Literature DB >> 28257017

Ab initio crystal structure prediction of magnesium (poly)sulfides and calculation of their NMR parameters.

Gregor Mali1.   

Abstract

Ab initio prediction of sensible crystal structures can be regarded as a crucial task in the quickly-developing methodology of NMR crystallography. In this contribution, an evolutionary algorithm was used for the prediction of magnesium (poly)sulfide crystal structures with various compositions. The employed approach successfully identified all three experimentally detected forms of MgS, i.e. the stable rocksalt form and the metastable wurtzite and zincblende forms. Among magnesium polysulfides with a higher content of sulfur, the most probable structure with the lowest formation energy was found to be MgS2, exhibiting a modified rocksalt structure, in which S2- anions were replaced by S22- dianions. Magnesium polysulfides with even larger fractions of sulfur were not predicted to be stable. For the lowest-energy structures, 25Mg quadrupolar coupling constants and chemical shift parameters were calculated using the density functional theory approach. The calculated NMR parameters could be well rationalized by the symmetries of the local magnesium environments, by the coordination of magnesium cations and by the nature of the surrounding anions. In the future, these parameters could serve as a reference for the experimentally determined 25Mg NMR parameters of magnesium sulfide species.

Entities:  

Keywords:  25Mg NMR; GIPAW/DFT calculations; MgS polymorphs; NMR crystallography; hypothetical MgS2 crystal structure

Year:  2017        PMID: 28257017     DOI: 10.1107/S2053229617000687

Source DB:  PubMed          Journal:  Acta Crystallogr C Struct Chem        ISSN: 2053-2296            Impact factor:   1.172


  1 in total

1.  Chemical shifts in molecular solids by machine learning.

Authors:  Federico M Paruzzo; Albert Hofstetter; Félix Musil; Sandip De; Michele Ceriotti; Lyndon Emsley
Journal:  Nat Commun       Date:  2018-10-29       Impact factor: 14.919

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.