Sigma Phase Stabilization by Nb Doping in a New High-Entropy Alloy in the FeCrMnNiCu System: A Study of Phase Prediction and Nanomechanical Response
The development of high-entropy alloys has been hampered by the challenge of effectively and verifiably predicting phases using predictive methods for functional design. This study validates remarkable phase prediction capability in complex multicomponent alloys by microstructurally predicting two n...
| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-01-01
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| Series: | Metals |
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| Online Access: | https://www.mdpi.com/2075-4701/14/1/74 |
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| author | Angelo Oñate Juan Pablo Sanhueza Gleydis Dueña Diego Wackerling Sergio Sauceda Christopher Salvo Marian Valenzuela Carlos Medina Abdul Herrim Seidou Jérôme Tchoufang Tchuindjang Manuel Meléndrez David Rojas Anne Mertens Víctor Tuninetti |
| author_facet | Angelo Oñate Juan Pablo Sanhueza Gleydis Dueña Diego Wackerling Sergio Sauceda Christopher Salvo Marian Valenzuela Carlos Medina Abdul Herrim Seidou Jérôme Tchoufang Tchuindjang Manuel Meléndrez David Rojas Anne Mertens Víctor Tuninetti |
| author_sort | Angelo Oñate |
| collection | DOAJ |
| description | The development of high-entropy alloys has been hampered by the challenge of effectively and verifiably predicting phases using predictive methods for functional design. This study validates remarkable phase prediction capability in complex multicomponent alloys by microstructurally predicting two novel high-entropy alloys in the FCC + BCC and FCC + BCC + IM systems using a novel analytical method based on valence electron concentration (VEC). The results are compared with machine learning, CALPHAD, and experimental data. The key findings highlight the high predictive accuracy of the analytical method and its strong correlation with more intricate prediction methods such as random forest machine learning and CALPHAD. Furthermore, the experimental results validate the predictions with a range of techniques, including SEM-BSE, EDS, elemental mapping, XRD, microhardness, and nanohardness measurements. This study reveals that the addition of Nb enhances the formation of the sigma (σ) intermetallic phase, resulting in increased alloy strength, as demonstrated by microhardness and nanohardness measurements. Lastly, the overlapping VEC ranges in high-entropy alloys are identified as potential indicators of phase transitions at elevated temperatures. |
| first_indexed | 2024-03-08T10:40:54Z |
| format | Article |
| id | doaj.art-fcd68321f83242f1816bb4bdb47437df |
| institution | Directory Open Access Journal |
| issn | 2075-4701 |
| language | English |
| last_indexed | 2024-03-08T10:40:54Z |
| publishDate | 2024-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Metals |
| spelling | doaj.art-fcd68321f83242f1816bb4bdb47437df2024-01-26T17:41:12ZengMDPI AGMetals2075-47012024-01-011417410.3390/met14010074Sigma Phase Stabilization by Nb Doping in a New High-Entropy Alloy in the FeCrMnNiCu System: A Study of Phase Prediction and Nanomechanical ResponseAngelo Oñate0Juan Pablo Sanhueza1Gleydis Dueña2Diego Wackerling3Sergio Sauceda4Christopher Salvo5Marian Valenzuela6Carlos Medina7Abdul Herrim Seidou8Jérôme Tchoufang Tchuindjang9Manuel Meléndrez10David Rojas11Anne Mertens12Víctor Tuninetti13Department of Materials Engineering, Faculty of Engineering, Universidad de Concepción, Edmundo Larenas 315, Concepción 4070138, ChileDepartment of Materials Engineering, Faculty of Engineering, Universidad de Concepción, Edmundo Larenas 315, Concepción 4070138, ChileDepartment of Materials Engineering, Faculty of Engineering, Universidad de Concepción, Edmundo Larenas 315, Concepción 4070138, ChileDepartment of Materials Engineering, Faculty of Engineering, Universidad de Concepción, Edmundo Larenas 315, Concepción 4070138, ChileDepartment of Materials Engineering, Faculty of Engineering, Universidad de Concepción, Edmundo Larenas 315, Concepción 4070138, ChileDepartment of Mechanical Engineering, Faculty of Engineering, Universidad del Bío–Bío, Av. Collao 1202, Concepción 4081112, ChileDoctoral Program in Sciences of Natural Resources, Universidad de La Frontera, Casilla 54-D, Temuco 4811230, ChileDepartment of Mechanical Engineering, Faculty of Engineering, Universidad de Concepción, Edmundo Larenas 219, Concepción 4070138, ChileDepartment A&M–MMS, University of Liège, 4000 Liège, BelgiumDepartment A&M–MMS, University of Liège, 4000 Liège, BelgiumDepartment of Materials Engineering, Faculty of Engineering, Universidad de Concepción, Edmundo Larenas 315, Concepción 4070138, ChileDepartment of Materials Engineering, Faculty of Engineering, Universidad de Concepción, Edmundo Larenas 315, Concepción 4070138, ChileDepartment A&M–MMS, University of Liège, 4000 Liège, BelgiumDepartment of Mechanical Engineering, Universidad de La Frontera, Francisco Salazar 01145, Temuco 4811230, ChileThe development of high-entropy alloys has been hampered by the challenge of effectively and verifiably predicting phases using predictive methods for functional design. This study validates remarkable phase prediction capability in complex multicomponent alloys by microstructurally predicting two novel high-entropy alloys in the FCC + BCC and FCC + BCC + IM systems using a novel analytical method based on valence electron concentration (VEC). The results are compared with machine learning, CALPHAD, and experimental data. The key findings highlight the high predictive accuracy of the analytical method and its strong correlation with more intricate prediction methods such as random forest machine learning and CALPHAD. Furthermore, the experimental results validate the predictions with a range of techniques, including SEM-BSE, EDS, elemental mapping, XRD, microhardness, and nanohardness measurements. This study reveals that the addition of Nb enhances the formation of the sigma (σ) intermetallic phase, resulting in increased alloy strength, as demonstrated by microhardness and nanohardness measurements. Lastly, the overlapping VEC ranges in high-entropy alloys are identified as potential indicators of phase transitions at elevated temperatures.https://www.mdpi.com/2075-4701/14/1/74phase predictionsigma phasemachine learninghigh-entropy alloys |
| spellingShingle | Angelo Oñate Juan Pablo Sanhueza Gleydis Dueña Diego Wackerling Sergio Sauceda Christopher Salvo Marian Valenzuela Carlos Medina Abdul Herrim Seidou Jérôme Tchoufang Tchuindjang Manuel Meléndrez David Rojas Anne Mertens Víctor Tuninetti Sigma Phase Stabilization by Nb Doping in a New High-Entropy Alloy in the FeCrMnNiCu System: A Study of Phase Prediction and Nanomechanical Response Metals phase prediction sigma phase machine learning high-entropy alloys |
| title | Sigma Phase Stabilization by Nb Doping in a New High-Entropy Alloy in the FeCrMnNiCu System: A Study of Phase Prediction and Nanomechanical Response |
| title_full | Sigma Phase Stabilization by Nb Doping in a New High-Entropy Alloy in the FeCrMnNiCu System: A Study of Phase Prediction and Nanomechanical Response |
| title_fullStr | Sigma Phase Stabilization by Nb Doping in a New High-Entropy Alloy in the FeCrMnNiCu System: A Study of Phase Prediction and Nanomechanical Response |
| title_full_unstemmed | Sigma Phase Stabilization by Nb Doping in a New High-Entropy Alloy in the FeCrMnNiCu System: A Study of Phase Prediction and Nanomechanical Response |
| title_short | Sigma Phase Stabilization by Nb Doping in a New High-Entropy Alloy in the FeCrMnNiCu System: A Study of Phase Prediction and Nanomechanical Response |
| title_sort | sigma phase stabilization by nb doping in a new high entropy alloy in the fecrmnnicu system a study of phase prediction and nanomechanical response |
| topic | phase prediction sigma phase machine learning high-entropy alloys |
| url | https://www.mdpi.com/2075-4701/14/1/74 |
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