{"title":"Na[Mn0.36Ni0.44Ti0.15Fe0.05]O2 predicted via machine learning for high energy Na-ion batteries†","authors":"Saaya Sekine, Tomooki Hosaka, Hayato Maejima, Ryoichi Tatara, Masanobu Nakayama and Shinichi Komaba","doi":"10.1039/D4TA04809A","DOIUrl":null,"url":null,"abstract":"<p >We optimize the composition of transition metal layered oxides for high energy Na-ion batteries using machine learning (ML) trained by our experimental data. The ML models predict their electrochemical performance and suggest promising compositions of quaternary Na[Ni,Mn,Fe,Ti]O<small><sub>2</sub></small>. Accordingly, we synthesized Na[Mn<small><sub>0.36</sub></small>Ni<small><sub>0.44</sub></small>Ti<small><sub>0.15</sub></small>Fe<small><sub>0.05</sub></small>]O<small><sub>2</sub></small> which achieves a high energy density of 549 W h per kg of active material, agreeing with the predicted value.</p>","PeriodicalId":82,"journal":{"name":"Journal of Materials Chemistry A","volume":" 45","pages":" 31103-31107"},"PeriodicalIF":10.7000,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.rsc.org/en/content/articlepdf/2024/ta/d4ta04809a?page=search","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Materials Chemistry A","FirstCategoryId":"88","ListUrlMain":"https://pubs.rsc.org/en/content/articlelanding/2024/ta/d4ta04809a","RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
引用次数: 0
Abstract
We optimize the composition of transition metal layered oxides for high energy Na-ion batteries using machine learning (ML) trained by our experimental data. The ML models predict their electrochemical performance and suggest promising compositions of quaternary Na[Ni,Mn,Fe,Ti]O2. Accordingly, we synthesized Na[Mn0.36Ni0.44Ti0.15Fe0.05]O2 which achieves a high energy density of 549 W h per kg of active material, agreeing with the predicted value.
期刊介绍：
The Journal of Materials Chemistry A, B & C covers a wide range of high-quality studies in the field of materials chemistry, with each section focusing on specific applications of the materials studied. Journal of Materials Chemistry A emphasizes applications in energy and sustainability, including topics such as artificial photosynthesis, batteries, and fuel cells. Journal of Materials Chemistry B focuses on applications in biology and medicine, while Journal of Materials Chemistry C covers applications in optical, magnetic, and electronic devices. Example topic areas within the scope of Journal of Materials Chemistry A include catalysis, green/sustainable materials, sensors, and water treatment, among others.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
