scholarly journals Exploration and Optimization in Crystal Structure Prediction: Combining Basin Hopping with Quasi-Random Sampling

2020 ◽  
Author(s):  
Shiyue Yang ◽  
Graeme Day
Keyword(s):  
Crystal Structure ◽  
Random Sampling ◽  
Structure Prediction ◽  
Molecular Crystals ◽  
Optimization Procedure ◽  
Low Energy ◽  
Random Structure ◽  
Crystal Structure Prediction ◽  
Structure Generation ◽  
Basin Hopping

We describe the implementation of a Monte Carlo basin hopping global optimization procedure for the prediction of molecular crystal structure. The basin hopping method is combined with quasi-random structure generation in a hybrid method for crystal structure prediction, QR-BH, which combines the low-discrepancy sampling provided by quasi-random sequences with basin hopping's efficiency at locating low energy structures. Through tests on a set of single-component molecular crystals and co-crystals, we demonstrate that QR-BH provides faster location of low energy structures than pure quasi-random sampling, while maintaining the efficient location of higher energy structures that are important for identifying important polymorphs.

scholarly journals Exploration and Optimization in Crystal Structure Prediction: Combining Basin Hopping with Quasi-Random Sampling

2020 ◽  
Author(s):  
Shiyue Yang ◽  
Graeme Day
Keyword(s):  
Crystal Structure ◽  
Random Sampling ◽  
Structure Prediction ◽  
Molecular Crystals ◽  
Optimization Procedure ◽  
Low Energy ◽  
Random Structure ◽  
Crystal Structure Prediction ◽  
Structure Generation ◽  
Basin Hopping

We describe the implementation of a Monte Carlo basin hopping global optimization procedure for the prediction of molecular crystal structure. The basin hopping method is combined with quasi-random structure generation in a hybrid method for crystal structure prediction, QR-BH, which combines the low-discrepancy sampling provided by quasi-random sequences with basin hopping's efficiency at locating low energy structures. Through tests on a set of single-component molecular crystals and co-crystals, we demonstrate that QR-BH provides faster location of low energy structures than pure quasi-random sampling, while maintaining the efficient location of higher energy structures that are important for identifying important polymorphs.

scholarly journals First-year experience with fully automated crystal structure prediction

2014 ◽  
Vol 70 (a1) ◽  
pp. C1618-C1618
Author(s):  
Marcus Neumann ◽  
Bernd Doser
Keyword(s):  
Crystal Structure ◽  
Structure Prediction ◽  
Density Functional ◽  
Method Development ◽  
Force Fields ◽  
Crystal Structure Prediction ◽  
Blind Test ◽  
Structure Generation ◽  
Statistical Correlations ◽  
Pharmaceutical Molecules

With improving hardware and software performance, usability has become one of the main obstacles to a more widespread use of Crystal Structure Prediction (CSP) with the GRACE program. In terms of method development, important milestones had already been passed by the time of the 5th blind test [1] in 2010, including the parameterization of dispersion-corrected Density Functional Theory (DFT-D) [2], the generation of tailor-made force fields from ab-initio reference data [3], a Monte-Carlo parallel tempering crystal structure generation engine and a DFT-d reranking procedure exploiting statistical correlations. These components have now been incorporated in automated data flow processes that remove the burden of scores of expert decisions from the user. Summarizing the results of CSP studies performed with the new Force Field Factory and CSP Factory modules throughout a year, the current performance of CSP is critically assessed and further method development needs are pinpointed. Studied compounds include 20 small molecules with competing hydrogen bonds motifs, 4 mono-hydrates of non-ionic molecules and the hydrates and chloride salts of several amino acids. The ability to handle flexible pharmaceutical molecules is demonstrated by a validation study on aripiprazole with one and two molecules per asymmetric unit. Salient features of the energy landscapes of other pharmaceutical molecules are discussed. Statistics are presented for the accuracy of tailor-made force fields, and the energy ranking performance of several DFT-d flavors is compared.

Mining Predicted Crystal Structure Landscapes with High Throughput Crystallization: Old Molecules, New Insights

2019 ◽  
Author(s):  
Peng Cui ◽  
David P. McMahon ◽  
Peter Spackman ◽  
Ben M. Alston ◽  
Marc A. Little ◽  
...  
Keyword(s):  
Crystal Structure ◽  
High Throughput ◽  
Structure Prediction ◽  
Organic Molecules ◽  
Screening Method ◽  
Molecular Crystals ◽  
Crystal Structure Prediction ◽  
Tetracarboxylic Acid ◽  
Trimesic Acid ◽  
Interconnected Pores

<a></a><a>Organic molecules tend to close pack to form dense structures when they are crystallized from organic solvents. Porous molecular crystals defy this rule: they typically crystallize with lattice solvent in the interconnected pores. However, the design and discovery of such structures is often challenging and time consuming, in part because it is difficult to predict solvent effects on crystallization. Here, we combine crystal structure prediction (CSP) with a high-throughput crystallization screening method to accelerate the discovery of stable hydrogen-bonded frameworks. We exemplify this strategy by finding new phases of two well-studied molecules in a computationally targeted way. Specifically, we find a new porous polymorph of trimesic acid, δ-<b>TMA</b>, that has a guest free hexagonal pore structure, as well as three new solvent-stabilized diamondoid frameworks</a> of adamantane-1,3,5,7-tetracarboxylic acid (<b>ADTA</b>).

Revisiting the Blind Tests in Crystal Structure Prediction: Accurate Energy Ranking of Molecular Crystals

2009 ◽  
Vol 113 (51) ◽  
pp. 16303-16313 ◽  
Author(s):  
Aldi Asmadi ◽  
Marcus A. Neumann ◽  
John Kendrick ◽  
Pascale Girard ◽  
Marc-Antoine Perrin ◽  
...  
Keyword(s):  
Crystal Structure ◽  
Structure Prediction ◽  
Molecular Crystals ◽  
Crystal Structure Prediction

Crystal Structure Prediction of Energetic Materials and a Twisted Arene with Genarris and GAtor

CrystEngComm ◽  
2021 ◽  
Author(s):  
Imanuel Bier ◽  
Dana O'Connor ◽  
Yun-Ting Hsieh ◽  
Wen Wen ◽  
Anna Hiszpanski ◽  
...  
Keyword(s):  
Crystal Structure ◽  
Genetic Algorithm ◽  
Energetic Materials ◽  
Structure Prediction ◽  
Random Structure ◽  
Crystal Structure Prediction ◽  
Structure Generator

A crystal structure prediction (CSP) workflow, based on the random structure generator, Genarris, and the genetic algorithm (GA), GAtor, is applied to the energetic materials 2,4,6-trinitrobenzene-1,3,5-triamine (TATB) and 2,4,6-trinitrobenzene-1,3-diamine (DATB),...

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