Induction and Ferroelectric Switching of Flux Closure Domains in Strained PbTiO with Neural Network Quantum Molecular Dynamics.

We have developed an extension of the Neural Network Quantum Molecular Dynamics (NNQMD) simulation method to incorporate electric-field dynamics based on Born effective charge (BEC), called NNQMD-BEC. We first validate NNQMD-BEC for the switching mechanisms of archetypal ferroelectric PbTiO bulk crystal and 180° domain walls (DWs). NNQMD-BEC simulations correctly describe the nucleation-and-growth mechanism during DW switching.

Squishing Skyrmions: Symmetry-Guided Dynamic Transformation of Polar Topologies Under Compression.

Mechanical controllability of recently discovered topological defects (., skyrmions) in ferroelectric materials is of interest for the development of ultralow-power mechano-electronics that are protected against thermal noise. However, fundamental understanding is hindered by the "multiscale quantum challenge" to describe topological switching encompassing large spatiotemporal scales with quantum mechanical accuracy.

Defect-free and crystallinity-preserving ductile deformation in semiconducting AgS.

Typical ductile materials are metals, which deform by the motion of defects like dislocations in association with non-directional metallic bonds. Unfortunately, this textbook mechanism does not operate in most inorganic semiconductors at ambient temperature, thus severely limiting the development of much-needed flexible electronic devices. We found a shear-deformation mechanism in a recently discovered ductile semiconductor, monoclinic-silver sulfide (AgS), which is defect-free, omni-directional, and preserving perfect crystallinity.

Hydrogen Bonding in Liquid Ammonia.

The nature of hydrogen bonding in condensed ammonia phases, liquid and crystalline ammonia has been a topic of much investigation. Here, we use quantum molecular dynamics simulations to investigate hydrogen bond structure and lifetimes in two ammonia phases: liquid ammonia and crystalline ammonia-I. Unlike liquid water, which has two covalently bonded hydrogen and two hydrogen bonds per oxygen atom, each nitrogen atom in liquid ammonia is found to have only one hydrogen bond at 2.

Improvement of the Force Field for -d-Glucose with Machine Learning.

While the construction of a dependable force field for performing classical molecular dynamics (MD) simulation is crucial for elucidating the structure and function of biomolecular systems, the attempts to do this for glycans are relatively sparse compared to those for proteins and nucleic acids. Currently, the use of GLYCAM06 force field is the most popular, but there have been a number of concerns about its accuracy in the systematic description of structural changes. In the present work, we focus on the improvement of the GLYCAM06 force field for β-d-glucose, a simple and the most abundant monosaccharide molecule, with the aid of machine learning techniques implemented with the TensorFlow library.

Neural Network Quantum Molecular Dynamics, Intermediate Range Order in GeSe, and Neutron Scattering Experiments.

A remarkable property of certain covalent glasses and their melts is intermediate range order, manifested as the first sharp diffraction peak (FSDP) in neutron-scattering experiments, as was exhaustively investigated by Price, Saboungi, and collaborators. Atomistic simulations thus far have relied on either quantum molecular dynamics (QMD), with systems too small to resolve FSDP, or classical molecular dynamics, without quantum-mechanical accuracy. We investigate prototypical FSDP in GeSe glass and melt using neural-network quantum molecular dynamics (NNQMD) based on machine learning, which allows large simulation sizes with validated quantum mechanical accuracy to make quantitative comparisons with neutron data.

Dielectric Constant of Liquid Water Determined with Neural Network Quantum Molecular Dynamics.

The static dielectric constant ϵ_{0} and its temperature dependence for liquid water is investigated using neural network quantum molecular dynamics (NNQMD). We compute the exact dielectric constant in canonical ensemble from NNQMD trajectories using fluctuations in macroscopic polarization computed from maximally localized Wannier functions (MLWF). Two deep neural networks are constructed.

Computational and training requirements for interatomic potential based on artificial neural network for estimating low thermal conductivity of silver chalcogenides.

We examined the estimation of thermal conductivity through molecular dynamics simulations for a superionic conductor, α-AgSe, using the interatomic potential based on an artificial neural network (ANN potential). The training data were created using the existing empirical potential of AgSe to help find suitable computational and training requirements for the ANN potential, with the intent to apply them to first-principles calculations. The thermal conductivities calculated using different definitions of heat flux were compared, and the effect of explicit long-range Coulomb interaction on the conductivities was investigated.

Temperature relaxation in binary hard-sphere mixture system: Molecular dynamics and kinetic theory study.

Computational schemes to describe the temperature relaxation in the binary hard-sphere mixture system are given on the basis of molecular dynamics (MD) simulation and renormalized kinetic theory. Event-driven MD simulations are carried out for three model systems in which the initial temperatures and the ratios of diameter and mass of two components are different to study the temporal evolution of each component temperature in nanoscale molecular conditions mimicking those in living cells. On the other hand, the temperature changes of the two components are also described in terms of a mean-field kinetic theory with the correlation functions calculated in the Percus-Yevick approximation.

Application of First-Principles-Based Artificial Neural Network Potentials to Multiscale-Shock Dynamics Simulations on Solid Materials.

The use of artificial neural network (ANN) potentials trained with first-principles calculations has emerged as a promising approach for molecular dynamics (MD) simulations encompassing large space and time scales while retaining first-principles accuracy. To date, however, the application of ANN-MD has been limited to processes. Here we combine first-principles-trained ANN-MD with multiscale shock theory (MSST) to successfully describe shock phenomena.

Hydrogen Bond Preserving Stress Release Mechanism Is Key to the Resilience of Aramid Fibers.

molecular dynamics simulations of shock loading on poly(-phenylene terephthalamide) (PPTA) reveal stress release mechanisms based on hydrogen bond preserving structural phase transformation (SPT) and planar amorphization. The SPT is triggered by [100] shock-induced coplanarity of phenylene groups and rearrangement of sheet stacking leading to a novel monoclinic phase. Planar amorphization is generated by [010] shock-induced scission of hydrogen bonds leading to disruption of polymer sheets, and -to- conformational change of polymer chains.

Guidelines for creating artificial neural network empirical interatomic potential from first-principles molecular dynamics data under specific conditions and its application to α-AgSe.

First-principles molecular dynamics (FPMD) simulations are highly accurate, but due to their high calculation cost, the computational scale is often limited to hundreds of atoms and few picoseconds under specific temperature and pressure conditions. We present here the guidelines for creating artificial neural network empirical interatomic potential (ANN potential) trained with such a limited FPMD data, which can perform long time scale MD simulations at least under the same conditions. The FPMD data for training are prepared on the basis of the convergence of radial distribution function [g(r)].

Instantaneous measurement of high-power millimeter-wave beam for 28 GHz gyrotron.

An instantaneous measurement system of high-power millimeter-wave was proposed and demonstrated with a 28 GHz gyrotron at the Plasma Research Center, University of Tsukuba. The high-power detector consists of an attenuator and a linear polarized microstrip antenna with an F-class load rectifier, which is a commonly used system for radio-frequency wireless power transmission. The detector obtained the power distribution of the gyrotron output beam which showed good agreement with the infrared camera image.

Ab initio molecular dynamics study of prebiotic production processes of organic compounds at meteorite impacts on ocean.

Recent experiments concerning prebiotic materials syntheses suggest that the iron-bearing meteorite impacts on ocean during Late Heavy Bombardment provided abundant organic compounds associated with biomolecules such as amino acids and nucleobases. However, the molecular mechanism of a series of chemical reactions to produce such compounds is not well understood. In this study, we simulate the shock compression state of a meteorite impact for a model system composed of CO , H O, and metallic iron slab by ab initio molecular dynamics combined with multiscale shock technique, and clarify possible elementary reaction processes up to production of organic compounds.

Meteorite impacts on ancient oceans opened up multiple NH production pathways.

A recent series of shock experiments by Nakazawa et al. starting in 2005 (e.g.

Rotation mechanism of methylammonium molecules in organometal halide perovskite in cubic phase: An ab initio molecular dynamics study.

Rotation of methylammonium (CHNH or MA) molecules is believed to govern the excellent transport properties of photocarriers in the MA lead iodide (MAPbI) perovskite. Of particular interest is its cubic phase, which exists in industrially important films at room temperature. In order to investigate the rotational behaviors of the MA molecules, we have performed ab initio molecular dynamics simulations of cubic-MAPbI at room temperature.

Meteorite Impact-Induced Rapid NH Production on Early Earth: Ab Initio Molecular Dynamics Simulation.

NH is an essential molecule as a nitrogen source for prebiotic amino acid syntheses such as the Strecker reaction. Previous shock experiments demonstrated that meteorite impacts on ancient oceans would have provided a considerable amount of NH from atmospheric N and oceanic HO through reduction by meteoritic iron. However, specific production mechanisms remain unclear, and impact velocities employed in the experiments were substantially lower than typical impact velocities of meteorites on the early Earth.

Anisotropic mechanoresponse of energetic crystallites: a quantum molecular dynamics study of nano-collision.

At the nanoscale, chemistry can happen quite differently due to mechanical forces selectively breaking the chemical bonds of materials. The interaction between chemistry and mechanical forces can be classified as mechanochemistry. An example of archetypal mechanochemistry occurs at the nanoscale in anisotropic detonating of a broad class of layered energetic molecular crystals bonded by inter-layer van der Waals (vdW) interactions.

Nanocarbon synthesis by high-temperature oxidation of nanoparticles.

High-temperature oxidation of silicon-carbide nanoparticles (nSiC) underlies a wide range of technologies from high-power electronic switches for efficient electrical grid and thermal protection of space vehicles to self-healing ceramic nanocomposites. Here, multimillion-atom reactive molecular dynamics simulations validated by ab initio quantum molecular dynamics simulations predict unexpected condensation of large graphene flakes during high-temperature oxidation of nSiC. Initial oxidation produces a molten silica shell that acts as an autocatalytic 'nanoreactor' by actively transporting oxygen reactants while protecting the nanocarbon product from harsh oxidizing environment.

The nature of free-carrier transport in organometal halide perovskites.

Organometal halide perovskites are attracting great attention as promising material for solar cells because of their high power conversion efficiency. The high performance has been attributed to the existence of free charge carriers and their large diffusion lengths, but the nature of carrier transport at the atomistic level remains elusive. Here, nonadiabatic quantum molecular dynamics simulations elucidate the mechanisms underlying the excellent free-carrier transport in CH3NH3PbI3.

Ninjurin1 is a novel factor to regulate angiogenesis through the function of pericytes.

Background: Capillary pericytes (cPCs), the mural cells of microvessels, play an important role in the formation and maintenance of microvessels; however, little is known about the mechanisms of how cPCs regulate angiogenesis. To identify factors that modulate cPC function, genes whose levels were altered in cPCs during neovessel formation were identified through a microarray screen.

Methods And Results: Ninjurin1 (nerve injury-induced protein, Ninj1) was selected as a candidate factor for angiogenesis regulation.

Immortalized multipotent pericytes derived from the vasa vasorum in the injured vasculature. A cellular tool for studies of vascular remodeling and regeneration.

Adventitial microvessels, vasa vasorum in the vessel walls, have an active role in the vascular remodeling, although its mechanisms are still unclear. It has been reported that microvascular pericytes (PCs) possess mesenchymal plasticity. Therefore, microvessels would serve as a systemic reservoir of stem cells and contribute to the tissues remodeling.

Hydrogen-on-demand using metallic alloy nanoparticles in water.

Hydrogen production from water using Al particles could provide a renewable energy cycle. However, its practical application is hampered by the low reaction rate and poor yield. Here, large quantum molecular dynamics simulations involving up to 16,611 atoms show that orders-of-magnitude faster reactions with higher yields can be achieved by alloying Al particles with Li.