Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Fast parallel algorithms for short-range molecular dynamics

Nucleotide sequences of a partial cytochrome c oxidase subunit I gene were used to assess the manner in which historical processes and geomorphological effects may have influenced genetic structuring and phylogeographic patterns in Channa striata. Assaying was based on individuals from twelve populations in four river systems, which were separated into two regions, the eastern and western, of the biodiversely rich state of Perak in central Peninsular Malaysia. In 238 specimens, a total of 368-bp sequences with ten polymorphic sites and eleven unique haplotypes were detected. Data on all the twelve populations revealed incomplete divergence due to past historical coalescence and the short period of separation. Nevertheless, SAMOVA and FST revealed geographical structuring existed to a certain extent in both regions. For the eastern region, the data also showed that the upstream populations were genetically significantly different compared to the midand downstream ones. It is inferred that physical barriers and historical processes played a dominant role in structuring the genetic dispersal of the species. A further inference is that the Grik, Tanjung Rambutan and Sungkai are potential candidates for conservation and aquaculture programmes since they contained most of the total diversity in this area.

Research Article 海色リモートセンシング

Tungsten is the heaviest transition metal in the family of common transition metal dichalcogenides (TMDCs). Despite the essential similarities of TMDCs, the considerable differences in the size and charge of the building elements can make the typical 2D layered structure suitable for various applications. There is not much flexibility on the chalcogen side, as the popular elements are S and Se. Following the successful history of transition metal sulphides in various applications, transition metal selenides are now the rising stars. On the transition metal side, WS2 and WSe2 have recently attracted considerable attention. In comparison with the Mo counterparts, W is more abundant in the Earth's crust and thus cheaper, and less toxic. The significantly larger size of W atoms can substantially tune the TMDC properties. The popularity of molybdenum dichalcogenides has somehow overshadowed the potentials of tungsten dichalcogenides. This manuscript attempts to collect the recent reports on various applications of WS2 and WSe2 to provide a general overview of tungsten dichalcogenides. Due to the popularity of sulphides, the prime focus of the present review is on WSe2, which is an emerging member of this family. Although WTe2 is not a common material like all transition metal tellurides, it is also briefly reviewed as a member of this sub-family of TMDCs owing to its unique properties, which named it as a potential candidate for giant magnetoresistance and superconductivity.

Tungsten dichalcogenides (WS2, WSe2, and WTe2): materials chemistry and applications

We introduce a scheme for molecular simulations, the deep potential molecular dynamics (DPMD) method, based on a many-body potential and interatomic forces generated by a carefully crafted deep neural network trained with ab initio data. The neural network model preserves all the natural symmetries in the problem. It is first-principles based in the sense that there are no ad hoc components aside from the network model. We show that the proposed scheme provides an efficient and accurate protocol in a variety of systems, including bulk materials and molecules. In all these cases, DPMD gives results that are essentially indistinguishable from the original data, at a cost that scales linearly with system size.

Deep Potential Molecular Dynamics: a Scalable Model with the Accuracy of Quantum Mechanics

We provide an introduction to Gaussian process regression (GPR) machine-learning methods in computational materials science and chemistry. The focus of the present review is on the regression of atomistic properties: in particular, on the construction of interatomic potentials, or force fields, in the Gaussian Approximation Potential (GAP) framework; beyond this, we also discuss the fitting of arbitrary scalar, vectorial, and tensorial quantities. Methodological aspects of reference data generation, representation, and regression, as well as the question of how a data-driven model may be validated, are reviewed and critically discussed. A survey of applications to a variety of research questions in chemistry and materials science illustrates the rapid growth in the field. A vision is outlined for the development of the methodology in the years to come.

Gaussian Process Regression for Materials and Molecules.

Transition metal nitrides have been suggested to have both high hardness and good thermal stability with large potential application value, but so far stable superhard transition metal nitrides have not been synthesized. Here, with our newly developed machine-learning accelerated crystal structure searching method, we designed a superhard tungsten nitride, h-WN6, which can be synthesized at pressure around 65 GPa and quenchable to ambient pressure. This h-WN6 is constructed with single-bonded armchair-like N6 rings and presents ionic-like features, which can be formulated as W2.4+N62.4−. It has a band gap of 1.6 eV at 0 GPa and exhibits an abnormal gap broadening behavior under pressure. Excitingly, this h-WN6 is found to be the hardest among transition metal nitrides known so far (Vickers hardness around 57 GPa) and also has a very high melting temperature (around 1,900 K). Additionally, the good gravimetric (3.1 kJ/g) and volumetric (28.0 kJ/cm3) energy densities make this nitrogen-rich compound a potential high-energy-density material. These predictions support the designing rules and may stimulate future experiments to synthesize superhard and high-energy-density material.

A novel superhard tungsten nitride predicted by machine-learning accelerated crystal structure search

The structure and superconductivity of $\mathrm{WT}{\mathrm{e}}_{2}$ under pressure are investigated using ab initio calculations combined with high-pressure synchrotron x-ray diffraction and Raman spectroscopy. We find that the emergence of superconductivity in $\mathrm{WT}{\mathrm{e}}_{2}$ under pressure can be attributed to the phase transition from ambient ${T}_{d}$ phase to the monoclinic $1T$\ensuremath{'} structure phase at around 4--5 GPa, which is associated with a sliding of the $\mathrm{WT}{\mathrm{e}}_{2}$ layers, resulting in a critical point in the changes of Te-Te interlayer distance. This phase transition introduces an inversion center and eliminates the topological Weyl fermions in the ${T}_{d}$ structure. Electron-phonon coupling calculations predict a similar ${T}_{c}$ as the reported value, implying that $\mathrm{WT}{\mathrm{e}}_{2}$ might belong to conventional normal Bardeen-Cooper-Schrieffer superconductors.

Origin of superconductivity in the Weyl semimetal WT e 2 under pressure

Transition metal nitrides have been suggested to have both high hardness and good thermal stability with large potential application value, but so far stable superhard transition metal nitrides have not been synthesized. Here, with our newly developed machine-learning accelerated crystal structure searching method, we designed a superhard tungsten nitride, h-WN6, which can be synthesized at pressure around 65 GPa and quenchable to ambient pressure. This h-WN6 is constructed with single-bonded N6 rings and presents ionic-like features, which can be formulated as W2.4+N62.4-. It has a band gap of 1.6 eV at 0 GPa and exhibits an abnormal gap broadening behavior under pressure. Excitingly, this h-WN6 is found to be the hardest among transition metal nitrides known so far (Vickers hardness around 57 GPa) and also has a very high melting temperature (around 1900 K). These predictions support the designing rules and may stimulate future experiments to synthesize superhard material.

A novel superhard tungsten nitride predicted by machine-learning accelerated crystal structure searching

Polynitrogen compounds especially pentazolate anion complexes recently have attracted substantial attention due to their promising potential as high-energy-density materials. Here, using a machine-...

Pressure-Stabilized High-Energy-Density Alkaline-Earth-Metal Pentazolate Salts

Superionic states are phases of matter that can simultaneously exhibit some of the properties of a liquid and of a solid. For example, in superionic ice, hydrogen atoms can move freely while oxygen atoms are fixed in their sublattice. ‘Superionicity’ has attracted much attention in both fundamental science and applications. Helium is the most inert element in nature and it is generally considered to be unreactive. Here, we use ab initio calculations to show that He and H2O can form stable compounds within a large pressure range that can exist even close to ambient pressure. Surprisingly, we find that they can form two previously unknown types of superionic state under high pressure and high temperature. In the first of these phases, the helium atoms exhibit liquid behaviour within a fixed ice-lattice framework. In the second phase, both helium and hydrogen atoms move in a liquid-like fashion within a fixed oxygen sublattice. As the He–O interaction is weaker than the H–O interaction, the helium atoms in these superionic states have larger diffusion coefficients and lower ‘melting’ temperatures than those of hydrogen, although helium is heavier than hydrogen. The insertion of helium atoms substantially decreases the pressure at which superionic states may be formed, compared to those in pure ice. Superionic states of matter simultaneously exhibit some of the properties of a liquid and of a solid. Detailed numerical simulations predict two superionic phases in mixtures of helium and water.

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Hao Gao

Papers

A novel superhard tungsten nitride predicted by machine-learning accelerated crystal structure search

Origin of superconductivity in the Weyl semimetal WT e 2 under pressure

A novel superhard tungsten nitride predicted by machine-learning accelerated crystal structure searching

Pressure-Stabilized High-Energy-Density Alkaline-Earth-Metal Pentazolate Salts

Multiple superionic states in helium–water compounds