相关论文: Machine Learned Interatomic Potential for Dispersi…
Determining thermal and physical quantities across a broad temperature domain, especially up to the ultra-high temperature region, is a formidable theoretical and experimental challenge. At the same time it is essential for understanding…
Tungsten carbide (WC) stands out as a crucial material for exploration in extreme environments due to its resistance to radiation and impressive mechanical strength. Widely utilized in cutting tools, high-wear components, and as a potential…
We report a molecular dynamics simulation of melting of tungsten (W) nanoparticles. The modified embedded atom method (MEAM) interatomic potentials are used to describe the interaction between tungsten atoms. The melting temperature of…
We investigate the effects of W incorporation into Cu-Zr thin film metallic glasses using molecular dynamics (MD) simulations combined with magnetron sputtering. All studies are carried out in the whole range of W concentrations (0 to 100…
Tungsten-copper (W-Cu) compounds are widely utilized in various industrial fields due to their exceptional mechanical properties. In this study, we have developed a neural-network-based deep potential (DP) model that covers a wide range of…
Machine Learning Interatomic Potentials (MLIPs) are a modern computational method that allows achieving near-quantum mechanical accuracy (DFT) while still describing large-scale systems in molecular dynamics (MD) simulations. In this work,…
Pulsed neutron diffraction investigations have been performed in the ferroelectric PZT system, Pb(Zr1-xTix)O3, doped with 1%wt. of Nb2O5, as a function of both temperature and composition. The study has been made in a wide range of…
The binary alloy of titanium-tungsten (TiW) is an established diffusion barrier in high-power semiconductor devices, owing to its ability to suppress the diffusion of copper from the metallisation scheme into the surrounding silicon…
Nanostructured tungsten has been reported as a possible alternative plasma-facing material due to its potential ability to self-heal radiation-induced defects, a property that is attributed to its high density of grain boundaries (GB).…
Retention of plasma-implanted D is studied in W targets damaged by a Cu ion beam at up to 0.2 dpa with sample temperatures between 300 K and 1200 K. At a D plasma ion fluence of $10^{24}/m^2$ on samples damaged to 0.2 dpa at 300 K, the…
Tungsten-based low-activation high-entropy alloys are possible candidates for next-generation fusion reactors due to their exceptional tolerance to irradiation, thermal loads, and stress. We develop an accurate and efficient machine-learned…
Tungsten is an important element for magnetically confined fusion plasmas but has the potential to cool, or even quench the plasma due to it being an efficient radiator. Total and level-resolved dielectronic recombination (DR) rate…
Materials used in commercial D-T fusion reactors will be exposed to irradiation and a mixture of helium and hydrogen plasma. Modeling the microstructural evolution of such materials requires the use of large-scale molecular dynamics…
Though offering unprecedented pathways to molecular dynamics (MD) simulations of technologically-relevant materials and conditions, machine-learning interatomic potentials (MLIPs) are typically trained for ``simple'' materials and…
Superconducting radio-frequency (SRF) resonators are critical components for particle accelerator applications, such as free-electron lasers, and for emerging technologies in quantum computing. Developing advanced materials and their…
The in plane coefficient of thermal expansion (CTE) and the residual stress of nanostructured W based coatings are extensively investigated. The CTE and the residual stresses are derived by means of an optimized ad-hoc developed…
Particle-producing targets in high-energy research facilities are often made from refractory metals, and they typically require dedicated cooling systems due to the challenging thermomechanical conditions they experience. However, direct…
The increasing demand for materials capable of withstanding high temperatures and harsh environments necessitates the discovery of advanced alloys. This study introduces a computational routine to predict solid-state phase stability and…
Computational modeling is usually applied to aid experimental exploration of advanced materials to better understand the fundamental plasticity mechanisms during mechanical testing. In this work, we perform Molecular dynamics (MD)…
The purpose of this short contribution is to report on the development of a Spectral Neighbor Analysis Potential (SNAP) for tungsten. We have focused on the characterization of elastic and defect properties of the pure material in order to…