Crystal structure prediction is a long-standing challenge in condensed matter and chemical science. Here we report a machine-learning approach for crystal structure prediction, in which a graph network (GN) is employed to establish a correlation model between the crystal structure and formation enthalp...
A Bayesian optimisation algorithm for deep learning crystal structure prediction software (CBD-GM) is used to predict the structures of Cu(I) and Cu(II) oxides of 2D and 3D materials. Two known 2D structures and two known 3D structures were anticipated, in addition to the prediction of 5 ...
Theoretical or Mathematical/ crystal structure particle swarm optimisation physics computing/ CALYPSO crystal structure prediction software package Crystal structure AnaLYsis by Particle Swarm Optimization metastable crystal structures chemical compositions particle-swarm optimization algorithm symmetry constraints structu...
57–62 Crystal structure prediction from the molecular structure without use of experimental data requires ab initio models. In the case of pigments, one of the most challenging aspects of crystal modeling is the ability of one molecular structure to exist in different crystal or polymorphic forms....
M.A.N. is the founder, owner and director of the company Avant-garde Materials Simulation that develops the GRACE software for crystal structure prediction. The remaining authors declare no competing financial interests. Supplementary information Supplementary Figures, Supplementary Tables, Supplementary Not...
CrySPY (pronounced as crispy) is a crystal structure prediction tool written in Python. Document:https://tomoki-yamashita.github.io/CrySPY_doc Questions and comments:https://github.com/Tomoki-YAMASHITA/CrySPY/discussions Latest version version 1.3.0 (2024 May 31) ...
First-principles calculations of the magnetic ordering confirm that Pmcm with a two-site model is energetically more favorable at high pressure, and predict that the ordered structure is anisotropic in its electrical and elastic properties. These results suggest that interpretations of seismic structure...
This software package implements the Crystal Graph Convolutional Neural Networks (CGCNN) that takes an arbitary crystal structure to predict material properties. The package provides two major functions: Train a CGCNN model with a customized dataset. ...
Crystallography and NMR system: a new software suite for macromolecular structure determination Acta Crystallogr. D Biol. Crystallogr., 54 (1998), pp. 905-921 View in ScopusGoogle Scholar Burmeister, 2000 W.P. Burmeister Structural changes in a cryo-cooled protein crystal owing to radiation damage...
The ultimate aim of crystal structure prediction as part of solid form selection is the derisking of the developed form to prevent the recurrence of a disaster such as that of ritonavir. As such, the uncertainty or expected error of the calculated values must be carefully quantified relative to...