Optimizing and extending ion dielectric polarizability database for microwave frequencies using machine learning methods

作     者：Jincheng Qin Zhifu Liu Mingsheng Ma Yongxiang Li 

作者机构：CAS Key Laboratory of Inorganic Functional Materials and DevicesShanghai Institute of CeramicsChinese Academy of Sciences201899 ShanghaiChina Center of Materials Sciences and Optoelectronics EngineeringUniversity of Chinese Academy of Sciences100049 BeijingChina 

出 版 物：《npj Computational Materials》 (计算材料学（英文）)

年 卷 期：2023年第9卷第1期

页      面：977-986页

核心收录：

学科分类：08[工学] 0835[工学-软件工程] 081202[工学-计算机软件与理论] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：The authors would like to acknowledge the support from the National Natural Science Foundation of China(61871369) M.M.acknowledges the Youth Innovation Promotion Association of CAS and Shanghai Rising-Star Program(20QA1410200) 

主　　题：database microwave dielectric 

摘      要：Permittivity at microwave frequencies determines the practical applications of microwave dielectric *** accuracy and universality of the permittivity prediction by Clausius–Mossotti equation depends on the dielectric polarizability(αD)*** most influentialαD database put forward by Shannon is facing three challenges in the 5 G era:(1)Few data,(2)Simplistic relation and(3)Low frequency(kHz–MHz)***,we optimized and extended the Shannon’s database for microwave frequencies by the four-stage multiple linear regression and support vector machine *** comparison with the conventional database,the optimized and extended databases achieved higher accuracy and expanded the amount of data from 60 to more than ***,we analyzed the relationships betweenαD and ion characteristics,including ionic radius(IR),atomic number(N),valence state(V)and coordination number(CN).We found that the positive cubic law of“αD~IR3discussed in Shannon’s work was valid for the IR changed by the N,but invalid for the change caused by the CN.