{"title":"利用第一性原理和机器学习揭示g-SiC/Nb2CO2异质结构作为锂/钠离子存储阳极的电化学性能","authors":"Zihan Qiu, Lingxia Li, Wenbo Zhang, Junqiang Ren, Xin Guo, Xuefeng Lu","doi":"10.1016/j.apsusc.2025.163882","DOIUrl":null,"url":null,"abstract":"Heterojunction has achieved some breakthroughs in the performance aspects such as specific capacity, rate performance and service life through interface structure, charge coupling and interaction regulation, and has become a key regulatory means for high-performance electrode materials. Herein, a heterojunction combined g-SiC with Nb<sub>2</sub>CO<sub>2</sub> is established to systematically predict the electrochemical properties through first-principles calculations and machine learning. Based on the results of AIMD simulation at 300 K, it is found that the heterojunction has neither structural deformation nor bond breakage, revealing good thermodynamic stability. Moreover, the lowest diffusion barriers of Li and Na migration are 0.58 eV and 0.27 eV, with the open circuit voltage lowered 0.97 V and 0.18 V, and theoretical specific capacities of 910.54 mAh/g and 505.86 mAh/g, respectively. These findings indicate that g-SiC/Nb<sub>2</sub>CO<sub>2</sub> is a promising anode material for Li/Na batteries. Meanwhile, combining the characteristics and physical properties of atoms as descriptors for machine learning, their key influence on adsorption performance is explored, which provides valuable insights for the design of anode materials toward high-performance metal ion batteries in the future.","PeriodicalId":247,"journal":{"name":"Applied Surface Science","volume":"1 1","pages":""},"PeriodicalIF":6.3000,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Unlock the electrochemical performance of g-SiC/Nb2CO2 heterostructure as lithium/sodium ion storage anode with first-principles and machine learning\",\"authors\":\"Zihan Qiu, Lingxia Li, Wenbo Zhang, Junqiang Ren, Xin Guo, Xuefeng Lu\",\"doi\":\"10.1016/j.apsusc.2025.163882\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Heterojunction has achieved some breakthroughs in the performance aspects such as specific capacity, rate performance and service life through interface structure, charge coupling and interaction regulation, and has become a key regulatory means for high-performance electrode materials. Herein, a heterojunction combined g-SiC with Nb<sub>2</sub>CO<sub>2</sub> is established to systematically predict the electrochemical properties through first-principles calculations and machine learning. Based on the results of AIMD simulation at 300 K, it is found that the heterojunction has neither structural deformation nor bond breakage, revealing good thermodynamic stability. Moreover, the lowest diffusion barriers of Li and Na migration are 0.58 eV and 0.27 eV, with the open circuit voltage lowered 0.97 V and 0.18 V, and theoretical specific capacities of 910.54 mAh/g and 505.86 mAh/g, respectively. These findings indicate that g-SiC/Nb<sub>2</sub>CO<sub>2</sub> is a promising anode material for Li/Na batteries. Meanwhile, combining the characteristics and physical properties of atoms as descriptors for machine learning, their key influence on adsorption performance is explored, which provides valuable insights for the design of anode materials toward high-performance metal ion batteries in the future.\",\"PeriodicalId\":247,\"journal\":{\"name\":\"Applied Surface Science\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":6.3000,\"publicationDate\":\"2025-06-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Surface Science\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://doi.org/10.1016/j.apsusc.2025.163882\",\"RegionNum\":2,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CHEMISTRY, PHYSICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Surface Science","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1016/j.apsusc.2025.163882","RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
Unlock the electrochemical performance of g-SiC/Nb2CO2 heterostructure as lithium/sodium ion storage anode with first-principles and machine learning
Heterojunction has achieved some breakthroughs in the performance aspects such as specific capacity, rate performance and service life through interface structure, charge coupling and interaction regulation, and has become a key regulatory means for high-performance electrode materials. Herein, a heterojunction combined g-SiC with Nb2CO2 is established to systematically predict the electrochemical properties through first-principles calculations and machine learning. Based on the results of AIMD simulation at 300 K, it is found that the heterojunction has neither structural deformation nor bond breakage, revealing good thermodynamic stability. Moreover, the lowest diffusion barriers of Li and Na migration are 0.58 eV and 0.27 eV, with the open circuit voltage lowered 0.97 V and 0.18 V, and theoretical specific capacities of 910.54 mAh/g and 505.86 mAh/g, respectively. These findings indicate that g-SiC/Nb2CO2 is a promising anode material for Li/Na batteries. Meanwhile, combining the characteristics and physical properties of atoms as descriptors for machine learning, their key influence on adsorption performance is explored, which provides valuable insights for the design of anode materials toward high-performance metal ion batteries in the future.
期刊介绍:
Applied Surface Science covers topics contributing to a better understanding of surfaces, interfaces, nanostructures and their applications. The journal is concerned with scientific research on the atomic and molecular level of material properties determined with specific surface analytical techniques and/or computational methods, as well as the processing of such structures.