Family of Two-Dimensional Transition Metal Dichlorides: Fundamental Properties, Structural Defects, and Environmental Stability

A large number of novel two-dimensional (2D) materials are constantly being discovered and deposited in databases. Consolidated implementation of machine learning algorithms and density functional theory (DFT)-based predictions have allowed the creation of several databases containing an unimaginable number of 2D samples. As the next step in this chain, the investigation leads to a comprehensive study of the functionality of the invented materials. In this work, a family of transition metal dichlorides have been screened out for systematic investigation of their structural stability, fundamental properties, structural defects, and environmental stability via DFT-based calculations. The work highlights the importance of using the potential of the invented materials and proposes a comprehensive characterization of a new family of 2D materials.

PASP: Property analysis and simulation package for materials

We have developed a software package, namely, PASP (Property Analysis and Simulation Package for materials), to analyze the structural, electronic, magnetic, and thermodynamic properties of complex condensed matter systems. Our package integrates several functionalities including symmetry analysis, global structure searching methods, effective Hamiltonian methods, and Monte Carlo simulation methods. In conjunction with first-principles calculations, PASP has been successfully applied to diverse physical systems. In this paper, we give a brief introduction to its main features and underlying theoretical formulism. Some typical applications are provided to demonstrate the usefulness, high efficiency, and reliability of PASP. We expect that further developments will make PASP a general-purpose tool for material simulation and property calculation of condensed matters.

Defect Dynamics in 2-D MoS2 Probed by Using Machine Learning, Atomistic Simulations, and High-Resolution Microscopy

Structural defects govern various physical, chemical, and optoelectronic properties of two-dimensional transition-metal dichalcogenides (TMDs). A fundamental understanding of the spatial distribution and dynamics of defects in these low-dimensional systems is critical for advances in nanotechnology. However, such understanding has remained elusive primarily due to the inaccessibility of (a) necessary time scales via standard atomistic simulations and (b) required spatiotemporal resolution in experiments. Here, we take advantage of supervised machine learning, in situ high-resolution transmission electron microscopy (HRTEM) and molecular dynamics (MD) simulations to overcome these limitations. We combine genetic algorithms (GA) with MD to investigate the extended structure of point defects, their dynamical evolution, and their role in inducing the phase transition between the semiconducting (2H) and metallic (1T) phase in monolayer MoS₂. GA-based structural optimization is used to identify the long-range structure of randomly distributed point defects (sulfur vacancies) for various defect densities. Regardless of the density, we find that organization of sulfur vacancies into extended lines is the most energetically favorable. HRTEM validates these findings and suggests a phase transformation from the 2H-to-1T phase that is localized near these extended defects when exposed to high electron beam doses. MD simulations elucidate the molecular mechanism driving the onset of the 2H to 1T transformation and indicate that finite amounts of 1T phase can be retained by increasing the defect concentration and temperature. This work significantly advances the current understanding of defect structure/evolution and structural transitions in 2D TMDs, which is crucial for designing nanoscale devices with desired functionality.

Global minimum beryllium hydride sheet with novel negative Poisson's ratio: first-principles calculations

As one of the most prominent metal-hydrides, beryllium hydride has received much attention over the past several decades, since 1978, and is considered as an important hydrogen storage material. By reducing the dimensionality from 3 to 2, the beryllium hydride monolayer is isoelectronic with graphene; thus the existence of its two-dimensional (2D) form is theoretically feasible and experimentally expected. However, little is known about its 2D form. In this work, by a global minimum search with the particle swarm optimization method via density functional theory computations, we predicted two new stable structures for the beryllium hydride sheets, named α-BeH2 and β-BeH2 monolayers. Both structures have more favorable thermodynamic stability than the recently reported planar square form (Nanoscale, 2017, 9, 8740), due to the forming of multicenter delocalized Be-H bonds. Utilizing the recently developed SSAdNDP method, we revealed that three-center-two-electron (3c-2e) delocalized Be-H bonds are formed in the α-BeH2 monolayer, while for the β-BeH2 monolayer, novel four-center-two-electron (4c-2e) delocalized bonds are observed in the 2D system for the first time. These unique multicenter chemical bonds endow both α- and β-BeH2 with high structural stabilities, which are further confirmed by the absence of imaginary modes in their phonon spectra, the favorable formation energies comparable to bulk and cluster beryllium hydride, and the high mechanical strength. These results indicate the potential for experimental synthesis. Furthermore, both α- and β-BeH2 are wide-bandgap semiconductors, in which the α-BeH2 has unusual mechanical properties with a negative Poisson's ratio of -0.19. If synthesized, it would attract interest both in experiment and theory, and be a new member of the 2D family isoelectronic with graphene.

Half-metallicity in a honeycomb–kagome-lattice Mg3C2 monolayer with carrier doping

A transition from an anti-ferromagnetic semiconductor to a ferromagnetic half metal can be induced by carrier doping in the honeycomb–kagome-lattice Mg₃C₂ monolayer.