相关论文: Self-learning analytical interatomic potential des…
New refractory alloys are being continuously designed and characterised for applications requiring good high-temperature mechanical properties and stability. Computational design from atomistic simulations is limited by interatomic…
At low temperatures, dynamics in amorphous silicon occurs through a sequence of discrete activated events that locally reorganize the topological network. Using the activation-relaxation technique, a data base containing over 8000 such…
Understanding the non-equilibrium behavior of stainless steel under extreme electronic excitation remains a critical challenge for laser processing and radiation science. We employ a hybrid framework integrating density-functional tight…
When atoms or molecules are exposed to strong short-pulse infrared radiation, ionization as well as "frustrated tunneling ionization" (FTI) can occur, in which a portion of the almost ionized electrons recombine into the initial ground or…
We have developed a thorough and accurate method of determining anharmonic free energies, the temperature dependent effective potential technique (TDEP). It is based on \emph{ab initio} molecular dynamics followed by a mapping onto a model…
Analysis of lithiation and delithiation kinetics in pulse-laser-deposited crystalline thin-film silicon (Si) electrodes is presented. Data from open-circuit relaxation experiments are used in conjunction with a model based on Tafel kinetics…
Preparing realistic atom-scale models of amorphous silicon (a-Si) is a decades-old condensed matter physics challenge. Herein, we combine the Activation Relaxation Technique nouveau (ARTn) to a Moment Tensor Potential (MTP) to generate…
Nanoparticles (NPs) formed in nonthermal plasmas (NTPs) can have unique properties and applications. However, modeling their growth in these environments presents significant challenges due to the non-equilibrium nature of NTPs, making them…
Analytic potentials are built for all four $^{2S+1}\Pi_{u/g}$ states of Li$_{2}$ dissociating to Li$(2S)$ + Li$(3P)$: $3b(3^{3}\Pi_{u})$, $3B(3^{1}\Pi_{u})$, $3C(3^{1}\Pi_{g}),$ and $3d(3^{3}\Pi_{g})$. These potentials include the effect of…
We introduce a force following active learning algorithm that integrates density functional theory DFT with the Gaussian Approximation Potential GAP framework to develop a robust interatomic potential IP for a dislocation in a topological…
We develop and compare four interatomic potentials for iron: a simple machine-learned embedded atom method (EAM) potential, a potential with machine-learned two- and three-body-dependent terms, a potential with machine-learned EAM and…
The introduction of machine learned potentials (MLPs) has greatly expanded the space available for studying Nuclear Quantum Effects computationally with ab initio path integral (PI) accuracy, with the MLPs' promise of an accuracy comparable…
Thin films of superconducting V$_3$Si were prepared by means of RF sputtering from a compound V$_3$Si target at room temperature onto sapphire and oxide-coated silicon wafers, followed by rapid thermal processing under secondary vacuum. The…
Accurate modeling of heat flux in inertial confinement fusion plasmas requires closures that remain predictive far from local equilibrium and across disparate spatial and temporal resolutions. We develop a resolution-independent…
In computational materials science, a common means for predicting macroscopic (e.g., mechanical) properties of an alloy is to define a model using combinations of descriptors that depend on some material properties (elastic constants,…
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…
Memristors have been intensively studied in recent years as promising building blocks for next-generation non-volatile memory, artificial neural networks and brain-inspired computing systems. Even though the environment adaptability of…
Interatomic potentials (IPs) are reduced-order models for calculating the potential energy of a system of atoms given their positions in space and species. IPs treat atoms as classical particles without explicitly modeling electrons and…
A potential experimental system, based on the Silicon Nitride (SiN) material, is proposed to generate steady-state room-temperature optomechanical entanglement. In the proposed structure, the nanostring interacts dispersively and reactively…
The intermetallic FeSi exhibits an unusual temperature dependence in its electronic and magnetic degrees of freedom, epitomized by the crossover from a low temperature non-magnetic semiconductor to a high temperature paramagnetic metal with…