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

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arxiv 2406.02753 v2 pith:V4RHUB6F submitted 2024-06-04 cond-mat.mtrl-sci

classification cond-mat.mtrl-sci
keywords materialselectronicaccurateapplicationsbeencarloelectronfunctional
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abstract

The field of two-dimensional (2D) materials has grown dramatically in the last two decades. 2D materials can be utilized for a variety of next-generation optoelectronic, spintronic, clean energy, and quantum computation applications. These 2D structures, which are often exfoliated from layered van der Waals (vdW) 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. In order 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, MoS$_2$, CrI$_3$, VSe$_2$, 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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  1. A many-body characterization of the fundamental gap in monolayer CrI$_3$

    cond-mat.mtrl-sci 2025-06 conditional novelty 6.0 of 10

    Fixed-node and fixed-phase spin-orbit diffusion Monte Carlo predict a 2.9(1) eV fundamental gap for monolayer CrI3, consistent with a QSGW result and the highest optical reflectance peak.

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