Related papers: Models for adatom diffusion on fcc(001) metal surf…
We have performed a density functional study of fifteen different structural models of the Si(557)-Au surface reconstruction. Here we present a brief summary of the main structural trends obtained for the more favourable models, focusing…
Diffraction patterns produced by grazing scattering of fast atoms from insulator surfaces are used to examine the atom-surface interaction. The method is applied to He atoms colliding with a LiF(001) surface along axial crystallographic…
Diffusion models are a powerful tool for probabilistic forecasting, yet most applications in high-dimensional complex systems predict future states individually. This approach struggles to model complex temporal dependencies and fails to…
We present Monte Carlo simulations for the size and temperature dependence of the diffusion coefficient of adatom islands on the Cu(100) surface. We show that the scaling exponent for the size dependence is not a constant but a decreasing…
This work presents a finite element method for simulating dynamic processes that involve the coupled evolution of dislocation motion and crack propagation. The method numerically solves the Concurrent Atomistic-Continuum (CAC) formulation…
The diffusion of two dimensional adatom islands (up to 100 atoms) on Cu(111) has been studied, using the self-learning Kinetic Monte Carlo (SLKMC) method [1]. A variety of multiple- and single-atom processes are revealed in the simulations,…
This work presents a novel three-dimensional Crack Element Method (CEM) designed to model transient dynamic crack propagation in quasi-brittle materials efficiently. CEM introduces an advanced element-splitting algorithm that enables…
Hydrogen embrittlement in metals is strongly governed by hydrogen diffusion and trapping, yet predicting these effects in polycrystalline systems remains challenging. This work introduces a multiscale modeling framework that links atomistic…
Recent advances in machine learning have opened new avenues for optimizing detector designs in high-energy physics, where the complex interplay of geometry, materials, and physics processes has traditionally posed a significant challenge.…
The continuous need towards improving the capacity of magnetic storage devices requires materials with strong perpendicular magnetic anisotropy. FePd, CoPd and their Co(Fe)Pt counterparts very attractive candidate for such purposes. The…
While the diffusion of hydrogen on silicon surfaces has been relatively well characterised both experimentally and theoretically, the diffusion around corners between surfaces, as will be found on nanowires and nanostructures, has not been…
Protein design with desirable properties has been a significant challenge for many decades. Generative artificial intelligence is a promising approach and has achieved great success in various protein generation tasks. Notably, diffusion…
With the development of artificial intelligence (AI) techniques, implementing AI-based techniques to improve wireless transceivers becomes an emerging research topic. Within this context, AI-based channel characterization and estimation…
Accurate description of nonadiabatic dynamics of molecules at metal surfaces involving electron transfer has been a longstanding challenge for theory. Here, we tackle this problem by first constructing high-dimensional neural network…
Cosmic ray nuclei fluxes are expected to be measured with high precision in the near future. For instance, high quality data on the antiproton component could give important clues about the nature of the astronomical dark matter. A very…
While it is known that alloy components can segregate to grain boundaries (GBs), and that the atomic mobility in GBs greatly exceeds the atomic mobility in the lattice, little is known about the effect of GB segregation on GB diffusion.…
We present and discuss the results of ab initio DFT plane-wave supercell calculations of the atomic and molecular oxygen adsorption and diffusion on the LaMnO3 (001) surface which serves as a model material for a cathode of solid oxide fuel…
Diffusion models (DMs) have been adopted across diverse fields with its remarkable abilities in capturing intricate data distributions. In this paper, we propose a Fast Diffusion Model (FDM) to significantly speed up DMs from a stochastic…
Turbulent, relativistic nonthermal plasmas are ubiquitous in high-energy astrophysical systems, as inferred from broadband nonthermal emission spectra. The underlying turbulent nonthermal particle acceleration (NTPA) processes have…
The ability to rapidly develop materials with desired properties has a transformative impact on a broad range of emerging technologies. In this work, we introduce a new framework based on the diffusion model, a recent generative machine…