Related papers: SiC-TGAP: A machine learning interatomic potential…
The noble elements constitute the simplest group of atoms. At low temperatures or high pressures they freeze into the face-centered cubic (fcc) crystal structure (except helium). We perform molecular dynamics using the recently proposed…
The silicon-hydrogen system is of key interest for solar-cell devices, including both crystalline and amorphous modifications. Elemental amorphous Si is now well understood, but the atomic-scale effects of hydrogenating the silicon matrix…
The design of efficient electrolysis devices for pure metal production requires accurate data on the properties of the melts used in the process. This work focuses on two key systems for calcium production: the molten Ca-Cu alloy and the…
Amorphous silicon (a-Si) is an important thermal-management material and also serves as an ideal playground for studying heat transport in strongly disordered materials. Theoretical prediction of the thermal conductivity of a-Si in a wide…
Device simulation plays a crucial role in complementing experimental device characterisation by enabling deeper understanding of internal physical processes. However, for simulations to be trusted, experimental validation is essential to…
Uranium monocarbide (UC) is an advanced ceramic fuel candidate due to its superior uranium density and thermal conductivity compared to traditional fuels. To accurately model UC at reactor operating conditions, we developed a machine…
Nanoporous carbon has been extensively used in a wide range of applications ranging from water treatment to electrochemical applications, such as in energy storage devices. An effort to relate structural to thermodynamical properties has…
Polymer-derived ceramics combine the thermal stability of ceramics with the versatile properties of carbon domains, but modeling their atomic-scale evolution during processing remains elusive due to the limitations of traditional…
Molten salts are promising candidates in numerous clean energy applications, where challenges in experimental methods limit knowledge of their safety-critical temperature-properties correlations. Herein, we developed and employed machine…
Silicon carbide (SiC) is the leading wide-bandgap semiconductor material, providing mature doping and device fabrication. Additionally, SiC hosts a multitude of optically active point defects (color centers) and is relevant for many…
The number of published Machine Learning Interatomic Potentials (MLIPs) has increased significantly in recent years. These new data-driven potential energy approximations often lack the physics-based foundations that inform many…
In the research of condensed matter, atomistic dynamic simulations play a crucial role, particularly in revealing dynamic processes, phase transitions and thermodynamic statistics macroscopic physical properties in systems such as solids…
Thermal decomposition of silicon carbide is a promising approach for the fabrication of graphene. However, the atomistic growth mechanism of graphene remains unclear. This paper describes the development of a new charge-transfer interatomic…
Accurate target parameter estimation of range, velocity, and angle is essential for vehicle safety in advanced driver assistance systems (ADAS) and autonomous vehicles. To enable spectrum sharing, ADAS may employ integrated sensing and…
Machine-learned interatomic potentials can offer near first-principles accuracy but are computationally expensive, limiting their application to large-scale molecular dynamics simulations. Inspired by quantum mechanics/molecular mechanics…
Gallium oxide (Ga2O3) is a wide-bandgap semiconductor with promising applications in high-power and high-frequency electronics. However, its complex polymorphic nature poses substantial challenges for fundamental studies, particularly in…
Silicon dioxide is a suitable material to encapsulate proteins at room temperature so that they can be analysed at the atomic level using laser-assisted atom probe tomography (La-APT). To achieve this goal, in this study we show that UV and…
The highly anisotropic thermal conductivity in layered materials is crucial for a broad range of applications such as thermal management of electronic devices, thermal insulation, and thermoelectrics. Understanding of anisotropic thermal…
In ion cancer therapy, high-intensity ion beams are used to treat tumors by taking advantage of the Bragg-Peak. Typical ion therapy centers use particle rates up to $10^{10}$ ions/second for treatment. On the other hand, such intensities…
Predicting the superconducting transition temperature ($T_c$) from crystal structure and composition remains a central challenge in condensed-matter physics, reflecting the absence of a broadly predictive framework connecting microscopic…