Related papers: Multi-Hill Strategy in Metadynamics for Interstiti…
We propose two metadynamics (MetaD)-based methodologies for efficiently mapping free energy surfaces (FESs) of multiple interacting carriers diffusing in crystalline solids. Our approaches circumvent the challenges of high-dimensional…
We propose a metadynamics-based (MetaD-based) approach for constructing the free energy surface (FES) of vacancy dynamics in crystals. In this approach, the vacancy FES can be constructed without explicitly defining a unique vacancy…
A known issue for future nuclear reactors is helium accumulation inside the steel structure materials, responsible for structural issues such as embrittlement and cracking. One possible solution is using new types of reinforced steel, such…
The step motions considered are those in which crystallization is controlled by a single diffusion process, either the substance diffusion for growth from solution or the flow of latent heat from the step for growth from melt. Quasi-static…
We propose the powerful integration of the Hybrid Monte Carlo (hybridMC) algorithm and Well-Tempered Metadynamics. This new algorithm, hybridMC-MetaD, enhances the flexibility and applicability of metadynamics by allowing for the…
In recent years, diffusion-based models have demonstrated exceptional performance in searching for simultaneously stable, unique, and novel (S.U.N.) crystalline materials. However, most of these models don't have the ability to change the…
Metadynamics, a member of the `flat histogram' class of advanced sampling algorithms, has been widely used in molecular simulations to drive the exploration of states separated by high free energy barriers and promote comprehensive sampling…
Polymorphs in molecular crystals are often very close in energy, yet they may possess markedly different physical and chemical properties. The understanding and prediction of polymorphism is of paramount importance for a variety of…
We calibrate a (3+1)-dimensional multistage hybrid framework using the measured pseudo-rapidity distribution of charged particles and rapidity distribution of net protons for central Au+Au collisions at $\sqrt{s_{\rm…
Metadynamics (MTD) is a very powerful technique to sample high-dimensional free energy landscapes, and due to its self-guiding property, the method has been successful in studying complex reactions and conformational changes. MTD sampling…
Metastable condensed matter typically fluctuates about local energy minima at the femtosecond time scale before transitioning between local minima after nanoseconds or microseconds. This vast scale separation limits the applicability of…
We propose a hybrid deterministic and stochastic approach to achieve extended time scales in atomistic simulations that combines the strengths of molecular dynamics (MD) and Monte Carlo (MC) simulations in an easy-to-implement way. The…
We investigate the effect of metastable gas-liquid (G-L) separation on crystal growth in a system of either monodisperse or slightly size-polydisperse square well particles, using a simulation setup that allows us to focus on the growth of…
Diffusion in coulomb crystals can be important for the structure of neutron star crusts. We determine diffusion constants $D$ from molecular dynamics simulations. We find that $D$ for coulomb crystals with relatively soft-core $1/r$…
We reveal the microscopic self-diffusion process of compact tri-interstitials in silicon using a combination of molecular dynamics and nudged elastic band methods. We find that the compact tri-interstitial moves by a collective…
A diffuse-interface model for microstructure with an arbitrary number of components and phases was developed from basic thermodynamic and kinetic principles and formalized within a variational framework. The model includes a composition…
Generative modeling of crystalline materials using diffusion models presents a series of challenges: the data distribution is characterized by inherent symmetries and involves multiple modalities, with some defined on specific manifolds.…
Classical Molecular Dynamics (MD) simulations are employed as a tool to investigate structural properties of ice crystals under several temperature and pressure conditions. All ice crystal phases are analyzed by means of a computational…
Crystal Structure Prediction (CSP) is crucial in various scientific disciplines. While CSP can be addressed by employing currently-prevailing generative models (e.g. diffusion models), this task encounters unique challenges owing to the…
We propose a machine-learning-based (ML-based) method for efficiently predicting atomic diffusivity in crystals, in which the potential energy surface (PES) of a diffusion carrier is partially evaluated by first-principles calculations. To…