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.

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.

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.

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.

Dynamic asymmetry of self-diffusion in liquid ZnCl2 under pressure: an ab initio molecular-dynamics study.

The static and dynamic properties of liquid ZnCl2 under pressure are investigated by ab initio molecular-dynamics simulations. The pressure range covers ambient to approximately 80 GPa. The ZnCl4 tetrahedra, which are rather stable at ambient pressure, are shown to deform and collapse with increasing pressure while maintaining an almost constant nearest-neighbor distance between Zn and Cl atoms. The average coordination number of Cl atoms around Zn atoms increases monotonically with pressure, from four at ambient pressure to seven at approximately 80 GPa. Although the self-diffusion coefficients of Zn and Cl atoms, d(Zn) and d(Cl), are almost the same at ambient pressure, the difference between them increases with pressure. At around 10 GPa, d(Zn) is about two times larger than d(Cl). Under further compression, this dynamic asymmetry becomes smaller. The microscopic mechanism of the appearance of the dynamic asymmetry is discussed in relation to the pressure dependence of the local structure.