Multi-Scale Optimization for Elastic Properties of the Cubic Materials in JARVIS-DFT Database

Published

April 6, 2022

Author(s)

Kamal Choudhary, Francesca Tavazza, Mahmudul Hasan, Pinar Acar

Abstract

A multi-scale design methodology is developed to estimate the optimum elastic properties (stiffness coefficient, C11, and Young's modulus, E11), of the cubic materials in the JARVIS-DFT database. The methodology aims to find the meso- scale (volume-averaged) material properties as a function of the underlying microstructure. Here, the microstructure is represented by the Orientation Distribution Function (ODF) that is discretized with a local finite element scheme and Rodrigues parameterization. The microstructure designs that minimize and maximize the mesoscale elastic properties are identified using a gradient- based optimization technique. Although the single crystal designs generally lead to the extreme values of the meso- scale properties, we have proposed both single crystal and polycrystal optimum solutions for the 4735 materials in the JARVIS database. This is because the polycrystals are advantageous for manufacturing and they also offer almost similar properties to the single crystal solutions. Next, the numerical optimization results are compared to the experimental data of the elastic parameters. The computed mesoscale properties in this work will openly be available for public access through the NIST-JARVIS repository( (https://jarvis.nist.gov/) and the Figshare repository (https://figshare.com/).

Citation

Integrating Materials and Manufacturing Innovation

Pub Type

Journals

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DOI Link

Keywords

Orientation distribution function, density functional theory

Citation

Choudhary, K. , Tavazza, F. , Hasan, M. and Acar, P. (2022), Multi-Scale Optimization for Elastic Properties of the Cubic Materials in JARVIS-DFT Database, Integrating Materials and Manufacturing Innovation, [online], https://doi.org/10.1007/s40192-022-00258-3 (Accessed April 18, 2024)