|About this Abstract
||2016 TMS Annual Meeting & Exhibition
||Computational Materials Discovery and Optimization: From 2D to Bulk Materials
||Exploring the Structure-composition Design Space in Multi-component Alloy Systems Using Nature Inspired Optimization Algorithms
||Aayush Sharma, Rahul Singh, Peter K. Liaw, Ganesh Balasubramanian
|On-Site Speaker (Planned)
Dissimilar elements arranged in different elemental compositions lead to multi-component alloy systems. Some of these materials have proven to have exceptional mechanical properties like strength and hardness, resistance to wear, fatigue, fracture, and corrosion. The structure-composition relationship in these materials influences the mechanical properties. Conventional design strategies employing experimental and computational resources for these materials have so far explored only a limited number of elemental compositions desired for high-strength application. We employ nature inspired heuristic optimization algorithms along with deterministic molecular-dynamics (MD) simulations to explore quenched multi-component alloy systems like AlCrCoFeNi for structural and deformation-tensile and compression characteristics, at high strain rates. Our investigation for the AlxCrCoFeNi alloy system has successfully predicted desired concentrations at which strength elevates from around 130 N/mm2 to above 200 N/mm2, using classical MD simulations coupled with an optimization algorithm. We aim to implement a similar simulation-optimization framework for different multi- principle element alloy systems.
||Planned: A print-only volume