AELAS: Automatic ELAStic property derivations via high-throughput first-principles computation

被引:97
|
作者
Zhang, S. H.
Zhang, R. F. [1 ]
机构
[1] Beihang Univ, Sch Mat Sci & Engn, Beijing 100191, Peoples R China
基金
中国国家自然科学基金;
关键词
Elastic properties; High-throughput computation; First-principles calculation; Two-dimensional materials; CONSTANTS; CRYSTALS; DIOPSIDE; GRAPHENE; MGO;
D O I
10.1016/j.cpc.2017.07.020
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The elastic properties are fundamental and important for crystalline materials as they relate to other mechanical properties, various thermodynamic qualities as well as some critical physical properties. However, a complete set of experimentally determined elastic properties is only available for a small subset of known materials, and an automatic scheme for the derivations of elastic properties that is adapted to high-throughput computation is much demanding. In this paper, we present the AELAS code, an automated program for calculating second-order elastic constants of both two-dimensional and three-dimensional single crystal materials with any symmetry, which is designed mainly for high throughput first-principles computation. Other derivations of general elastic properties such as Young's, bulk and shear moduli as well as Poisson's ratio of polycrystal materials, Pugh ratio, Cauchy pressure, elastic anisotropy and elastic stability criterion, are also implemented in this code. The implementation of the code has been critically validated by a lot of evaluations and tests on a broad class of materials including two-dimensional and three-dimensional materials, providing its efficiency and capability for high-throughput screening of specific materials with targeted mechanical properties. Program summary Program title: AELAS Program Files doi: http://dx.doi.org/10.17632/f8fwg4j9tw.1 Licensing provisions: BSD 3-Clause Programming language: Fortran Nature of problem: To automate the calculations of second-order elastic constants and the derivations of other elastic properties for two-dimensional and three-dimensional materials with any symmetry via high-throughput first-principles computation. Solution method: The space-group number is firstly determined by the SPGLIB code [1] and the structure is then redefined to unit cell with IEEE-format [2]. Secondly, based on the determined space group number, a set of distortion modes is automatically specified and the distorted structure files are generated. Afterwards, the total energy for each distorted structure is calculated by the first-principles codes, e.g. VASP [3]. Finally, the second-order elastic constants are determined from the quadratic coefficients of the polynomial fitting of the energies vs strain relationships and other elastic properties are accordingly derived. References [1] http://atztogo.github.io/spglib/. [2] A. Meitzler, H.F. Tiersten, A.W. Warner, D. Berlincourt, G.A. Couqin, F.S. Welsh III, IEEE standard on piezoelectricity, Society, 1988. [3] G. Kresse, J. Furthmilller, Phys. Rev. B 54 (1996) 11169. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:403 / 416
页数:14
相关论文
共 50 条
  • [31] The effects of combining alloying elements on the elastic properties of γ-Ni in Ni-based superalloy: High-throughput first-principles calculations
    Lu, Baokun
    Wang, Chongyu
    CHINESE PHYSICS B, 2018, 27 (07)
  • [32] First-principles-based high-throughput computation for high entropy alloys with short range order
    Sorkin, V.
    Chen, S.
    Tan, Teck L.
    Yu, Z. G.
    Man, M.
    Zhang, Y. W.
    JOURNAL OF ALLOYS AND COMPOUNDS, 2021, 882
  • [33] Searching for materials with high refractive index and wide band gap: A first-principles high-throughput study
    Naccarato, Francesco
    Ricci, Francesco
    Suntivich, Jin
    Hautier, Geoffroy
    Wirtz, Ludger
    Rignanese, Gian-Marco
    PHYSICAL REVIEW MATERIALS, 2019, 3 (04):
  • [34] Core-Shell Nanocatalyst Design by Combining High-Throughput Experiments and First-Principles Simulations
    Peela, Nageswara Rao
    Zheng, Weiqing
    Lee, Ivan C.
    Karim, Ayman M.
    Vlachos, Dionisios G.
    CHEMCATCHEM, 2013, 5 (12) : 3712 - 3718
  • [35] Machine learning aided high-throughput first-principles calculations to predict the formation enthalpy of σ phase
    Su, Yue
    Wang, Jiong
    CALPHAD-COMPUTER COUPLING OF PHASE DIAGRAMS AND THERMOCHEMISTRY, 2023, 82
  • [36] Photovoltaic properties of novel quaternary chalcogenides based on high-throughput screening and first-principles calculations
    Kang, Jia-Xing
    Yan, Quan-He
    Cao, Hao-Yu
    Meng, Wei-Wei
    Xu, Fei
    Hong, Feng
    ACTA PHYSICA SINICA, 2024, 73 (17)
  • [37] High-throughput first-principles investigation on grain boundary segregation of alloying elements in ferritic steel
    Yang, Mengmeng
    Zhou, Jiaying
    Huang, Haijun
    Cao, Shuo
    Hu, Qing-Miao
    Li, Wei
    Chen, Qingjun
    Qiao, Yanxin
    Wang, Hao
    JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T, 2023, 26 : 2140 - 2150
  • [38] Accelerating ferroelectric materials discovery through high-throughput first-principles screening and experimental validation
    Hirai, Daisuke
    Murata, Tomoki
    Hirose, Sakyo
    JAPANESE JOURNAL OF APPLIED PHYSICS, 2024, 63 (07)
  • [39] High-Throughput First-Principles Prediction of Interfacial Adhesion Energies in Metal-on-Metal Contacts
    Restuccia, Paolo
    Losi, Gabriele
    Chehaimi, Omar
    Marsili, Margherita
    Righi, M. Clelia
    ACS APPLIED MATERIALS & INTERFACES, 2023, 15 (15) : 19624 - 19633
  • [40] High-throughput first-principles prediction of superlubricity at the interfaces of NbS2 based heterostructures
    Chen, Lu
    Chen, Jianbang
    Bi, Xinyue
    Cao, Tengfei
    Shi, Junqin
    Fan, Xiaoli
    JOURNAL OF MATERIALS SCIENCE, 2025, : 6138 - 6150