Toward improved property prediction of 2D materials using many-body quantum Monte Carlo methods Article Swipe

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Daniel Wines , Jeonghwan Ahn , Anouar Benali , Paul R. C. Kent , Jaron T. Krogel , Yongkyung Kwon , Luboš Mitáš , Fernando A. Reboredo , Brenda M. Rubenstein , Kayahan Saritas , Hyeondeok Shin , I. Štich , Can Ataca ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.1063/5.0220257

The field of 2D materials has grown dramatically in the past two decades. 2D materials can be utilized for a variety of next-generation optoelectronic, spintronic, clean energy, and quantum computing applications. These 2D structures, which are often exfoliated from layered van der Waals materials, possess highly inhomogeneous electron densities and can possess short- and long-range electron correlations. The complexities of 2D materials make them challenging to study with standard mean-field electronic structure methods such as density functional theory (DFT), which relies on approximations for the unknown exchange-correlation functional. To overcome the limitations of DFT, highly accurate many-body electronic structure approaches such as diffusion Monte Carlo (DMC) can be utilized. In the past decade, DMC has been used to calculate accurate magnetic, electronic, excitonic, and topological properties in addition to accurately capturing interlayer interactions and cohesion and adsorption energetics of 2D materials. This approach has been applied to 2D systems of wide interest, including graphene, phosphorene, MoS2, CrI3, VSe2, GaSe, GeSe, borophene, and several others. In this review article, we highlight some successful recent applications of DMC to 2D systems for improved property predictions beyond standard DFT.

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Monte Carlo method Property (philosophy) Quantum Computer science Statistical physics Physics Mathematics Statistics Quantum mechanics Epistemology Philosophy

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Type: article
Language: en
Landing Page: https://doi.org/10.1063/5.0220257
PDF: https://pubs.aip.org/aip/apr/article-pdf/doi/10.1063/5.0220257/20663720/031317_1_5.0220257.pdf
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Cited By: 3
References: 402
Related Works: 10
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DOI: https://doi.org/10.1063/5.0220257

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Title: Toward improved property prediction of 2D materials using many-body quantum Monte Carlo methods

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Language: en

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Publication year: 2025

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Publication date: 2025-08-22

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Authors: Daniel Wines, Jeonghwan Ahn, Anouar Benali, Paul R. C. Kent, Jaron T. Krogel, Yongkyung Kwon, Luboš Mitáš, Fernando A. Reboredo, Brenda M. Rubenstein, Kayahan Saritas, Hyeondeok Shin, I. Štich, Can Ataca

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Landing page: https://doi.org/10.1063/5.0220257

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Concepts: Monte Carlo method, Property (philosophy), Quantum, Computer science, Statistical physics, Physics, Mathematics, Statistics, Quantum mechanics, Epistemology, Philosophy

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Cited by: 3

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