High-Throughput Experimentally and Computationally Guided Discovery of Next Generation High-Temperature Shape Memory Alloys
Abstract
We have developed a framework for the discovery of novel high-temperature shape memory alloys by combining high-throughput experimental techniques, high-throughput computational methods, and statistical analysis/machine learning techniques. We have fabricated a novel resistance sensor array for the combinatorial screening of shape memory alloys, built a binary alloy database, and developed an efficient experiment design technique. An in-depth experimental-computational study on a broad range of Cu-Zr-X shape memory alloys shows that DFT simulations are a useful tool to guide the experimental development of shape memory alloys provided relevant energy terms are taken into account.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jul 31, 2019
- Accession Number
- AD1096609
Entities
People
- Joost J Vlassak
- Raymundo Arróyave
Organizations
- Harvard University