University of Illinois Urbana-Champaign

Computation of van der Waals effects in layered materials

Krongchon, Kittithat

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KRONGCHON-DISSERTATION-2024.pdf

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https://hdl.handle.net/2142/127132

Description

Title
Computation of van der Waals effects in layered materials
Author(s)
Krongchon, Kittithat
Issue Date
2024-08-01
Director of Research (if dissertation) or Advisor (if thesis)
Wagner, Lucas K
Doctoral Committee Chair(s)
Ertekin, Elif
Committee Member(s)
  • Mahmood, Fahad
  • DeMarco, Brian L
Department of Study
Physics
Discipline
Physics
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
  • Layered materials
  • 2D materials
  • van der Waals
  • vdW
  • interactions
  • twisted bilayer graphene
  • TBG
  • cuprates
  • quantum Monte Carlo
  • QMC
  • density functional theory
  • DFT
  • graphene
  • bilayer
  • hexagonal boron nitride
  • hBN
  • moire
  • flat bands
  • corrugation
  • superconductor
  • superconductivity
  • strongly correlated
  • strong correlations
  • electron correlations
  • atomistic potential
  • molecular dynamics
  • phonons
  • vibrations
  • tight binding
  • tight-binding model
  • variational Monte Carlo
  • diffusion Monte Carlo
  • multi-scale modeling
  • optimization
  • wave function
  • quantum mechanics
  • Schrödinger equation
  • stacking-fault energy
  • vdW correction
  • electronic structure
  • relaxation
Abstract
Layered materials are a type of materials composed of multiple thin layers stacked on top of each other, which can exhibit interesting properties. These properties depend critically on the electron correlation induced forces between the layers, which are termed van der Waals (vdW) interactions. However, accurately modeling these interactions poses a challenge, especially in systems with large length scales like twisted bilayer graphene (TBG). To address this challenge, I employ a multi-scale modeling approach that combines first-principles methods, such as density functional theory (DFT) and quantum Monte Carlo (QMC), with atomistic potential models. In my first project, I analyze phonons in a cuprate material to understand the low-energy modes observed in experiment. These modes were proposed by experimentalists to be related to charge density waves in the material. Through my DFT calculations, we learned that these modes are shearing motions of the Bi planes, not the Cu-O planes that are generally believed to host charge density waves and superconductivity. In my second project, I calculate the relaxed atomic structure of TBG using the atomistic potential derived from QMC. In TBG, relaxation and corrugation significantly influence the electronic properties. However, widely used DFT-based vdW models predict different corrugations. To resolve this uncertainty, I use QMC, which treats electron correlations explicitly rather than through approximations, to compute the interlayer vdW interactions between graphene bilayers. By referencing the new QMC-derived potential, I demonstrate that some vdW approximations incorrectly predict properties like atomic structure and flat bandwidth. My study provides refined potential parameters and atomic corrugation data for graphene, useful for accurate computations in subsequent research. In my final project, I compute the interlayer interactions between graphene and hexagonal boron nitride (hBN), a common substrate in graphene experiments. Substrates can affect the corrugation and electronic structure. However, the graphene-substrate interaction has not been studied at the QMC accuracy level. By generating QMC energy data, I analyze the binding energy curve and stacking-fault energy from different vdW models, which can affect the structural relaxation and ultimately electronic properties. This work provides accurate potential parameters that will support future studies on graphene-hBN systems. The new state-of-the-art potential enables researchers to model electronic behaviors with greater accuracy.
Graduation Semester
2024-12
Type of Resource
Thesis
Handle URL
https://hdl.handle.net/2142/127132
Copyright and License Information
Copyright 2024 Kittithat Krongchon

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