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At least 55 records · Page 3

Data-driven studies of magnetic two-dimensional materials

We use a data-driven approach to study the magnetic and thermodynamic properties of van der Waals (vdW) layered materials. We investigate monolayers of the form A 2 B 2 X 6 , based on the known material Cr 2 Ge 2 Te 6 , using density functional theory (DFT) calculations and machine learning methods to determine their magnetic properties, such as magnetic order and magnetic moment. We also examine formation energies and use them as a proxy for chemical stability. We show that machine learning tools, combined with DFT calculations, can provide a computationally efficient means to predict properties of such two-dimensional (2D) magnetic materials. Our data analytics approach provides insights into the microscopic origins of magnetic ordering in these systems. For instance, we find that the X site strongly affects the magnetic coupling between neighboring A sites, which drives the magnetic ordering. Our approach opens new ways for rapid discovery of chemically stable vdW materials that exhibit magnetic behavior.

42 ENGINEERING↗

Multi-objective parametrization of interatomic potentials for large deformation pathways and fracture of two-dimensional materials

Abstract This investigation presents a generally applicable framework for parameterizing interatomic potentials to accurately capture large deformation pathways. It incorporates a multi-objective genetic algorithm, training and screening property sets, and correlation and principal component analyses. The framework enables iterative definition of properties in the training and screening sets, guided by correlation relationships between properties, aiming to achieve optimal parametrizations for properties of interest. Specifically, the performance of increasingly complex potentials, Buckingham, Stillinger-Weber, Tersoff, and modified reactive empirical bond-order potentials are compared. Using MoSe 2 as a case study, we demonstrate good reproducibility of training/screening properties and superior transferability. For MoSe 2 , the best performance is achieved using the Tersoff potential, which is ascribed to its apparent higher flexibility embedded in its functional form. These results should facilitate the selection and parametrization of interatomic potentials for exploring mechanical and phononic properties of a large library of two-dimensional and bulk materials.

Zhang, Xu↗

Out-of-Plane Magnetic Anisotropy Engineered via Band Distortion in Two-Dimensional Materials

We unveil the connection between magnetic anisotropy and band structures in Γ-specialized In 2 Se 3 /Fe 3 GeTe 2 heterostructure, through first-principles calculations. A significant band distortion occurs near the Γ point with a formed valley. As the band-distortion-caused valley moves relative to the quasivalence band maximum, the magnetic anisotropy switches between in-plane and out-of-plane magnetic anisotropy. Such a rule applies to either the strained or polarization-switched In 2 Se 3 /Fe 3 GeTe 2 heterostructure. Furthermore, these findings demonstrate the feasibility of predicting the magnetic anisotropy by band structure modification in two-dimensional magnetic systems.

2-dimensional systems↗

Optoelectronic properties of bent two-dimensional materials from first-principles methods combined with machine learning

A material’s interaction with light is highly relevant in the design of nanoelectronic devices such as photodiodes, solar cells, photocatalytic cells, phototransistors, and photodetectors. The interaction of a material with light can be altered by mechanical deformation. Fine tuning of the optical properties can be achieved by mechanical bending that alters the electronic structure. Optical properties strongly depend on band gaps, therefore any alteration in the band structure results in a changed optical response of the material. The impact of bending was explored in this project. The goal of this project was to assess the impact of mechanical bending of two-dimensional transition metal dichalcogenides on their optoelectronic properties, using first-principles methods. These first-principles approximations are largely built upon many-body theory for the optical properties of magnetic and topological nanoribbons. GW-BSE is standard for optical absorption, but it is less practical for collective excitations as it was shown in model systems. Time-dependent density functional theory, however, has better promises for collective excitations in low-dimensional materials.

36 MATERIALS SCIENCE↗

Multiphonon diffuse scattering in solids from first principles: Application to layered crystals and two-dimensional materials

Time-resolved diffuse scattering experiments have gained increasing attention due to their potential to reveal nonequilibrium dynamics of crystal lattice vibrations with full momentum resolution. Although progress has been made in interpreting experimental data on the basis of one-phonon scattering, understanding the role of individual phonons can be sometimes hindered by multiphonon excitations. In Ref. [M. Zacharias, H. Seiler, F. Caruso, D. Zahn, F. Giustino, P. C. Kelires, and R. Ernstorfer, Phys. Rev. Lett. 127, 207401 (2021)], we have introduced a rigorous approach for the calculation of the all-phonon inelastic scattering intensity of solids from first-principles. In the present work, we describe our implementation in detail and show that multiphonon interactions are captured efficiently by exploiting translational and time-reversal symmetries of the crystal. We demonstrate its predictive power by calculating the scattering patterns of monolayer molybdenum disulfide (MoS 2 ), bulk MoS 2 , and black phosphorus (bP), and we obtain excellent agreement with our measurements of thermal electron diffuse scattering. Remarkably, our results show that multiphonon excitations dominate in bP across multiple Brillouin zones, while in MoS 2 they play a less pronounced role. We expand our analysis for each system and examine the effect of individual atomic and interatomic vibrational motion on the diffuse scattering signals. We further demonstrate the high-throughput capability of our approach by reporting all-phonon scattering maps of two-dimensional MoSe 2 , WSe 2 , WS 2 , graphene, and CdI 2 , rationalizing in each case the effect of multiphonon processes. As a side point, we show that the special displacement method reproduces the thermally distorted configuration that generates precisely the all-phonon diffuse pattern. In conclusion, the present methodology opens the way for systematic calculations of the scattering intensity in crystals and the accurate interpretation of static and time-resolved inelastic scattering experiments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Quantum Machine-Learning for Eigenstate Filtration in Two-Dimensional Materials

Quantum machine-learning algorithms have emerged to be a promising alternative to their classical counterparts as they leverage the power of quantum computers. Such algorithms have been developed to solve problems like electronic structure calculations of molecular systems and spin models in magnetic systems. However, the discussion in all these recipes focuses specifically on targeting the ground state. Herein we demonstrate a quantum algorithm that can filter any energy eigenstate of the system based on either symmetry properties or a predefined choice of the user. The workhorse of our technique is a shallow neural network encoding the desired state of the system with the amplitude computed by sampling the Gibbs–Boltzmann distribution using a quantum circuit and the phase information obtained classically from the nonlinear activation of a separate set of neurons. We show that the resource requirements of our algorithm are strictly quadratic. To demonstrate its efficacy, we use state filtration in monolayer transition metal dichalcogenides which are hitherto unexplored in any flavor of quantum simulations. We implement our algorithm not only on quantum simulators but also on actual IBM-Q quantum devices and show good agreement with the results procured from conventional electronic structure calculations. We thus expect our protocol to provide a new alternative in exploring the band structures of exquisite materials to usual electronic structure methods or machine-learning techniques that are implementable solely on a classical computer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dynamics of ballistic photocurrents driven by Coulomb scattering in a two-dimensional material

First-principles real-time time-dependent density-functional theory (rt-TDDFT) calculations reveal the existence of ballistic photocurrents generated by Coulomb scattering, which has not previously been considered as a mechanism for the bulk photovoltaic effect. With monolayer GeS as an example, it is predicted that ballistic currents can be comparable to shift currents under experimentally accessible conditions.

2-dimensional systems↗

Topological Exact Flat Bands in Two-Dimensional Materials under Periodic Strain

Here we study flat bands and their topology in 2D materials with quadratic band crossing points under periodic strain. In contrast to Dirac points in graphene, where strain acts as a vector potential, strain for quadratic band crossing points serves as a director potential with angular momentum . We prove that when the strengths of the strain fields hit certain “magic” values, exact flat bands with emerge at charge neutrality point in the chiral limit, in strong analogy to magic angle twisted-bilayer graphene. These flat bands have ideal quantum geometry for the realization of fractional Chern insulators, and they are always fragile topological. The number of flat bands can be doubled for certain point group, and the interacting Hamiltonian is exactly solvable at integer fillings. We further demonstrate the stability of these flat bands against deviations from the chiral limit, and discuss possible realization in 2D materials.

36 MATERIALS SCIENCE↗