Related papers: Spin Neural Network Potential for Magnetic Phase T…

We report the mechanisms of atomic ordering in Fe$_{1-x}$Pt$_{x}$ alloys using density functional theory (DFT) and machine-learning interatomic potential Monte Carlo (MLIP-MC) simulations. We clarified that the formation enthalpy of the…

From the study of long-range-interacting systems to the simulation of gauge fields, open-shell Lanthanide atoms with their large magnetic moment and narrow optical transitions open novel directions in the field of ultracold quantum gases.…

We apply Density Functional Theory (DFT) and the DFT+U technique to study the adsorption of transition metal porphine molecules on atomistically flat Au(111) surfaces. DFT calculations using the Perdew-Burke-Ernzerhof (PBE) exchange…

Material characterization in nano-mechanical tests requires precise interatomic potentials for the computation of atomic energies and forces with near-quantum accuracy. For such purposes, we develop a robust neural-network interatomic…

Reactive force fields for molecular dynamics have enabled a wide range of studies in numerous material classes. These force fields are computationally inexpensive as compared to electronic structure calculations and allow for simulations of…

Universal machine-learning interatomic potentials (uMLIPs) enable reactive molecular simulations with near-DFT accuracy, yet applying them efficiently to large, realistic condensed-phase systems remains computationally demanding. Here we…

We demonstrate the real-time detection of dynamical phase transitions (DPTs) in lattice-confined spinor gases subject to a priori unknown time-variant interactions, via the temporal behaviors of both the system energy and spinor phases…

Information can be stored in magnetic materials by encoding with the direction of the magnetic moment of elements. A figure of merit for these systems is the energy needed to change the information rewrite the storage by changing the…

We analyze possible ways to calculate magnetic exchange interactions within the density functional theory plus dynamical mean-field theory (DFT+DMFT) approach in the paramagnetic phase. Using the susceptibilities obtained within the ladder…

Spin waves, or magnons, in the anti-ferromagnetic $\alpha$ phase of solid oxygen provide a novel mechanism for ultra-cold neutron (UCN) production. Magnons dominate the energy exchange mechanisms for cold neutrons and UCN in solid…

Studying the physical properties of materials under high pressure and temperature through experiments is difficult. Theoretical simulations can compensate for this deficiency. Currently, large-scale simulations using machine learning force…

Density functional theory (DFT) is one of the main methods in Quantum Chemistry that offers an attractive trade off between the cost and accuracy of quantum chemical computations. The electron density plays a key role in DFT. In this work,…

Large-scale simulations of plastic deformation and phase transformations in alloys require reliable classical interatomic potentials. We construct an embedded-atom method potential for niobium as the first step in alloy potential…

This study introduces time-reversal E(3)-equivariant neural network and SpinGNN++ framework for constructing a comprehensive interatomic potential for magnetic systems, encompassing spin-orbit coupling and noncollinear magnetic moments.…

Optical dynamic nuclear polarization (DNP) offers an attractive approach to enhancing the sensitivity of nuclear magnetic resonance (NMR) spectroscopy. Efficient, optically-generated electron polarization can be leveraged to operate across…

A DFT-based method is presented which allows the computation of all-electron NMR shifts of metallic compounds with periodic boundary conditions. NMR shifts in metals measure two competing physical phenomena. Electrons interact with the…

We report comprehensive inelastic neutron scattering measurements of the magnetic excitations in the 2D spin-5/2 Heisenberg antiferromagnet Rb2MnF4 as a function of temperature from deep in the Neel ordered phase up to paramagnetic, 0.13 <…

In search of the ferromagnetic insulators for spintronic device applications, we have studied the electronic, optical, and magnetic properties ofLa2CrNiO6(LCNO) using the first principle density functional theory (DFT)and monte carlo…

Though offering unprecedented pathways to molecular dynamics (MD) simulations of technologically-relevant materials and conditions, machine-learning interatomic potentials (MLIPs) are typically trained for ``simple'' materials and…

Large-scale computations of fission properties are an important ingredient for nuclear reaction network calculations simulating rapid neutron-capture process (the r process) nucleosynthesis. Due to the large number of fissioning nuclei…