Systematic DFT+U and Quantum Monte Carlo Benchmark of Magnetic Two-Dimensional (2D) CrX3 (X = I, Br, Cl, F)

Theoretical Study on the Raman Effect Due to Magnons in Two-Dimensional Magnets

Raman spectroscopy is one of the most useful experimental tools for studying elementary excitations in two-dimensional (2D) materials. The Raman scattering due to phonons was widely employed for detecting structural evolutions, especially those caused by magnetic phase transitions in 2D magnets. A first-principles theory of the Raman scattering effect caused by magnons is still lacking. We theoretically study the magnon Raman effect in 2D magnet CrI3. We propose a first-principles method and have calculated the intensity of circularly polarized Raman signals due to different magnon modes in the CrI3 monolayer and bilayers. The calculated Raman intensities due to magnons in the CrI3 monolayer and the rhombohedral bilayer are consistent with the selection rule deduced from the magnon pseudoangular moment and the parity of magnon modes. We also find that the selection rule is violated in the symmetry-broken monoclinic bilayer due to interlayer coupling.

Inverse Design of Next-Generation Superconductors Using Data-Driven Deep Generative Models

Finding new superconductors with a high critical temperature (T_c) has been a challenging task due to computational and experimental costs. We present a diffusion model inspired by the computer vision community to generate new superconductors with unique structures and chemical compositions. Specifically, we used a crystal diffusion variational autoencoder (CDVAE) along with atomistic line graph neural network (ALIGNN) pretrained models and the Joint Automated Repository for Various Integrated Simulations (JARVIS) superconducting database of density functional theory (DFT) calculations to generate new superconductors with a high success rate. We started with a DFT data set of ∼1000 superconducting materials to train the diffusion model. We used the model to generate 3000 new structures, which along with pretrained ALIGNN screening results in 61 candidates. For the top candidates, we performed DFT calculations for validation. Such approaches go beyond funnel-like materials screening approaches and allow for the inverse design of next-generation materials.

A Quantum Monte Carlo Study of the Structural, Energetic, and Magnetic Properties of Two-Dimensional H and T Phase VSe2

Previous works have controversially claimed near-room-temperature ferromagnetism in two-dimensional (2D) VSe₂, with conflicting results throughout the literature. These discrepancies in magnetic properties between both phases (T and H) of 2D VSe₂ are most likely due to the structural parameters being coupled to the magnetic properties. Specifically, both phases have a close lattice match and similar total energies, which makes it difficult to determine which phase is being observed experimentally. In this study, we used a combination of density functional theory, highly accurate diffusion Monte Carlo (DMC), and a surrogate Hessian line-search optimization technique to resolve the previously reported discrepancy in structural parameters and relative phase stability. With DMC accuracy, we determined the free-standing geometry of both phases and constructed a phase diagram. Our findings demonstrate the successes of the DMC method coupled with the surrogate Hessian structural optimization technique when applied to a 2D magnetic system.

High-Throughput DFT-Based Discovery of Next Generation Two-Dimensional (2D) Superconductors

High-throughput density functional theory (DFT) calculations allow for a systematic search for conventional superconductors. With the recent interest in two-dimensional (2D) superconductors, we used a high-throughput workflow to screen over 1000 2D materials in the JARVIS-DFT database and performed electron-phonon coupling calculations, using the McMillan-Allen-Dynes formula to calculate the superconducting transition temperature (T_c) for 165 of them. Of these 165 materials, we identify 34 dynamically stable structures with transition temperatures above 5 K, including materials such as W₂N₃, NbO₂, ZrBrO, TiClO, NaSn₂S₄, Mg₂B₄C₂, and the previously unreported Mg₂B₄N₂ (T_c = 21.8 K). Finally, we performed experiments to determine the T_c of selected layered superconductors (2H-NbSe₂, 2H-NbS₂, ZrSiS, FeSe) and discuss the measured results within the context of our DFT results. We aim that the outcome of this workflow can guide future computational and experimental studies of new and emerging 2D superconductors by providing a roadmap of high-throughput DFT data.