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RESEARCH PAPER · Acta Materialia · 2024

Multi-objective, multi-constraint high-throughput design, synthesis, and characterization of tungsten-containing refractory multi-principal element alloys

Cafer Acemi, Brent Vela, Eli Norris, William Trehern, Kadri Can Atli, C. Cleek, Raymundo Arróyave, İbrahim Karaman

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Multi-objective, multi-constraint high-throughput design, synthesis, and characterization of tungsten-containing refractory multi-principal element alloysOriginalData-augmented modeling in laser powder bed fusion: A Bayesian approach4Visualizing high entropy alloy spaces: methods and best practices13Compositionally Grading Alloy Stacking Fault Energy Using Autonomous Path Planning and Additive Manufacturing with Elemental Powders1Physics-informed Gaussian process classification for constraint-aware alloy design5Supply risk-aware alloy discovery and design: A case study on the MoNbTiVW system5Screening the TiZrHfNbVMoTa refractory high-entropy alloys with multi-property constraints7Two-shot optimization of compositionally complex refractory alloys13A high-throughput physics- and data-driven framework for High-Entropy Alloy development5Design of refractory complex concentrated alloys combining good tensile strength and ductility at 22–1000 °C6Computational studies on BCC superalloys6Machine learning-driven design of high-entropy alloys: Phase prediction, performance optimization, and challenges19Enhanced strain hardening response of multi-principal element alloys with L12 nanodomains designed for multiple objectives and constraints0Accelerated multi-objective alloy discovery through efficient bayesian methods: Application to the FCC high entropy alloy space21Design of high-hardness complex concentrated alloys from physics, machine learning, and experiments2Accelerated discovery through multi-property screening strategy: Achieving strength-ductility synergy in TiZrHfNbMoTa RHEAs4Leveraging domain knowledge for optimal initialization in Bayesian materials optimization1DuctGPT: A Generative Transformer for Forward Screening of Ductile Refractory Multi-Principal Element Alloys7A two-step high-throughput design strategy of refractory medium-entropy composites with strength-plasticity synergy from room temperature to 2000 °C2Current research status on the effects of processing and composition design of refractory high-entropy alloys on performance10A Machine Learning Approach to Assessing Printability of High Entropy Alloys for Laser Powder Bed Fusion0Machine learning-driven closed-loop discovery of hard multiple principal element alloys2Metallurgy-informed Bayesian optimization: rethinking alloy discovery and design0Design of shape memory alloys with enhanced thermal management properties via adaptively constrained multi-objective optimization8Compositionally grading alloy stacking fault energy using autonomous path planning and additive manufacturing with elemental powders2Deep Gaussian process-based cost-aware batch Bayesian optimization for complex materials design campaigns3A novel data-driven strategy for rapid design of synergistic heat treatment in titanium bimetal1Data-driven design of Nb-W refractory alloys using Transformer-based stress-strain modeling1Machine learning driven discovery of low modulus biomedical titanium alloys for additive manufacturing11Discovering a strong and ductile Mo–Nb–Ta–V–W refractory multi-principal element alloy using surrogate-based optimization with computational data2Tuning Aluminum Content to Enhance Stress Rupture Properties of High‐Tungsten Superalloy0A comprehensive study on the room-temperature rolling and tensile ductility of refractory high-entropy alloys3High-temperature tensile properties of thermo-mechanically processed equiatomic NbTaV refractory alloy0Microstructure evolution and strengthening mechanism of ultrahigh temperature W-Nb-Zr alloy manufactured by laser coupled electromagnetic levitation0Wear and cavitation erosion of ultrasonic-induction assisted laser directed energy deposition NbMoTaWV coatings on 316Ti0Compositional modulation enables crack suppression through grain refinement in laser powder bed fusion W-Nb0Spot melting of ultra-dense tungsten via electron beam powder bed fusion: A reproducible fabrication strategy0Toward autonomous experimentation: Bayesian optimization over problem formulation space for accelerated alloy development0High-throughput design of refractory multi principal element alloys for laser processing1Machine learning-enabled discovery of refractory high entropy alloys on curated data0Data-driven analysis of molten pool morphology and porosity formation in laser powder bed fusion via integrated DEM-CFD and machine learning2Linking Dislocation Mobility, Compatible Heterogeneity and Service Stability in NbTaV-Containing and Related BCC Refractory High- and Medium-Entropy Alloys0Unveiling keyhole-induced porosity and grain orientation in laser powder bed fusion (LPBF) of maraging 300 steel through coupled computational fluid dynamics and cellular automaton0Physics-informed residual learning for high-temperature yield-strength prediction in refractory BCC HEAs0

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  1. Data-augmented modeling in laser powder bed fusion: A Bayesian approach

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  2. Visualizing high entropy alloy spaces: methods and best practices

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  3. Compositionally Grading Alloy Stacking Fault Energy Using Autonomous Path Planning and Additive Manufacturing with Elemental Powders

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  4. Physics-informed Gaussian process classification for constraint-aware alloy design

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  5. Supply risk-aware alloy discovery and design: A case study on the MoNbTiVW system

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  6. Screening the TiZrHfNbVMoTa refractory high-entropy alloys with multi-property constraints

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  7. Two-shot optimization of compositionally complex refractory alloys

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

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  9. Design of refractory complex concentrated alloys combining good tensile strength and ductility at 22–1000 °C

    International Journal of Refractory Metals and Hard Materials · 2025-05-24

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  10. Computational studies on BCC superalloys

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  12. Enhanced strain hardening response of multi-principal element alloys with L12 nanodomains designed for multiple objectives and constraints

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  13. Accelerated multi-objective alloy discovery through efficient bayesian methods: Application to the FCC high entropy alloy space

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  14. Design of high-hardness complex concentrated alloys from physics, machine learning, and experiments

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  15. Accelerated discovery through multi-property screening strategy: Achieving strength-ductility synergy in TiZrHfNbMoTa RHEAs

    International Journal of Refractory Metals and Hard Materials · 2025-09-01

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  16. Leveraging domain knowledge for optimal initialization in Bayesian materials optimization

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  17. DuctGPT: A Generative Transformer for Forward Screening of Ductile Refractory Multi-Principal Element Alloys

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    Sai Pranav Reddy Guduru, Mkpe O. Kekung, Ryan Timothy Ott, Sougata Roy, Prashant Kumar Singh

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  18. A two-step high-throughput design strategy of refractory medium-entropy composites with strength-plasticity synergy from room temperature to 2000 °C

    Journal of Material Science and Technology · 2025-12-02

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  19. Current research status on the effects of processing and composition design of refractory high-entropy alloys on performance

    Journal of Alloys and Compounds · 2025-12-06

    Guofu Lian, Bojin Wang, Weibo Gao, Changrong Chen, Meiyan Feng, Chenmin Zhao

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  20. A Machine Learning Approach to Assessing Printability of High Entropy Alloys for Laser Powder Bed Fusion

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  21. Machine learning-driven closed-loop discovery of hard multiple principal element alloys

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  22. Metallurgy-informed Bayesian optimization: rethinking alloy discovery and design

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  23. Design of shape memory alloys with enhanced thermal management properties via adaptively constrained multi-objective optimization

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  24. Compositionally grading alloy stacking fault energy using autonomous path planning and additive manufacturing with elemental powders

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  25. Deep Gaussian process-based cost-aware batch Bayesian optimization for complex materials design campaigns

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  26. A novel data-driven strategy for rapid design of synergistic heat treatment in titanium bimetal

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  27. Data-driven design of Nb-W refractory alloys using Transformer-based stress-strain modeling

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  28. Machine learning driven discovery of low modulus biomedical titanium alloys for additive manufacturing

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  29. Discovering a strong and ductile Mo–Nb–Ta–V–W refractory multi-principal element alloy using surrogate-based optimization with computational data

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  30. Tuning Aluminum Content to Enhance Stress Rupture Properties of High‐Tungsten Superalloy

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  32. High-temperature tensile properties of thermo-mechanically processed equiatomic NbTaV refractory alloy

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  33. Microstructure evolution and strengthening mechanism of ultrahigh temperature W-Nb-Zr alloy manufactured by laser coupled electromagnetic levitation

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  34. Wear and cavitation erosion of ultrasonic-induction assisted laser directed energy deposition NbMoTaWV coatings on 316Ti

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  35. Compositional modulation enables crack suppression through grain refinement in laser powder bed fusion W-Nb

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  36. Spot melting of ultra-dense tungsten via electron beam powder bed fusion: A reproducible fabrication strategy

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  37. Toward autonomous experimentation: Bayesian optimization over problem formulation space for accelerated alloy development

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  41. Linking Dislocation Mobility, Compatible Heterogeneity and Service Stability in NbTaV-Containing and Related BCC Refractory High- and Medium-Entropy Alloys

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  42. Unveiling keyhole-induced porosity and grain orientation in laser powder bed fusion (LPBF) of maraging 300 steel through coupled computational fluid dynamics and cellular automaton

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  43. Physics-informed residual learning for high-temperature yield-strength prediction in refractory BCC HEAs

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