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一种用于材料设计的计算框架。

A Computational Framework for Material Design.

作者信息

Li Shengyen, Kattner Ursula R, Campbell Carelyn E

机构信息

1NIST/Materials Science and Engineering Division, 100 Bureau Dr. Stop 8555, Gaithersburg, MD 20899-8555 USA.

2Theiss Research, La Jolla, CA USA.

出版信息

Integr Mater Manuf Innov. 2017;6(3):229-248. doi: 10.1007/s40192-017-0101-8. Epub 2017 Aug 31.

Abstract

A computational framework is proposed that enables the integration of experimental and computational data, a variety of user-selected models, and a computer algorithm to direct a design optimization. To demonstrate this framework, a sample design of a ternary Ni-Al-Cr alloy with a high work-to-necking ratio is presented. This design example illustrates how CALPHAD phase-based, composition and temperature-dependent phase equilibria calculations and precipitation models are coupled with models for elastic and plastic deformation to calculate the stress-strain curves. A genetic algorithm then directs the search within a specific set of composition and processing constraints for the ideal composition and processing profile to optimize the mechanical properties. The initial demonstration of the framework provides a potential solution to initiate the material design process in a large space of composition and processing conditions. This framework can also be used in similar material systems or adapted for other material classes.

摘要

提出了一个计算框架,该框架能够集成实验数据和计算数据、各种用户选择的模型以及一种计算机算法,以指导设计优化。为了演示这个框架,给出了一个具有高缩颈功比的三元镍 - 铝 - 铬合金的示例设计。这个设计示例说明了基于CALPHAD相图、成分和温度相关的相平衡计算以及析出模型是如何与弹性和塑性变形模型相结合来计算应力 - 应变曲线的。然后,遗传算法在一组特定的成分和加工约束条件下进行搜索,以寻找理想的成分和加工方案,从而优化力学性能。该框架的初步演示为在成分和加工条件的大空间中启动材料设计过程提供了一个潜在的解决方案。这个框架也可以用于类似的材料系统,或适用于其他材料类别。

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本文引用的文献

1
Optimizing core-shell nanoparticle catalysts with a genetic algorithm.
J Chem Phys. 2009 Dec 21;131(23):234103. doi: 10.1063/1.3272274.
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