Related papers: Modelling Silica using MACE-MP-0 Machine Learnt In…
Over the past decade inter-atomic potentials based on machine-learning (ML) techniques have become an indispensable tool in the atomic-scale modeling of materials. Trained on energies and forces obtained from electronic-structure…
We evaluate the phase diagram of the ``BKS'' potential [Van Beest, Kramer and van Santen, Phys. Rev. Lett. 64, 1955 (1990)], a model of silica widely used in molecular dynamics (MD) simulations. We conduct MD simulations of the liquid, and…
Serpentines are layered hydrous magnesium silicates (MgO$\cdot$SiO$_2\cdot$H$_2$O) formed through serpentinization, a geochemical process that significantly alters the physical property of the mantle. They are hard to investigate…
Accurately modeling the structural reconstruction and thermodynamic behavior of van der Waals (vdW) heterostructures remains a significant challenge due to the limitations of conventional force fields in capturing their complex mechanical,…
Zeolites are inorganic materials known for their diversity of applications, synthesis conditions, and resulting polymorphs. Although their synthesis is controlled both by inorganic and organic synthesis conditions, computational studies of…
Accurate prediction of surface energies and stabilities is essential for materials design, yet first-principles calculations remain computationally expensive and most existing interatomic potentials are trained only on bulk systems. Here,…
High-Temperature Superconductors (HTS) such as YBa2Cu3O7-delta (YBCO) are essential for next-generation Tokamak fusion reactors, where Rare-Earth Barium Copper Oxides (REBCO) form the functional layers in HTS magnets. Because YBCO's…
The structural and dynamical properties of four silicate liquids (silica, rhyolite, a model basalt and enstatite) are evaluated by ab initio molecular dynamics simulation using the density functional theory and are compared with classical…
\textit{In situ} high-pressure Brillouin light scattering experiments along loading-unloading paths are used to investigate the compressibility of vitreous silica. An accurate equation of state is obtained below \SI{9}{GPa} using sound…
Machine-Learned Interatomic Potentials (MLIPs) require vast amounts of atomic structure data to learn forces and energies, and their performance continues to improve with training set size. Meanwhile, the even greater quantities of…
In this paper we test two strategies to improving the accuracy of machine-learning potentials, namely adding more fitting parameters thus making use of large volumes of available quantum-mechanical data, and adding a charge-equilibration…
Prevailing machine-learned interatomic potential (MLIP) uncertainty-quantification methods rely on ensembles of independently trained backbones. These methods scale unfavorably with foundation-scale MLIPs, and their member-disagreement…
Machine-learning interatomic potentials (MLIPs) offer a powerful avenue for simulations beyond length and timescales of ab initio methods. Their development for investigation of mechanical properties and fracture, however, is far from…
Room temperature ionic liquids (ILs) at solid surfaces have been recognized for their significant interfacial properties in electrochemical and electronic devices. To ascertain the interface effects, we investigate dynamical and structural…
We present a study on the transport and materials properties of aluminum spanning from ambient to warm dense matter conditions using a machine-learned interatomic potential (ML-IAP). Prior research has utilized ML-IAPs to simulate phenomena…
Calculating sublimation enthalpies of molecular crystal polymorphs is relevant to a wide range of technological applications. However, predicting these quantities at first-principles accuracy -- even with the aid of machine learning…
Experimental microstylolites have been observed at stressed contacts between quartz grains loaded for several weeks in the presence of an aqueous silica solution, at 350 8C and 50 MPa of differential stress. Stereoscopic analysis of pairs…
Using molecular dynamics simulations we study the thermodynamic behavior of a single-component covalent material described by the recently proposed Environment-Dependent Interatomic Potential (EDIP). The parameterization of EDIP for silicon…
Accounting for nuclear quantum effects (NQEs) can significantly alter material properties at finite temperatures. Atomic modeling using the path-integral molecular dynamics (PIMD) method can fully account for such effects, but requires…
Glass formation in Zeolitic Imidazolate Frameworks (ZIFs) has garnered significant attention in the field of Metal-Organic Frameworks (MOFs) in recent years. Numerous works have been conducted to investigate the microscopic mechanisms…