Crystal structure predictionLattice energyForce-fieldsPolymorphismA computational method of predicting all the polymorphs of an organic molecule would be a valuable complement to polymorph screening in the deve
Computational Crystal Structure Prediction: Towards In Silico Solid Form Screening, in: Tiekink, E.R.T., Vittal, J., Zaworotko, M. (Eds.), Organic Crystal Engineering: 35 Frontiers in Crystal Engineering. Wiley, pp. 43-66.Day, G.M., 2010. Computational Crystal Structure Prediction: ...
近日,吉林大学物理学院王彦超教授受Nature Computational Science邀请,撰写了题为 “Boosting crystal structure prediction via symmetry” 的 News & Views 文章,对凝聚态物理领域中晶体结构预测的最新进展进行了评述。 在材料研究领域,传统的材料...
Crystal structure prediction has been widely used to accelerate the discovery of new materials in recent years. Up to this day, it remains a challenge to predict the stable stoichiometries and structures of ternary or more complex systems due to the explosive increase of the size of the chemica...
Structure Prediction Introduction Crystal structure fundamentally shapes all physical and chemical properties of materials, making the determination of atomic arrangements that define the crystal structure an essential and crucial task across a wide range of scientific disciplines1. Crystal structure prediction...
Crystal structure prediction for ternary systems Cluster expansion is an efficient approach for studying alloying in (MoxSc1–x)2AlB2but requires an input structure to build a model upon. The hexagonal Ti2InB2withP6¯m2 symmetry and the orthorhombic Cr2AlB2, Mn2AlB2and Fe2AlB2withCmmmsymmetry13...
Computational prediction of high thermoelectric performance in p-type CuGaTe2with a first-principles study Chaoran Chen, Peng Zhang, Luo Yue, Juan Li, ... Guiwu Lu Pages 369-375 select article Valley polarization and biaxial strain dependent conductivity of WS2/SrRuO3(1 1 1) heterostructure...
Podryabinkin, E. V., Tikhonov, E. V., Shapeev, A. V. & Oganov, A. R. Accelerating crystal structure prediction by machine-learning interatomic potentials with active learning., 064114 (2019). Novoselov, I. I., Yanilkin, A. V., Shapeev, A. V. & Podryabinkin, E. V. Moment te...
Efficient crystal structure prediction based on the symmetry principle This study presents a symmetry principle-biased crystal structure prediction scheme within the MAGUS framework, achieving up to a fourfold performance improvement compared with state-of-the-art methods. Yu Han Chi Ding Jian Sun Ar...
In this work, we introduce Crystal Twins (CT): an SSL framework for crystalline material property prediction with GNNs (Fig. 1). In pre-training, the models in the CT framework does not make use of any labeled data to learn crystalline representations, instead, it trains ML models in a ...