Results 21 to 30 of about 101,057 (252)
The 7th Blind Test of CSP Methods: Triumphs, Challenges and Insights [PDF]
Structural DynamicsCrystalline forms are of high interest to industry and academia alike for the exquisite control they confer over physicochemical properties affecting functional material performance, the quality, safety and efficacy of medicines, as well as their ...
Susan M Reutzel-Edens, Lily M Hunnisett
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Deep Learning Classification of Crystal Structures Utilizing Wyckoff Positions
Crystals, 2022 In materials science, crystal lattice structures are the primary metrics used to measure the structure–property paradigm of a crystal structure. Crystal compounds are understood by the number of various atomic chemical settings, which are associated with
Nada Ali Hakami +1 more
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Reinforcement Learning in Crystal Structure Prediction
Digital Discovery, 2023 Crystal Structure Prediction (CSP) is a fundamental computational problem in materials science. Basin-hopping is a prominent CSP method that combines global Monte Carlo sampling to search over candidate trial structures with local energy minimisation of these candidates.
Elena Zamaraeva +9 more
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npj Computational Materials, 2023 A desired prerequisite when performing a quantum mechanical calculation is to have an initial idea of the atomic positions within an approximate crystal structure. The atomic positions combined should result in a system located in, or close to, an energy
Adam Carlsson +2 more
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On the Hardness of Energy Minimisation for Crystal Structure Prediction [PDF]
Fundamenta Informaticae, 2020 Crystal Structure Prediction (CSP) is one of the central and most challenging problems in materials science and computational chemistry. In CSP, the goal is to find a configuration of ions in 3D space that yields the lowest potential energy. Finding an efficient procedure to solve this complex optimisation question is a well known open problem.
Duncan Adamson +3 more
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Chemically directed structure evolution for crystal structure prediction [PDF]
Physical Chemistry Chemical Physics, 2020 The chemically directed structure evolution method uses chemical models to quantify the environment of atoms and vacancy sites in a crystal structure with that information used to inform how to modify the structure for crystal structure prediction.
Paul M. Sharp +4 more
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A Comprehensive Review of Machine-Learning Approaches for Crystal Structure/Property Prediction
CrystalsCrystal Property Prediction (CPP) and Crystal Structure Prediction (CSP) play an important role in accelerating the design and discovery of advanced materials across various scientific disciplines.
Mostafa Sadeghian +2 more
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Crystal structure prediction from first principles: The crystal structures of glycine [PDF]
Chemical Physics Letters, 2015 Here we present the results of our unbiased searches of glycine polymorphs obtained using the Genetic Algorithms search implemented in Modified Genetic Algorithm for Crystals coupled with the local optimization and energy evaluation provided by Quantum Espresso.
Lund, Albert M. +4 more
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Aniline–phenol recognition: from solution through supramolecular synthons to cocrystals
IUCrJ, 2014 Aniline–phenol recognition is studied in the crystal engineering context in several 1:1 cocrystals that contain a closed cyclic hydrogen-bonded [...O—H...N—H...]2 tetramer supramolecular synthon (II). Twelve cocrystals of 3,4,5- and 2,3,4-trichlorophenol
Arijit Mukherjee +3 more
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High-throughput calculation screening for new silicon allotropes with monoclinic symmetry
IUCrJ, 2023 A total of 87 new monoclinic silicon allotropes are systematically scanned by a random strategy combined with group and graph theory and high-throughput calculations.
Qingyang Fan +4 more
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