journal article·2025-06

A high-throughput physics- and data-driven framework for High-Entropy Alloy development

Shardul Kamat, Victoria Tucker, Michael S. Titus, Gregory J. Wagner

Acta Materialia· Volume 292
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Abstract

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Research context

OpenAlex topics: High Entropy Alloys Studies · Additive Manufacturing Materials and Processes · Advanced Materials Characterization Techniques

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References (59)

Show source-provided references
1. Nanostructured high-entropy alloys with multiple principal elements: Novel alloy design concepts and outcomes10.1002/adem.200300567 ↗
2. Mechanical properties of nb25mo25ta25w25 and v20nb20mo20ta20w20 refractory high entropy alloys10.1016/j.intermet.2011.01.004 ↗
3. Solid-solution strengthening in refractory high entropy alloys10.1016/j.actamat.2019.06.006 ↗
4. Cooperative deformation in high-entropy alloys at ultralow temperatures10.1126/sciadv.aax4002 ↗
5. A novel low-density, high-hardness, high-entropy alloy with close-packed single-phase nanocrystalline structures10.1080/21663831.2014.985855 ↗
6. High-throughput rapid experimental alloy development (ht-read)10.1016/j.actamat.2021.117352 ↗
7. A titanium alloys design method based on high-throughput experiments and machine learning10.1016/j.jmrt.2021.02.055 ↗
8. High-throughput experiment-assisted study of the alloying effects on oxidation of nb-based alloys10.1016/j.corsci.2022.110383 ↗
9. Accelerated development of hard high-entropy alloys with data-driven high-throughput experiments
10. High entropy alloys towards industrial applications: High-throughput screening and experimental investigation10.1016/j.msea.2021.142297 ↗
11. High throughput synthesis enabled exploration of cocrfeni-based high entropy alloys10.1016/j.jmst.2021.09.031 ↗
12. A critical review of high entropy alloys and related concepts10.1016/j.actamat.2016.08.081 ↗
13. A perspective on bayesian methods applied to materials discovery and design10.1557/s43579-022-00288-0 ↗
14. Hierarchical gaussian process-based bayesian optimization for materials discovery in high entropy alloy spaces10.1016/j.actamat.2025.120908 ↗
15. Two-shot optimization of compositionally complex refractory alloys10.1016/j.actamat.2025.120820 ↗
16. Current application status of multi-scale simulation and machine learning in research on high-entropy alloys10.1016/j.jmrt.2023.07.233 ↗
17. High-entropy alloy: challenges and prospects10.1016/j.mattod.2015.11.026 ↗
18. Accelerated design of high entropy alloys by integrating high throughput calculation and machine learning10.1016/j.jallcom.2023.170543 ↗
19. The eutectic compositional space in al-cr-fe-ni system utilizing the high-throughput calphad approach10.1016/j.scriptamat.2024.116178 ↗
20. Search for eutectic high entropy alloys by integrating high-throughput calphad
21. The need for reliable data in computational thermodynamics10.32908/hthp.v49.853 ↗
22. First-principles calculations and CALPHAD modeling of thermodynamics10.1007/s11669-009-9570-6 ↗
23. Saunders · 1998
24. Calphad-aided design for superior thermal stability and mechanical behavior in a tizrhfnb refractory high-entropy alloy10.1016/j.actamat.2023.118728 ↗
25. Database on the mechanical properties of high entropy alloys and complex concentrated alloys10.1016/j.dib.2018.11.111 ↗
26. Combinatorial processing and evaluation of the phase evolution and oxidation behavior of hf-al-si refractory complex concentrated alloys10.1016/j.actamat.2024.120114 ↗
27. Multi-constraint high-throughput design, synthesis, and characterization of tungsten-containing refractory multi-principal element alloys10.1016/j.actamat.2024.120379 ↗
28. The CALPHAD approach for HEAs: Challenges and opportunities10.1557/s43577-022-00284-8 ↗
29. Calphad design and high-throughput search of novel ni-based superalloys that are reinforced by γ′+γ′′
30. Mapping the world of complex concentrated alloys10.1016/j.actamat.2017.06.027 ↗
31. Modeling oxidation of alcocrfeni high-entropy alloy using stochastic cellular automata10.3390/e24091263 ↗
32. Predicting grain structure in high pressure die casting of aluminum alloys: A coupled cellular automaton and process model10.1016/j.commatsci.2019.01.029 ↗
33. Improved grain structure prediction in metal additive manufacturing using a dynamic kinetic Monte Carlo framework
34. Simulation of metal additive manufacturing microstructures using kinetic monte carlo10.1016/j.commatsci.2017.03.053 ↗
35. Phase-field simulation of coherent bcc/b2 microstructures in high entropy alloys10.1016/j.actamat.2020.07.030 ↗
36. Microstructural design via spinodal-mediated phase transformation pathways in high-entropy alloys (heas) using phase-field modelling10.1016/j.actamat.2022.118438 ↗
37. Process-structure linkages using a data science approach: Application to simulated additive manufacturing data10.1007/s40192-017-0088-1 ↗
38. Accelerating phase-field-based microstructure evolution predictions via surrogate models trained by machine learning methods10.1038/s41524-020-00471-8 ↗
39. A data-driven surrogate model to rapidly predict microstructure morphology during physical vapor deposition10.1016/j.apm.2020.06.046 ↗
40. A novel physics-regularized interpretable machine learning model for grain growth10.1016/j.matdes.2022.111032 ↗
41. Microstructure of two-phase random media. i. the n point probability functions10.1063/1.444011 ↗
42. Reconstructing random media10.1103/PhysRevE.57.495 ↗
43. Microstructure reconstructions from 2-point statistics using phase-recovery algorithms10.1016/j.actamat.2007.10.044 ↗
44. Digital polycrystalline microstructure generation using diffusion probabilistic models10.1016/j.mtla.2023.101976 ↗
45. 2023
46. V. Tucker, A. Bejjipurapu, A. Hernandez, M. Titus, pyTCPlotter URL https://github.itap.purdue.edu/michaeltitusgroup/pyTCPlotter.
47. Texture analysis with mtex – free and open source software toolbox
48. ANSYS · 2024
49. A 3d cellular automaton algorithm for the prediction of dendritic grain growth10.1016/S1359-6454(96)00303-5 ↗
50. A three-dimensional cellular automation-finite element model for the prediction of solidification grain structures10.1007/s11661-999-0226-2 ↗
51. Steady state columnar and equiaxed growth of dendrites and eutectic10.1016/0025-5416(84)90201-5 ↗
52. Calibration of cellular automaton model for microstructure prediction in additive manufacturing using dissimilarity score10.1115/1.4056690 ↗
53. The Jensen-Shannon divergence10.1016/S0016-0032(96)00063-4 ↗
54. Use of Sobol’s quasirandom sequence generator for integration of modified uncertainty importance measure10.1080/18811248.1995.9731832 ↗
55. Who belongs in the family?10.1007/BF02289263 ↗
56. Unsupervised clustering for identifying spatial inhomogeneity on local electronic structures10.1038/s41535-021-00407-5 ↗
57. A sensitivity analysis of the columnar-to-equiaxed transition for ni-based superalloys in electron beam additive manufacturing10.1016/j.commatsci.2018.08.064 ↗
58. A simplex method for function minimization10.1093/comjnl/7.4.308 ↗
59. Empowering faculty: A campus cyberinfrastructure strategy for research communities