{"title":"机器学习辅助设计具有增强硬度的crtativ基耐火高熵合金","authors":"Liang Li, Shu Wang, Chen Su, Shengfeng Guo","doi":"10.1016/j.ijrmhm.2025.107400","DOIUrl":null,"url":null,"abstract":"<div><div>Refractory high entropy alloys (RHEAs) with enhanced hardness exhibit superior performance. However, traditional trial-and-error methods could be time-consuming and inefficient facing the enormous compositional space. In this paper, machine learning (ML) was utilized to design RHEAs with enhanced hardness. Several candidate alloys were selected by high-throughput screening and verified. The hardness of Cr<sub>45</sub>Ta<sub>21</sub>Ti<sub>20</sub>V<sub>14</sub> is up to 1074 HV, which is 33.4 % higher than the maximum value (805 HV) in the database. Moreover, the Shapley additive explanation (SHAP) was introduced to further comprehend the model interpretability.</div></div>","PeriodicalId":14216,"journal":{"name":"International Journal of Refractory Metals & Hard Materials","volume":"133 ","pages":"Article 107400"},"PeriodicalIF":4.6000,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Machine learning assisted design of CrTaTiV-based refractory high entropy alloys with enhanced hardness\",\"authors\":\"Liang Li, Shu Wang, Chen Su, Shengfeng Guo\",\"doi\":\"10.1016/j.ijrmhm.2025.107400\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Refractory high entropy alloys (RHEAs) with enhanced hardness exhibit superior performance. However, traditional trial-and-error methods could be time-consuming and inefficient facing the enormous compositional space. In this paper, machine learning (ML) was utilized to design RHEAs with enhanced hardness. Several candidate alloys were selected by high-throughput screening and verified. The hardness of Cr<sub>45</sub>Ta<sub>21</sub>Ti<sub>20</sub>V<sub>14</sub> is up to 1074 HV, which is 33.4 % higher than the maximum value (805 HV) in the database. Moreover, the Shapley additive explanation (SHAP) was introduced to further comprehend the model interpretability.</div></div>\",\"PeriodicalId\":14216,\"journal\":{\"name\":\"International Journal of Refractory Metals & Hard Materials\",\"volume\":\"133 \",\"pages\":\"Article 107400\"},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2025-08-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Refractory Metals & Hard Materials\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0263436825003658\",\"RegionNum\":2,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Refractory Metals & Hard Materials","FirstCategoryId":"88","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0263436825003658","RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
Machine learning assisted design of CrTaTiV-based refractory high entropy alloys with enhanced hardness
Refractory high entropy alloys (RHEAs) with enhanced hardness exhibit superior performance. However, traditional trial-and-error methods could be time-consuming and inefficient facing the enormous compositional space. In this paper, machine learning (ML) was utilized to design RHEAs with enhanced hardness. Several candidate alloys were selected by high-throughput screening and verified. The hardness of Cr45Ta21Ti20V14 is up to 1074 HV, which is 33.4 % higher than the maximum value (805 HV) in the database. Moreover, the Shapley additive explanation (SHAP) was introduced to further comprehend the model interpretability.
期刊介绍:
The International Journal of Refractory Metals and Hard Materials (IJRMHM) publishes original research articles concerned with all aspects of refractory metals and hard materials. Refractory metals are defined as metals with melting points higher than 1800 °C. These are tungsten, molybdenum, chromium, tantalum, niobium, hafnium, and rhenium, as well as many compounds and alloys based thereupon. Hard materials that are included in the scope of this journal are defined as materials with hardness values higher than 1000 kg/mm2, primarily intended for applications as manufacturing tools or wear resistant components in mechanical systems. Thus they encompass carbides, nitrides and borides of metals, and related compounds. A special focus of this journal is put on the family of hardmetals, which is also known as cemented tungsten carbide, and cermets which are based on titanium carbide and carbonitrides with or without a metal binder. Ceramics and superhard materials including diamond and cubic boron nitride may also be accepted provided the subject material is presented as hard materials as defined above.