相关论文: Engineering Point Defects in MoS2 for Tailored Mat…

Pre-trained transformer language models on large unlabeled corpus have produced state-of-the-art results in natural language processing, organic molecule design, and protein sequence generation. However, no such models have been applied to…

To leverage advancements in machine learning for metallic materials design and property prediction, it is crucial to develop a data-reduced representation of metal microstructures that surpasses the limitations of current physics-based…

Accelerated materials discovery is an urgent demand to drive advancements in fields such as energy conversion, storage, and catalysis. Property-directed generative design has emerged as a transformative approach for rapidly discovering new…

Patterning and defect engineering are key methods to tune 2D materials' properties. However, generating 2D periodic patterns of point defects in 2D materials has been elusive until now, despite the well-established methods for creating…

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…

Computing atomic-scale properties of chemically disordered materials requires an efficient exploration of their vast configuration space. Traditional approaches such as Monte Carlo or Special Quasirandom Structures either entail sampling an…

We present a physically motivated strategy for the construction of training sets for transferable machine learning interatomic potentials. It is based on a systematic exploration of all possible space groups in random crystal structures,…

We calculate from first principles the electronic structure and optical properties of a number of transition metal dichalcogenide (TMD) bilayer heterostructures consisting of MoS2 layers sandwiched with WS2, MoSe2, MoTe2, BN, or graphene…

Two-dimensional (2D) transition metal dichalcogenides (TMDs) have recently been shown to demonstrate non-volatile resistive switching (NVRS), offering significant advantages such as high-density integration and low energy consumption due to…

Two dimensional transition metal dichalcogenides (TMDC) have very interesting properties for optoelectronic devices. In this work we theoretically investigate and predict that superlattices comprised of MoS$_{2}$ and WSe$_{2}$ multilayers…

Two-dimensional (2D) transition metal dichalcogenides (TMDCs), exemplified by molybdenum disulfide (MoS2), have shown exceptional potential for data-centred, energy-efficient electronic applications due to their unique electrical,…

Efficient and accurate prediction of material properties is critical for advancing materials design and applications. The rapid-evolution of large language models (LLMs) presents a new opportunity for material property predictions,…

The research field of two dimensional (2D) materials strongly relies on optical microscopy characterization tools to identify atomically thin materials and to determine their number of layers. Moreover, optical microscopy-based techniques…

The ability to extract materials just a few atoms thick has led to discovery of graphene, monolayer transition metal dichalcogenides (TMDs), and other important two-dimensional materials. The next step in promoting understanding and utility…

The presence and evolution of defects that appear in the manufacturing process play a vital role in the failure mechanisms of engineering materials. In particular, the collective behavior of dislocation dynamics at the mesoscale leads to…

The understanding of various types of disorders in atomically thin transition metal dichalcogenides (TMDs), including dangling bonds at the edges, chalcogen deficiencies in the bulk, and charges in the substrate, is of fundamental…

Accelerated discovery with machine learning (ML) has begun to provide the advances in efficiency needed to overcome the combinatorial challenge of computational materials design. Nevertheless, ML-accelerated discovery both inherits the…

Transition metal dichalcogenides (TMDCs) have emerged as a new two dimensional materials field since the monolayer and few-layer limits show different properties when compared to each other and to their respective bulk materials. For…

Transition metal dichalcogenides (TMDs) are ideal systems for two-dimensional (2D) optoelectronic applications, owing to their strong light-matter interaction and various band gap energies. New techniques to modify the crystallographic…

Defects in two-dimensional transition metal dichalcogenides (TMDCs) broadly affect their optical and electronic properties. Directly capturing the ultrafast processes of exciton trapping and defect-bound exciton formation is crucial for…