相关论文: Machine-Learning Enabled Search for The Next-Gener…
Two-dimensional (2D) materials and their heterostructures, with wafer-scale synthesis methods and fascinating properties, have attracted numerous interest and triggered revolutions of corresponding device applications. However, facile…
Potential Energy Surfaces (PESs) are an indispensable tool to investigate, characterise and understand chemical and biological systems in the gas and condensed phases. Advances in Machine Learning (ML) methodologies have led to the…
Two-dimensional (2D) layered nanomaterials heterostructures, arising from the combination of 2D materials with other low-dimensional species, feature large surface area to volume ratio, which provides a high density of active sites for…
Hydrothermal carbonization (HTC) is a process that converts biomass into versatile hydrochar without the need for prior drying. The physicochemical properties of hydrochar are influenced by biomass properties and processing parameters,…
Low-dimensional transition metal dichalcogenides (TMDC) exhibit great photocatalytic performance and tunability. In this work, using first-principles simulations based on density functional theory (DFT), we demonstrate that external…
Ultrathin layers of semiconducting molybdenum disulfide (MoS2) offer significant prospects in future electronic and optoelectronic applications. Although an increasing number of experiments bring light into the electronic transport…
We set up an evolutionary algorithm combined with density functional tight-binding (DFTB) calculations to investigate hydrogen adsorption on flat graphene and graphene monolayers curved over substrate steps. During the evolution, candidates…
One important use of layered semiconductors such as molybdenum disulfide (MoS2) could be in making novel heterojunction devices leading to functionalities unachievable using conventional semiconductors. Here we demonstrate an ultrafast…
Refractory high-entropy alloys (RHEAs) are a promising class of alloys that show elevated-temperature yield strengths and have potential to use as high-performance materials in gas turbine engines. However, exploring the vast RHEA…
In molecular simulations, machine-learning force fields can achieve ab initio accuracy at a lower cost but remain limited in the explicit modeling of electrons. In this work, we develop an electron-aware machine-learning force field, in…
We present helium atom micro-diffraction as an ideal technique for characterization of 2D materials due to its ultimate surface sensitivity combined with sub-micron spatial resolution. Thermal energy neutral helium scatters from the valence…
Microstructure--property relationships are key to effective design of structural materials for advanced applications. Advances in computational methods enabled modeling microstructure-sensitive properties using 3D models (e.g., finite…
The optimization of the electrode manufacturing process is important for upscaling the application of Lithium Ion Batteries (LIBs) to cater for growing energy demand. In particular, LIB manufacturing is very important to be optimized…
To address the urgent challenge of climate change, there is a critical need to transition away from fossil fuels towards sustainable energy systems, with renewable energy sources playing a pivotal role. However, the inherent variability of…
Porous single layer molybdenum disulfide (MoS$_2$) is a promising material for applications such as DNA sequencing and water desalination. In this work, we introduce irradiation with highly charged ions (HCIs) as a new technique to…
The design of high-entropy alloys (HEA) with desired properties is challenging due to their large compositional space. While various machine learning (ML) models can predict specific HEA solid-solution phases (SS), predicting high-entropy…
The conversion of $\mathrm{CO_2}$ into useful products such as methanol is a key strategy for abating climate change and our dependence on fossil fuels. Developing new catalysts for this process is costly and time-consuming and can thus…
The energetics of hydrogen absorption in C15 cubic and C14 hexagonal TiCr$_2$H$_x$ Laves phases is investigated for $0 < x \le 6$ with density functional theory (DFT) and machine learning interatomic potentials (MLIPs). The MLIPs are…
The potential application of the single-layer MoS2 as photocatalyst was revealed in this work based on first-principles calculations. It is found that the pristine single-layer MoS2 is a good candidate for photocatalyst, and its catalyzing…
The environmental impacts of global warming driven by methane (CH4) emissions have catalyzed significant research initiatives in developing novel technologies that enable proactive and rapid detection of CH4. Several data-driven machine…