Correction to "Generative Adversarial Networks for Crystal Structure Prediction". [PDF]
ACS Cent Sci, 2022 Correction to “Generative Adversarial Networks for Crystal Structure ...
Kim S +4 more
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Crystal structure prediction at finite temperatures
npj Computational Materials, 2023 Crystal structure prediction is a central problem of crystallography and materials science, which until mid-2000s was considered intractable. Several methods, based on either energy landscape exploration or, more commonly, global optimization, largely ...
Ivan A. Kruglov +5 more
doaj +2 more sources
Crystal structure prediction: are we there yet? [PDF]
Acta Crystallographica Section B Structural Science, Crystal Engineering and Materials, 2016 This contribution comments on the advances of the latest Crystal Structure Prediction blind test and the challenges still lying ahead.
Cruz Cabeza, Aurora
openaire +5 more sources
Efficient Crystal Structure Prediction for Structurally Related Molecules with Accurate and Transferable Tailor-Made Force Fields. [PDF]
J Chem Theory Comput, 2022 Crystal structure prediction (CSP) has been historically used to complement experimental solid form screening and applied to individual molecules in drug development.
Mattei A +10 more
europepmc +2 more sources
End-to-End Crystal Structure Prediction from Powder X-Ray Diffraction. [PDF]
Adv Sci (Weinh)Powder X‐ray diffraction (PXRD) is a prevalent technique in materials characterization. While the analysis of PXRD often requires extensive human manual intervention, and most automated method only achieved at coarse‐grained level. The more difficult and
Lai Q +11 more
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Crystal structure prediction by combining graph network and optimization algorithm. [PDF]
Nat Commun, 2022 Predicting crystal structure prior to experimental synthesis is highly desirable. Here the authors propose a machine-learning framework combining graph network and optimization algorithms for crystal structure prediction, which is about three orders of ...
Cheng G, Gong XG, Yin WJ.
europepmc +2 more sources
Geometric Deep Learning for Molecular Crystal Structure Prediction. [PDF]
J Chem Theory Comput, 2023 We develop and test new machine learning strategies for accelerating molecular crystal structure ranking and crystal property prediction using tools from geometric deep learning on molecular graphs. Leveraging developments in graph-based learning and the
Kilgour M, Rogal J, Tuckerman M.
europepmc +4 more sources
Noncovalent Interactions and Crystal Structure Prediction of Energetic Materials. [PDF]
Molecules, 2022 The crystal and molecular structures, intermolecular interactions, and energy of CL-20, HATO, and FOX-7 were comparatively predicted based on molecular dynamic (MD) simulations.
Liu Y +5 more
europepmc +2 more sources
Generative Adversarial Networks for Crystal Structure Prediction. [PDF]
ACS Cent Sci, 2020 Kim S +4 more
europepmc +2 more sources
Exploring organic chemical space for materials discovery using crystal structure prediction-informed evolutionary optimisation. [PDF]
Nat CommunOrganic molecular crystals offer a broad spectrum of potential applications. The vast number of possible molecules is both an opportunity and a challenge, because of the prohibitive expense of exhaustively searching chemical space to find novel molecules
Johal J, Day GM.
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