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Fast Bayesian force fields from active learning: study of inter-dimensional t...
Gaussian process (GP) regression is one promising technique of constructing machine learning force fields with built-in uncertainty quantification, which can be used to monitor... -
Active learning of reactive Bayesian force fields applied to heterogeneous ca...
Atomistic modeling of chemically reactive systems has so far relied on either expensive ab initio methods or bond-order force fields requiring arduous parametrization. Here, we... -
Electronic structure of water from Koopmans-compliant functionals
Obtaining a precise theoretical description of the spectral properties of liquid water poses challenges for both molecular dynamics (MD) and electronic structure methods. The... -
Electronic structure of water from Koopmans-compliant functionals
Obtaining a precise theoretical description of the spectral properties of liquid water poses challenges for both molecular dynamics (MD) and electronic structure methods. The... -
Temperature Dependence of Homogeneous Nucleation in Ice
Ice nucleation is a process of great relevance in physics, chemistry, technology, and environmental sciences; much theoretical effort has been devoted to its understanding, but... -
Fast Bayesian force fields from active learning and mapped Gaussian processes...
Gaussian process (GP) regression is one promising technique of constructing machine learning force fields with built-in uncertainty quantification, which can be used to monitor... -
Dynamics of the Bulk Hydrated Electron from Many‐Body Wave‐Function Theory
Trajectories and spin densities for the bulk hydrated electron at the MP2 level of theory. The data represent the first ab initio molecular dynamics study of the hydrated... -
E(3)-equivariant graph neural networks for data-efficient and accurate intera...
This work presents Neural Equivariant Interatomic Potentials (NequIP), an E(3)-equivariant neural network approach for learning interatomic potentials from ab-initio... -
Hierarchical short- and medium-range order structures in amorphous Ge_x Se_1–...
In the upcoming process to overcome the limitations of the standard von Neumann architecture, synaptic electronics is gaining a primary role for the development of in-memory... -
Impact of glutamate carboxylation in the adsorption of the alpha-1 domain of ...
This record contains files necessary to reproduce enhanced sampling well-tempered metadynamics (wtMTD) and parallel tempering metadynamics in the well-tempered ensemble... -
Naphthalene crystal shape prediction from molecular dynamics simulations
We used molecular dynamics simulations to predict the steady state crystal shape of naphthalene grown from ethanol solution. The simulations were performed at constant... -
A transferable force field for gallium nitride crystal growth from the melt u...
Atomic-scale simulations of reactive processes have been stymied by two factors: the general lack of a suitable semi-empirical force field on the one hand, and the impractically... -
Graph Dynamical Networks for Unsupervised Learning of Atomic Scale Dynamics i...
Understanding the dynamical processes that govern the performance of functional materials is essential for the design of next generation materials to tackle global energy and... -
Raman spectra of 2D titanium carbide MXene from machine-learning force field ...
MXenes represent one of the largest class of 2D materials with promising applications in many fields and their properties tunable by the surface group composition. Raman... -
Probing temperature responsivity of microgels and its interplay with a solid ...
Super-resolution microscopy has become a powerful tool to investigate the internal structure of complex colloidal and polymeric systems, such as microgels, at the nanometer... -
Accurate and scalable multi-element graph neural network force field and mole...
Data includes the the ab initio molecular dynamic simulation of Li7P3S11 that was used to measure the performance of the GNNFF. The data is divided into training and testing... -
Global free-energy landscapes as a smoothly joined collection of local maps
This repository contains the scripts that were used to run the calculations that present a new biasing technique, the Adaptive Topography of Landscape for Accelerated Sampling...