Literature DB >> 32544334

Prediction of Lattice Constant of A2XY6 Cubic Crystals Using Gene Expression Programming.

Menad Nait Amar1, Mohammed Abdelfetah Ghriga2,3, Mohamed El Amine Ben Seghier4,5, Hocine Ouaer6.   

Abstract

Lattice constant is one of the paramount parameters that mark the quality of thin film fabrication. Numerous research efforts have been made to calculate and measure lattice constant, including experimental and empirical approaches. Not withstanding these efforts, a reliable and simple-to-use model is still needed to predict accurately this vital parameter. In this study, gene expression programming (GEP) approach was implemented to establish trustworthy model for prediction of the lattice constant of A2XY6 (A = K, Cs, Rb, TI; X = tetravalent cation; and Y = F, Cl, Br, I) cubic crystals based on a comprehensive experimental database. The obtained results showed that the proposed GEP correlation provides excellent prediction performance with an overall average absolute relative deviation (AARD%) of 0.3596% and a coefficient of determination (R2) of 0.9965. Moreover, the comparison of the performance between the newly proposed correlation and the best pre-existing paradigms demonstrated that the established GEP correlation is more robust, reliable, and efficient than the prior models for prediction of lattice constant of A2XY6 cubic crystals.

Entities:  

Year:  2020        PMID: 32544334     DOI: 10.1021/acs.jpcb.0c04259

Source DB:  PubMed          Journal:  J Phys Chem B        ISSN: 1520-5207            Impact factor:   2.991


  1 in total

1.  Mlatticeabc: Generic Lattice Constant Prediction of Crystal Materials Using Machine Learning.

Authors:  Yuxin Li; Wenhui Yang; Rongzhi Dong; Jianjun Hu
Journal:  ACS Omega       Date:  2021-04-20
  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.