About this Abstract |
Meeting |
MS&T22: Materials Science & Technology
|
Symposium
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High Entropy Materials: Concentrated Solid Solutions, Intermetallics, Ceramics, Functional Materials and Beyond III
|
Presentation Title |
Towards to an ICME Approach for the Discovery of the Lightweight High Entropy Alloys |
Author(s) |
Shengyen Li, Jianliang Lin, John Macha, Mirella Vargas, Michael A Miller |
On-Site Speaker (Planned) |
Shengyen Li |
Abstract Scope |
This presentation will discuss the feasibility of integrating high throughput experiments (HTE) with computational approaches to discover composition spaces for lightweight high entropy alloys (LHEAs). The objectives are to reduce density by 25% while the mechanical properties comparable to Ni-based superalloys for high temperature applications. To explore the potential space cost-effectively, the first iteration of the material discovery focuses on data gathering, knowledge managing, and design of experiments. A data-handling tool is developed to parse, analyze, and save data from literatures and experiments. The statistical functions and machine learning algorithms follow the data gathering to clean-up and map-out high dimensional information for the development of the alloy-structure-properties relationships in an effective fashion. This informatics system also integrates with a preliminary modeling hierarchy and Monte Carlo tool to select the potential composition space for the subsequent high throughput experimentations. The outcomes guide the iterative experiments to achieve the goal of discovery. |