Related papers: Neural-network-enabled molecular dynamics study of…
The temperature-induced structural and electronic transformation in VO$_2$ between the monoclinic M1 and tetragonal rutile phases was studied by means of \textit{ab initio} molecular dynamics, based on density functional theory with Hubbard…
Over the last decade, an increasing body of evidence has emerged, supporting the existence of a metastable liquid-liquid critical point in supercooled water, whereby two distinct liquid phases of different densities coexist. Analysing long…
We survey the phase diagram of high-pressure molecular hydrogen with path integral molecular dynamics using a machine-learned interatomic potential trained with Quantum Monte Carlo forces and energies. Besides the HCP and C2/c-24 phases, we…
We consider the rate of transition for a particle between two metastable states coupled to a thermal environment for various magnitudes of the coupling strength, using the recently proposed infrequent metadynamics approach (Tiwary and…
We present a machine learning framework to train and validate neural networks to predict the anisotropic elastic response of the monoclinic organic molecular crystal $\beta$-HMX in the geometrical nonlinear regime. A filtered molecular…
The glass transition of supercooled fluids is a particular challenge for computer simulation, because the (longest) relaxation times increase by about 15 decades upon approaching the transition temperature T_g. Brute-force molecular…
Motivated by recent experiments, the isotropic-nematic phase transition in chromonic liquid crystals is studied. As temperature decreases, nematic nuclei nucleate, grow, and coalesce, giving rise to tactoid microstructures in an isotropic…
We quantitatively characterize the metastability in a multi-phase lattice Boltzmann model. The structure factor of density fluctuations is theoretically obtained and numerically verified to a high precision, for all simulated wave-vectors…
Perovskite oxides are known to exhibit many magnetic, electronic and structural phases as function of doping and temperature. These materials are theoretically frequently investigated by the DFT+U method, typically in their ground state…
The high-pressure behavior of monoclinic VO$_2$ is revisited by a combination of Raman spectroscopy and X-ray diffraction on a single crystal under hydrostatic conditions at room temperature. A soft mode is observed up to P$_c$ = 13.9(1)…
Machine learning techniques such as artificial neural networks are currently revolutionizing many technological areas and have also proven successful in quantum physics applications. Here we employ an artificial neural network and deep…
Since the first report of ferroelectricity in nanoscale HfO$_2$-based thin films in 2011, this silicon-compatible binary oxide has quickly garnered intense interest in academia and industry, and continues to do so. Despite its deceivingly…
We report the results of molecular dynamics (MD) simulations of a complete monolayer of hexane physisorbed onto the basal plane of graphite. At low temperatures the system forms a herringbone solid. With increasing temperature, a solid to…
Classical empirical force fields have dominated biomolecular simulation for over 50 years. Although widely used in drug discovery, crystal structure prediction, and biomolecular dynamics, they generally lack the accuracy and transferability…
In this work, we have carried out molecular dynamics (MD) simulation techniques to study the diffusion coefficient of interlayer molecules at different temperature. Within the wider context of water dynamics in soils, and with a particular…
We used high-resolution quasielastic neutron scattering spectroscopy to study the single-particle dynamics of water molecules on the surface of hydrated DNA samples. Both H2O and D2O hydrated samples were measured. The contribution of…
Neutron powder diffraction studies of the crystal and magnetic structures of the magnetocaloric compound Mn1.1Fe0.9(P0.8Ge0.2) have been carried out as a function of temperature, applied magnetic field, and pressure. The data reveal that…
The recent discovery of a connection between Transformers and Modern Hopfield Networks (MHNs) has reignited the study of neural networks from a physical energy-based perspective. This paper focuses on the pivotal effect of the inverse…
We studied the isotropic Compton profile of the prototypical oxide VO$_2$ across the temperature induced electronic and structural phase transition at T$_C$ $\approx$ 340 K. We show that the phase transition leaves an observable signal,…
Realistic finite temperature simulations of matter are a formidable challenge for first principles methods. Long simulation times and large length scales are required, demanding years of compute time. Here we present an on-the-fly machine…