相关论文: Predicting phase preferences of two-dimensional tr…

Machine Learning (ML) techniques are revolutionizing the way to perform efficient materials modeling. Nevertheless, not all the ML approaches allow for the understanding of microscopic mechanisms at play in different phenomena. To address…

Machine learning has the potential to accelerate materials discovery by accurately predicting materials properties at a low computational cost. However, the model inputs remain a key stumbling block. Current methods typically use…

Atomically thin polycrystalline transition-metal dichalcogenides (TMDs) are relevant to both fundamental science investigation and applications. TMD thin-films present uniquely difficult challenges to effective nanoscale crystalline…

This article explores the recent advancements in atomically thin two-dimensional transition metal dichalcogenides (2D TMDs) and their potential applications in various fields, including nanoelectronics, photonics, sensing, energy storage,…

Transition Metal Dichalcogenides (TMDs) are one of the most studied two-dimensional materials in the last 5-10 years due to their extremely interesting layer dependent properties. Despite the presence of vast research work on TMDs, the…

Crystallization of the amorphous phases into metastable crystals plays a fundamental role in the formation of new matter, from geological to biological processes in nature to synthesis and development of new materials in the laboratory.…

Determining the stability of chemical compounds is essential for advancing material discovery. In this study, we introduce a novel deep neural network model designed to predict a crystal's formation energy, which identifies its stability…

The tunability of physical properties in transition metal dichalcogenides (TMDCs) through point defect engineering offers significant potential for the development of next-generation optoelectronic and high-tech applications. Building upon…

Magnetic materials have been applied in a large variety of technologies, from data storage to quantum devices. The development of 2D materials has opened new arenas for magnetic compounds, even when classical theories discourage their…

Among two-dimensional (2D) materials, transition metal dichalcogenides (TMDs) stand out for their remarkable electronic, optical, and chemical properties. In addition to being variable bandgap semiconductor materials, the atomic thinness…

Transition metal dichalcogenides (TMDs) are two-dimensional (2D) materials with remarkable electrical, optical and chemical properties. One promising strategy to tailor TMD properties of TMDs is to create alloys through dopant-induced…

Atomically thin group-VIB transition metal dichalcogenides (TMDs) have recently emerged as a new class of two-dimensional (2D) semiconductors with extraordinary properties including the direct band gap in the visible frequency range, the…

Two-dimensional semiconductors, known as Transition Metal Dichalcogenides (TMDCs), are of great interest among many materials due to their unique 2D characteristics, including exceptional electronic and optical properties. These compounds…

Two-dimensional transition metal dichalcogenides (TMDs) exist in two polymorphs, referred to as $1T$ and $1H$, depending on the coordination sphere of the transition metal atom. The broken octahedral and trigonal prismatic symmetries lead…

Machine learning algorithms have been available since the 1990s, but it is much more recently that they have come into use also in the physical sciences. While these algorithms have already proven to be useful in uncovering new properties…

Transition metal dichalcogenides (TMDs) are considered an advantageous alternative to their celebrated two-dimensional (2D) van der Waals akin compound, graphene, for a number of applications, especially those requiring a gapped and…

We present a comprehensive first-principles study of the structural and elastic properties of 2H-MX$_2$ transition metal dichalcogenides (TMDs) (M = W, Mo, Ta, Nb; X = S, Se). Using density functional theory with various van der Waals…

Two-dimensional (2D) materials have been a central focus of recent research because they host a variety of properties, making them attractive both for fundamental science and for applications. It is thus crucial to be able to identify…

Despite considerable interest in layered transition metal dichalcogenides (TMDs), such as MX2 with M = (Mo, W) and X = (S, Se, Te), the physical origin of their topological nature is still poorly understood. In the conventional view of…

Machine learning has proven to be a valuable tool to approximate functions in high-dimensional spaces. Unfortunately, analysis of these models to extract the relevant physics is never as easy as applying machine learning to a large dataset…