|About this Abstract
||2018 TMS Annual Meeting & Exhibition
||Computational Materials Discovery and Optimization
||Tailoring Properties in Multi-component Alloys through Heuristic Optimization
||Aayush Sharma, Rahul Singh, Ganesh Balasubramanian
|On-Site Speaker (Planned)
Multi-component alloys have recently shown tremendous applications as they inherit superior strength and hardness, resistance to wear, fatigue and corrosion. The structure-composition relationship in these materials is often complex and greatly influences its mechanical and electrical/thermal properties. Conventional design strategy employing experimental and analytical/computational resources, for these materials are often limited in designing tailored alloy compositions. We employ an adaptive cuckoo search optimization algorithm along side deterministic molecular dynamics simulation to explore design of multi-component alloys for multi-functional capabilities. Our design strategy has the potential to predict specific individual elemental compositions that tailors different desired properties in such alloy systems. Heuristic optimization techniques have proven to be effective when design space is multi-modal. Our previous investigation for AlxCoCrFeNi alloy system has successfully predicted desired concentrations for strength elevation. We aim to extend the framework to develop a parameter free optimization framework for exploring complex alloy systems with multi-functional capabilities.
||Planned: Supplemental Proceedings volume