persist in moiré structures, and how are they altered compared to the pristine monolayer/bilayer? Traditional first-principles methods face limitations due to the computational resources required for long-wavelength moiré patterns; for instance, a 1-degree twist angle necessitates modeling over 10,000 atoms, making simulations impractical. This study employs first-principles data to develop machine learning interatomic potentials with the Allegro architecture, enabling scalable and accurate simulations. We investigate the formation and evolution of CDW order in monolayers and twisted bilayers, validating our results against density functional theory calculations with minimal errors in energy and forces. Beyond niobium diselenide, our goal is to establish a protocol for studying CDWs in two-dimensional systems. We outline strategies for producing training data and perform a detailed hyperparameter scan to identify key aspects for studying these systems [1].

1. Norma Rivano et al. arXiv.2504.13675 2025

This talk is part of the Theory of Condensed Matter series.

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