Silicene growth through island migration and coalescence

Ab Initio-Based Bond Order Potential for Arsenene Polymorphs Developed via Hierarchical Reinforcement Learning

Arsenene, a less-explored two-dimensional material, holds the potential for applications in wearable electronics, memory devices, and quantum systems. This study introduces a bond-order potential model with Tersoff formalism, the ML-Tersoff, which leverages multireward hierarchical reinforcement learning (RL), trained on an ab initio data set. This data set covers a spectrum of properties for arsenene polymorphs, enhancing our understanding of its mechanical and thermal behaviors without the complexities of traditional models requiring multiple parameter sets. Our RL strategy utilizes decision trees coupled with a hierarchical reward strategy to accelerate convergence in high-dimensional continuous search spaces. Unlike the Stillinger-Weber approach, which demands separate formalisms for buckled and puckered forms, the ML-Tersoff model concurrently captures multiple properties of the two polymorphs by effectively representing the local environment, thereby avoiding the need for different atomic types. We apply the ML model to understand the mechanical and thermal properties of the arsenene polymorphs and nanostructures. We observe an inverse relationship between the critical strain and temperature in arsenene. Thermal conductivity calculations in nanosheets show good agreement with ab initio data, reflecting a decrease in thermal conductivity attributable to increased anharmonic effects at higher temperatures. We also apply the model to predict the thermal behavior of arsenene nanotubes.

Silicene growth mechanisms on Au(111) and Au(110) substrates

Despite the remarkable theoretical applications of silicene, its synthesis remains a complex task, with epitaxial growth being one of the main routes involving depositing evaporated Si atoms onto a suitable substrate. Additionally, the requirement for a substrate to maintain the silicene stability poses several difficulties in accurately determining the growth mechanisms and the resulting structures, leading to conflicting results in the literature. In this study, large-scale molecular dynamics simulations are performed to uncover the growth mechanisms and characteristics of epitaxially grown silicene sheets on Au(111) and Au(110) substrates, considering different temperatures and Si deposition rates. The growth process has been found to initiate with the nucleation of several independent islands homogeneously distributed on the substrate surface, which gradually merge to form a complete silicene sheet. The results consistently demonstrate the presence of a buckled silicene structure, although this characteristic is notably reduced when using an Au(111) substrate. Furthermore, the analysis also focuses on the quality and growth mode of the silicene sheets, considering the influence of temperature and deposition rate. The findings reveal a prevalence of the Frank-van der Merwe growth mode, along with diverse forms of defects throughout the sheets.

Epitaxial growth and structural properties of silicene and other 2D allotropes of Si

Since the breakthrough of graphene, considerable efforts have been made to search for two-dimensional (2D) materials composed of other group 14 elements, in particular silicon and germanium, due to their valence electronic configuration similar to that of carbon and their widespread use in the semiconductor industry. Silicene, the silicon counterpart of graphene, has been particularly studied, both theoretically and experimentally. Theoretical studies were the first to predict a low-buckled honeycomb structure for free-standing silicene possessing most of the outstanding electronic properties of graphene. From an experimental point of view, as no layered structure analogous to graphite exists for silicon, the synthesis of silicene requires the development of alternative methods to exfoliation. Epitaxial growth of silicon on various substrates has been widely exploited in attempts to form 2D Si honeycomb structures. In this article, we provide a comprehensive state-of-the-art review focusing on the different epitaxial systems reported in the literature, some of which having generated controversy and long debates. In the search for the synthesis of 2D Si honeycomb structures, other 2D allotropes of Si have been discovered and will also be presented in this review. Finally, with a view to applications, we discuss the reactivity and air-stability of silicene as well as the strategy devised to decouple epitaxial silicene from the underlying surface and its transfer to a target substrate.

Chemical vapor deposition of 2D materials: A review of modeling, simulation, and machine learning studies

Chemical vapor deposition (CVD) is extensively used to produce large-area two-dimensional (2D) materials. Current research is aimed at understanding mechanisms underlying the nucleation and growth of various 2D materials, such as graphene, hexagonal boron nitride (hBN), and transition metal dichalcogenides (e.g., MoS₂/WSe₂). Herein, we survey the vast literature regarding modeling and simulation of the CVD growth of 2D materials and their heterostructures. We also focus on newer materials, such as silicene, phosphorene, and borophene. We discuss how density functional theory, kinetic Monte Carlo, and reactive molecular dynamics simulations can shed light on the thermodynamics and kinetics of vapor-phase synthesis. We explain how machine learning can be used to develop insights into growth mechanisms and outcomes, as well as outline the open knowledge gaps in the literature. Our work provides consolidated theoretical insights into the CVD growth of 2D materials and presents opportunities for further understanding and improving such processes

Tunable spin-polarized band gap in Si2/NiI2 vdW heterostructure

Using density functional theory (DFT) calculations we investigate the structural and electronic properties of a heterogeneous van der Waals (vdW) structure consisting of silicene and NiI₂ single layers. We observe an interaction between the two layers with a net charge transfer from the ferromagnetic semiconductor NiI₂ to silicene, breaking the inversion symmetry of the silicene structure. However, the charges flow in opposite directions for the two spin channels, which leads to a vdW heterostructure with a spin-polarized band gap between the π and π* states. The band gap can be tuned by controlling the vertical distance between the layers. The features shown by this vdW heterostructure are new, and we believe that silicene on a NiI₂ layer can be used to construct heterostructures which have appropriate properties to be used in nanodevices where control of the spin-dependent carrier mobility is necessary and can be incorporated into silicon based electronics.

Using density functional theory (DFT) calculations we investigate the structural and electronic properties of a heterogeneous van der Waals (vdW) structure consisting of silicene and NiI₂ single layers.

Machine learning a bond order potential model to study thermal transport in WSe2 nanostructures

Nanostructures of transition metal di-chalcogenides (TMDCs) exhibit exotic thermal, chemical and electronic properties, enabling diverse applications from thermoelectrics and catalysis to nanoelectronics. The thermal properties of these nanoscale TMDCs are of particular interest for thermoelectric applications. Thermal transport studies on nanotubes and nanoribbons remain intractable to first principles calculations whereas existing classical molecular models treat the two chalcogen layers in a monolayer with different atom types; this imposes serious limitations in studying multi-layered TMDCs and dynamical phenomena such as nucleation and growth. Here, we overcome these limitations using machine learning (ML) and introduce a bond order potential (BOP) trained against first principles training data to capture the structure, dynamics, and thermal transport properties of a model TMDC such as WSe2. The training is performed using a hierarchical objective genetic algorithm workflow to accurately describe the energetics, as well as thermal and mechanical properties of a free-standing sheet. As a representative case study, we perform molecular dynamics simulations using the ML-BOP model to study the structure and temperature-dependent thermal conductivity of WSe2 tubes and ribbons of different chiralities. We observe slightly higher thermal conductivities along the armchair direction than zigzag for WSe2 monolayers but the opposite effect for nanotubes, especially of smaller diameters. We trace the origin of these differences to the anisotropy in thermal transport and the restricted momentum selection rules for phonon-phonon Umpklapp scattering. The developed ML-BOP model is of broad interest and will facilitate studies on nucleation and growth of low dimensional WSe2 structures as well as their transport properties for thermoelectric and thermal management applications.

The adsorption of silicon on an iridium surface ruling out silicene growth

The adsorption of Si atoms on a metal surface might proceed through complex surface processes, whose rate is determined differently by factors such as temperature, Si coverage, and metal cohesive energy. Among other transition metals, iridium is a special case since the Ir(111) surface was reported first, in addition to Ag(111), as being suitable for the epitaxy of silicene monolayers. In this study we followed the adsorption of Si on the Ir(111) surface via high resolution core level photoelectron spectroscopy, starting from the clean metal surface up to a coverage exceeding one monolayer, in a temperature range between 300 and 670 K. Density functional theory calculations were carried out in order to evaluate the stability of the different Si adsorption configurations as a function of the coverage. Results indicate that, at low coverage, the Si adatoms tend to occupy the hollow Ir sites, although a small fraction of them penetrates the first Ir layer. Si penetration of the Ir surface can take place if the energy gained upon Si adsorption is used to displace the Ir surface atoms, rather then being dissipated differently. At a Si coverage of ∼1 monolayer, the Ir 4f spectrum indicates that not only the metal surface but also the layers underneath are perturbed. Our results point out that the Si/Ir(111) interface is unstable towards Si-Ir intermixing, in agreement with the silicide phase formation reported in the literature for the reverted interface.

The mechanism for the stabilization and surfactant properties of epitaxial silicene

Using real-time in situ scanning tunneling microscopy and density functional theory simulations, we have studied the growth of Si films on Ag(111) beyond the silicene monolayer, evidencing the existence of metastable phases and an original growth mechanism. Above monolayer Si coverage, an initial structure forms, which is identified as an Ag-free Si bilayer with additional Si adatoms. With further deposition, this structure is replaced by a distinct bilayer structure covered by Si trimers and Ag atoms. The formation of these bilayers follows counterintuitive dynamics: they are partially inserted within the Ag substrate and form by expelling, from the underlying substrate, the atoms that reinsert below the adjacent silicene layer. The growth is therefore characterized by an unexpected "surfactant competition" between Ag and silicene: while silicene is a metastable surfactant for the Ag(111) surface, Ag plays the role of a surfactant for thicker diamond-like Si islands. In spite of being thermodynamically unfavoured, the silicene monolayer is, thus, a remarkably stable structure because of the high kinetic barrier for the growth of thicker layers.