In many scenarios, such as disordered phases (liquid, amorphous), the potential achieved a near-perfect match with the reference method in terms of accuracy, using exactly the same simulation time(very short) and conditions. Even when utilizing longer simulation times and large system with a semi...
The use of machine learning is becoming increasingly common in computational materials science. To build effective models of the chemistry of materials, useful machine-based representations of atoms and their compounds are required. We derive distributed representations of compounds from their chemical form...
exhibiting a natural hierarchy in both computational cost and accuracy. A good materials science example is the band gap of insulators computed at an inexpensive lower
Superionics are fascinating materials displaying both solid- and liquid-like characteristics: as solids, they respond elastically to shear stress; as liquids, they display fast-ion diffusion at normal conditions. In addition to such scientific interest, superionics are technologically relevant for energy...
X-ray absorption spectroscopy (XAS) is a widely used materials characterization technique to determine oxidation states, coordination environment, and other local atomic structure information. Analysis of XAS relies on comparison of measured spectra to reliable reference spectra. However, existing databases...
该文近期发表于npj Computational Materials6: 43 (2020),英文标题与摘要如下,点击https://www.nature.com/articles/s41524-020-0310-0可以自由获取论文PDF。 Completing density functional theory by machine learning hidden messages from molecules Ryo Nagai, Ryosuke Akashi & Osamu Sugino ...
of magnetic structure information from experiments, our high-throughput predictions provide insightful reference results and make the step toward a complete diagnosis of magnetic topological materials. 本文系网易新闻·网易号“各有态度”特色内容
Nuclear magnetic resonance (NMR) spectroscopy is a powerful tool for obtaining precise information about the local bonding of materials, but difficult to interpret without a well-vetted dataset of reference spectra. The ability to predict NMR parameters and connect them to three-dimensional local envir...
the quadratic scaling with the number of atoms exhibited by conventional force-training methods can be avoided, which enables the training on reference datasets containing complex atomic structures. We demonstrate for different materials systems, clusters of water molecules, bulk liquid water, and a lit...
The α/β interface is central to the microstructure and mechanical properties of titanium alloys. We investigate the structure, thermodynamics and migration of the coherent and semicoherent Ti α/β interfaces as a function of temperature and misfit str