Literature DB >> 25338876

Predicting polymeric crystal structures by evolutionary algorithms.

Qiang Zhu1, Vinit Sharma2, Artem R Oganov1, Ramamurthy Ramprasad2.   

Abstract

The recently developed evolutionary algorithm USPEX proved to be a tool that enables accurate and reliable prediction of structures. Here we extend this method to predict the crystal structure of polymers by constrained evolutionary search, where each monomeric unit is treated as a building block with fixed connectivity. This greatly reduces the search space and allows the initial structure generation with different sequences and packings of these blocks. The new constrained evolutionary algorithm is successfully tested and validated on a diverse range of experimentally known polymers, namely, polyethylene, polyacetylene, poly(glycolic acid), poly(vinyl chloride), poly(oxymethylene), poly(phenylene oxide), and poly (p-phenylene sulfide). By fixing the orientation of polymeric chains, this method can be further extended to predict the structures of complex linear polymers, such as all polymorphs of poly(vinylidene fluoride), nylon-6 and cellulose. The excellent agreement between predicted crystal structures and experimentally known structures assures a major role of this approach in the efficient design of the future polymeric materials.

Entities:  

Year:  2014        PMID: 25338876     DOI: 10.1063/1.4897337

Source DB:  PubMed          Journal:  J Chem Phys        ISSN: 0021-9606            Impact factor:   3.488


  3 in total

1.  Bonding-restricted structure search for novel 2D materials with dispersed C2 dimers.

Authors:  Cunzhi Zhang; Shunhong Zhang; Qian Wang
Journal:  Sci Rep       Date:  2016-07-12       Impact factor: 4.379

2.  A polymer dataset for accelerated property prediction and design.

Authors:  Tran Doan Huan; Arun Mannodi-Kanakkithodi; Chiho Kim; Vinit Sharma; Ghanshyam Pilania; Rampi Ramprasad
Journal:  Sci Data       Date:  2016-03-01       Impact factor: 6.444

3.  Predicting phase behavior of grain boundaries with evolutionary search and machine learning.

Authors:  Qiang Zhu; Amit Samanta; Bingxi Li; Robert E Rudd; Timofey Frolov
Journal:  Nat Commun       Date:  2018-02-01       Impact factor: 14.919

  3 in total

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