Journal article
Mining of lattice distortion, strength, and intrinsic ductility of refractory high entropy alloys
NPJ COMPUTATIONAL MATERIALS, v 9(1), 53
05 Apr 2023
Abstract
Severe lattice distortion is a prominent feature of high-entropy alloys (HEAs) considered a reason for many of those alloys' properties. Nevertheless, accurate characterizations of lattice distortion are still scarce to only cover a tiny fraction of HEA's giant composition space due to the expensive experimental or computational costs. Here we present a physics-informed statistical model to efficiently produce high-throughput lattice distortion predictions for refractory non-dilute/high-entropy alloys (RHEAs) in a 10-element composition space. The model offers improved accuracy over conventional methods for fast estimates of lattice distortion by making predictions based on physical properties of interatomic bonding rather than atomic size mismatch of pure elements. The modeling of lattice distortion also implements a predictive model for yield strengths of RHEAs validated by various sets of experimental data. Combining our previous model on intrinsic ductility, a data mining design framework is demonstrated for efficient exploration of strong and ductile single-phase RHEAs.
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Details
- Title
- Mining of lattice distortion, strength, and intrinsic ductility of refractory high entropy alloys
- Publication Details
- NPJ COMPUTATIONAL MATERIALS, v 9(1), 53
- Publisher
- NATURE PORTFOLIO; BERLIN
- Grant note
- C.T. and Y.J.H. thank the financial support from the startup fund from Drexel University. L.Q. acknowledge the financial support from the National Science Foundation (NSF) Award DMR-1847837. P.K.L. very much appreciates the supports from (1) the National Science Foundation (DMR-1611180, 1809640, and 2226508) and (2) the US Army Research Office (W911NF-13-1-0438 and W911NF-19-2-0049). The computational support from the Drexel's University Research Computing Facility is greatly acknowledged. A part of the calculations was also carried out using the Extreme Science and Engineering Discovery Environment (XSEDE) Stampede2 at the TACC through allocation TG-DMR190035, and allocation MAT220033 from the Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support (ACCESS) program, which is supported by National Science Foundation Grants #2138259, #2138286, #2138307, #2137603, and #2138296.
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Drexel University
- Web of Science ID
- WOS:000964735100001
- Scopus ID
- 2-s2.0-85152634158
- Other Identifier
- 991021861169904721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Chemistry, Physical
- Materials Science, Multidisciplinary