Induction and Ferroelectric Switching of Flux Closure Domains in Strained PbTiO3 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 PbTiO3 bulk crystal and 180° domain walls (DWs). NNQMD-BEC simulations correctly describe the nucleation-and-growth mechanism during DW switching. In triaxially strained PbTiO3 with strain conditions commonly seen in many superlattice configurations, we find that flux-closure texture can be induced with application of an electric field perpendicular to the original polarization direction. Upon field reversal, the flux-closure texture switches via a pair of transient vortices as the intermediate state, indicating an energy-efficient switching pathway. Our NNQMD-BEC method provides a theoretical guidance to study electro-mechano effects with existing machine learning force fields using a simple BEC extension, which will be relevant for engineering applications such as field-controlled switching in mechanically strained ferroelectric devices.

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

Mechanical controllability of recently discovered topological defects (e.g., 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. Here, we overcome this challenge by developing a machine-learning-based multiscale simulation framework─a hybrid neural network quantum molecular dynamics (NNQMD) and molecular mechanics (MM) method. For nanostructures composed of SrTiO3 and PbTiO3, we find how the symmetry of mechanical loading essentially controls polar topological switching. We find under symmetry-breaking uniaxial compression a squishing-to-annihilation pathway versus formation of a topological composite named skyrmionium under symmetry-preserving isotropic compression. The distinct pathways are explained in terms of the underlying materials' elasticity and symmetry, as well as the Landau-Lifshitz-Kittel scaling law. Such rational control of ferroelectric topologies will likely facilitate exploration of the rich ferroelectric "topotronics" design space.

Defect-free and crystallinity-preserving ductile deformation in semiconducting Ag2S.

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 (Ag2S), which is defect-free, omni-directional, and preserving perfect crystallinity. Our first-principles molecular dynamics simulations elucidate the ductile deformation mechanism in monoclinic-Ag2S under six types of shear systems. Planer mass movement of sulfur atoms plays an important role for the remarkable structural recovery of sulfur-sublattice. This in turn arises from a distinctively high symmetry of the anion-sublattice in Ag2S, which is not seen in other brittle silver chalcogenides. Such mechanistic and lattice-symmetric understanding provides a guideline for designing even higher-performance ductile inorganic semiconductors.

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 2.24 Å. The computed lifetime of the hydrogen bond is t ≅ 0.1 ps. In contrast to crystalline water-ice, we find that hydrogen bonding is practically nonexistent in crystalline ammonia-I.

Improvement of the Force Field for ß-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 ß-d-glucose, a simple and the most abundant monosaccharide molecule, with the aid of machine learning techniques implemented with the TensorFlow library. Following the pre-sampling over a wide range of configuration space generated by MD simulation, the atomic charge and dihedral angle parameters in the GLYCAM06 force field were re-optimized to accurately reproduce the relative energies of ß-d-glucose obtained by the density functional theory (DFT) calculations according to the structural changes. The validation for the newly proposed force-field parameters was then carried out by verifying that the relative energy errors compared to the DFT value were significantly reduced and that some inconsistencies with experimental (e.g., NMR) results observed in the GLYCAM06 force field were resolved relevantly.

Neural Network Quantum Molecular Dynamics, Intermediate Range Order in GeSe2, 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 GeSe2 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. The system-size dependence of the FSDP height is determined by comparing QMD and NNQMD simulations with experimental data. Partial pair distribution functions, bond-angle distributions, partial and neutron structure factors, and ring-size distributions are presented. Calculated FSDP heights agree quantitatively with neutron scattering data for GeSe2 glass at 10 K and melt at 1100 K.

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. The first, NNQMD, is trained on QMD configurations for liquid water under a variety of temperature and density conditions to learn potential energy surface and forces and then perform molecular dynamics simulations. The second network, NNMLWF, is trained to predict locations of MLWF of individual molecules using the atomic configurations from NNQMD. Training data for both the neural networks is produced using a highly accurate quantum-mechanical method, DFT-SCAN that yields an excellent description of liquid water. We produce 280×10^{6} configurations of water at 7 temperatures using NNQMD and predict MLWF centers using NNMLWF to compute the polarization fluctuations. The length of trajectories needed for a converged value of the dielectric constant at 0°C is found to be 20 ns (40×10^{6} configurations with 0.5 fs time step). The computed dielectric constants for 0, 15, 30, 45, 60, 75, and 90°C are in good agreement with experiments. Our scalable scheme to compute dielectric constants with quantum accuracy is also applicable to other polar molecular liquids.

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-Ag2Se, using the interatomic potential based on an artificial neural network (ANN potential). The training data were created using the existing empirical potential of Ag2Se 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. We clarified that using a rigorous heat flux formula for the ANN potential, even for highly ionic α-Ag2Se, the resulting thermal conductivity was reasonably consistent with the reference value without explicitly considering Coulomb interaction. It was found that ANN training including the virial term played an important role in reducing the dependency of thermal conductivity on the initial values of the weight parameters of the ANN.

Optically Induced Three-Stage Picosecond Amorphization in Low-Temperature SrTiO3.

Photoexcitation can drastically modify potential energy surfaces of materials, allowing access to hidden phases. SrTiO3 (STO) is an ideal material for photoexcitation studies due to its prevalent use in nanostructured devices and its rich range of functionality-changing lattice motions. Recently, a hidden ferroelectric phase in STO was accessed through weak terahertz excitation of polarization-inducing phonon modes. In contrast, whereas strong laser excitation was shown to induce nanostructures on STO surfaces and control nanopolarization patterns in STO-based heterostructures, the dynamic pathways underlying these optically induced structural changes remain unknown. Here nonadiabatic quantum molecular dynamics reveals picosecond amorphization in photoexcited STO at temperatures as low as 10 K. The three-stage pathway involves photoinduced charge transfer and optical phonon activation followed by nonlinear charge and lattice dynamics that ultimately lead to amorphization. This atomistic understanding could guide not only rational laser nanostructuring of STO but also broader "quantum materials on demand" technologies.

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. The calculated results by both the computational approaches have shown fair agreement with each other, whereas slight deviations have been found in the temporal range of femto- to picoseconds when the initial temperatures of the two components are significantly different, such as 300 K vs 1000 K. This discrepancy can be ascribed to the fast intra-component temperature relaxation assumed in the kinetic theory, and its violation in the MD simulations can be evaluated in terms of the Kullback-Leibler divergence between the equilibrated Maxwell-Boltzmann distribution at each temperature and the actual non-equilibrium velocity distribution realized in the MD. Thus, the present analysis provides a quantitative basis for addressing the temperature inhomogeneities experimentally observed in nanoscale crowding conditions.

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 near-equilibrium processes. Here we combine first-principles-trained ANN-MD with multiscale shock theory (MSST) to successfully describe far-from-equilibrium shock phenomena. Our ANN-MSST-MD approach describes shock-wave propagation in solids with first-principles accuracy but a 5000 times shorter computing time. Accordingly, ANN-MD-MSST was able to resolve fine, long-time elastic deformation at low shock speed, which was impossible with first-principles MD because of the high computational cost. This work thus lays a foundation of ANN-MD simulation to study a wide range of far-from-equilibrium processes.

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

Ab initio molecular dynamics simulations of shock loading on poly(p-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 trans-to-cis conformational change of polymer chains. In contrast to the latter, the former mechanism preserves the hydrogen bonding and cohesiveness of polymer chains in the identified novel crystalline phase preserving the strength of PPTA. The interplay between hydrogen bond preserving (SPT) and nonpreserving (planar amorphization) shock release mechanisms is critical to understanding the shock performance of aramid fibers.

Guidelines for creating artificial neural network empirical interatomic potential from first-principles molecular dynamics data under specific conditions and its application to α-Ag2Se.

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)]. While training the ANN using total energy and atomic forces of the FPMD data, the error of pressure is also monitored and minimized. To create further robust potential, we add a small amount of FPMD data to reproduce the interaction between two atoms that are close to each other. ANN potentials for α-Ag2Se were created as an application example, and it has been confirmed that not only g(r) and mean square displacements but also the specific heat requiring a long time scale simulation matched the FPMD and the experimental values. In addition, the MD simulation using the ANN potential achieved over 104 acceleration over the FPMD one. The guidelines proposed here mitigate the creation difficulty of the ANN potential, and a lot of FPMD data sleeping on the hard disk after the research may be put on the front stage again.

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. The rectenna array detector received 45 W RF input power with a 0.4 ms response time. The results revealed that the proposed narrow band detector is useful as an imaging sensor and power meter for high-power millimeter-wave beam output with a wide wavelength range.

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 CO2 , H2 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. The reactions included not only pathways similar to the Fischer-Tropsch process known as an important hydrocarbon synthesis in many planetary processes but also those resulting in production of a carboxylic acid. It is also found that bicarbonate ions formed from CO2 and H2 O participated in some forms in most of these observed elementary reaction processes. These findings would deepen the understanding of the full range of chemical reactions that could occur in the meteorite impact events. © 2018 Wiley Periodicals, Inc.

Meteorite impacts on ancient oceans opened up multiple NH3 production pathways.

A recent series of shock experiments by Nakazawa et al. starting in 2005 (e.g. [Nakazawa et al., Earth Planet. Sci. Lett., 2005, 235, 356]) suggested that meteorite impacts on ancient oceans would have yielded a considerable amount of NH3 to the early Earth from atmospheric N2 and oceanic H2O through reduction by meteoritic iron. To clarify the mechanisms, we imitated the impact events by performing multi-scale shock technique-based ab initio molecular dynamics in the framework of density functional theory in combination with multi-scale shock technique (MSST) simulations. Our previous simulations with impact energies close to that of the experiments revealed picosecond-order rapid NH3 production during shock compression [Shimamura et al., Sci. Rep., 2016, 6, 38952]. It was also shown that the reduction of N2 took place with an associative mechanism as seen in the catalysis of nitrogenase enzymes. In this study, we performed an MSST-AIMD simulation to investigate the production by meteorite impacts with higher energies, which are closer to the expected values on the early Earth. It was found that the amount of NH3 produced further increased. We also found that the increased NH3 production is due to the emergence of multiple reaction mechanisms at increased impact energies. We elucidated that the reduction of N2 was not only attributed to the associative mechanism but also to a dissociative mechanism as seen in the Haber-Bosch process and to a mechanism through a hydrazinium ion. The emergence of these multiple production mechanisms capable of providing a large amount of NH3 would support the suggestions from recent experiments much more strongly than was previously believed, i.e., shock-induced NH3 production played a key role in the origin of life on Earth.

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

Rotation of methylammonium (CH3NH3 or MA) molecules is believed to govern the excellent transport properties of photocarriers in the MA lead iodide (MAPbI3) 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-MAPbI3 at room temperature. There are two types of rotational motions of MA molecules in a crystalline PbI3 cage: reorientation of a whole molecule and intramolecular rotation around the C-N bond within MA molecules. Using a cubic symmetry-assisted analysis (CSAA), we found that the prominent orientation of the C-N bond is the crystalline ⟨110⟩ directions, rather than the ⟨100⟩ and ⟨111⟩ directions. Rapid rotation around the C-N bond is also observed, which easily occurs when the rotational axis is parallel to the ⟨110⟩ directions according to the CSAA. To explain the atomistic mechanisms underlying these CSAA results, we have focused on the relation between H-I hydrogen bonds and the orientation of an MA molecule. Here, the hydrogen bonds were defined by population analysis, and it has been found that, while H atoms in the CH3 group (HC) hardly interacts with I atoms, those in the NH3 group (HN) form at least one hydrogen bond with I atoms and their interatomic distances are in a wide range, 2.2-3.7 Å. Based on these findings, we have given a possible explanation to why the ⟨110⟩ directions are preferred. Namely, the atomic arrangement and interatomic distance between MA and surrounding I atoms are most suitable for the formation of hydrogen bonds. In addition to films, these results are potentially applicable to the rotational behaviors in bulk MAPbI3 as well, considering that the atomistic structure and time constants regarding the rotation of MA molecules statistically agree with bulk experiments.

Meteorite Impact-Induced Rapid NH3 Production on Early Earth: Ab Initio Molecular Dynamics Simulation.

NH3 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 NH3 from atmospheric N2 and oceanic H2O 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. Here, to investigate the issues from the atomistic viewpoint, we performed multi-scale shock technique-based ab initio molecular dynamics simulations. The results revealed a rapid production of NH3 within several picoseconds after the shock, indicating that shocks with greater impact velocities would provide further increase in the yield of NH3. Meanwhile, the picosecond-order production makes one expect that the important nitrogen source precursors of amino acids were obtained immediately after the impact. It was also observed that the reduction of N2 proceeded according to an associative mechanism, rather than a dissociative mechanism as in the Haber-Bosch process.

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. Here, we introduce an ab initio study of the collision, in which quantum molecular dynamic simulations of binary collisions between energetic vdW crystallites, TATB molecules, reveal atomistic mechanisms of anisotropic shock sensitivity. The highly sensitive lateral collision was found to originate from the twisting and bending to breaking of nitro-groups mediated by strong intra-layer hydrogen bonds. This causes the closing of the electronic energy gap due to an inverse Jahn-Teller effect. On the other hand, the insensitive collisions normal to multilayers are accomplished by more delocalized molecular deformations mediated by inter-layer interactions. Our nano-collision studies provide a much needed atomistic understanding for the rational design of insensitive energetic nanomaterials and the detonation synthesis of novel nanomaterials.

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. Percolation transition produces porous nanocarbon with fractal geometry, which consists of mostly sp(2) carbons with pentagonal and heptagonal defects. This work suggests a simple synthetic pathway to high surface-area, low-density nanocarbon with numerous energy, biomedical and mechanical-metamaterial applications, including the reinforcement of self-healing composites.