Data-driven PSP linkages for atomistic datasets

Grain boundaries;Materials informatics;Molecular dynamics;Pair correlation function;Principal component analysis;Process-structure-property linkage;Interatomic potentials;Multiscale modeling

Gomberg, Joshua A. ; Kalidindi, Surya R. Materials Science and Engineering McDowell, David L. Li, Mo Haaland, Benjamin Garmestani, Hamid ; Kalidindi, Surya R.

University:Georgia Institute of Technology

Department:Materials Science and Engineering

关键词: Grain boundaries;    Materials informatics;    Molecular dynamics;    Pair correlation function;    Principal component analysis;    Process-structure-property linkage;    Interatomic potentials;    Multiscale modeling;   

Others  :  https://smartech.gatech.edu/bitstream/1853/60125/1/GOMBERG-DISSERTATION-2017.pdf

美国|英语

来源: SMARTech Repository

【 摘 要 】

For a variety of materials, atomic-scale modeling techniques are commonly employed as a means of investigating fundamental properties, including both structural and chemical responses. While force-field based calculations are significantly less computationally expensive than their quantum-mechanical counterparts, the datasets often investigated are large in size (10^3 – 10^9 atoms) and high-dimensional, and thus cumbersome for use in multi-scale models. The development of quantitative “process-structure-property” (PSP) linkages for atomistic simulations presents a powerful route to convert atomistic simulation data into actionable knowledge. Here, a framework is presented for quantifying structure from these simulations in full- and reduced-dimensional form, and a series of protocols are developed for establishing regression models for process-structure and structure-property linkages.