The increasing awareness of environmental concerns has prompted a surge in the exploration of leadfree,high-power ceramic capacitors.Ongoing efforts to develop leadfree dielectric ceramics with exceptional energystora...The increasing awareness of environmental concerns has prompted a surge in the exploration of leadfree,high-power ceramic capacitors.Ongoing efforts to develop leadfree dielectric ceramics with exceptional energystorage performance(ESP)have predominantly relied on multicomponent composite strategies,often accomplished under ultrahigh electric fields.However,this approach poses challenges in insulation and system downsizing due to the necessary working voltage under such conditions.Despite extensive study,bulk ceramics of(Bi_(0.5)Na_(0.5))TiO_(3)(BNT),a prominent lead-free dielectric ceramic family,have seldom achieved a recoverable energy-storage(ES)density(Wrec)exceeding 7 J cm^(−3).This study introduces a novel approach to attain ceramic capacitors with high ESP under moderate electric fields by regulating permittivity based on a linear dielectric model,enhancing insulation quality,and engineering domain structures through chemical formula optimization.The incorporation of SrTiO_(3)(ST)into the BNT matrix is revealed to reduce the dielectric constant,while the addition of Bi(Mg_(2/3)Nb_(1/3))O_(3)(BMN)aids in maintaining polarization.Additionally,the study elucidates the methodology to achieve high ESP at moderate electric fields ranging from 300 to 500 kV cm^(−1).In our optimized composition,0.5(Bi_(0.5)Na_(0.4)K_(0.1))TiO_(3)–0.5(2/3ST-1/3BMN)(B-0.5SB)ceramics,we achieved a Wrec of 7.19 J cm^(−3) with an efficiency of 93.8%at 460 kV cm^(−1).Impressively,the B-0.5SB ceramics exhibit remarkable thermal stability between 30 and 140℃ under 365 kV cm^(−1),maintaining a Wrec exceeding 5 J cm^(−3).This study not only establishes the B-0.5SB ceramics as promising candidates for ES materials but also demonstrates the feasibility of optimizing ESP by modifying the dielectric constant under specific electric field conditions.Simultaneously,it provides valuable insights for the future design of ceramic capacitors with high ESP under constraints of limited electric field.展开更多
A machine learning(ML)-based random forest(RF)classification model algorithm was employed to investigate the main factors affecting the formation of the core-shell structure of BaTiO_(3)-based ceramics and their inter...A machine learning(ML)-based random forest(RF)classification model algorithm was employed to investigate the main factors affecting the formation of the core-shell structure of BaTiO_(3)-based ceramics and their interpretability was analyzed by using Shapley additive explanations(SHAP).An F1-score changed from 0.8795 to 0.9310,accuracy from 0.8450 to 0.9070,precision from 0.8714 to 0.9000,recall from 0.8929 to 0.9643,and ROC/AUC value of 0.97±0.03 was achieved by the RF classification with the optimal set of features containing only 5 features,demonstrating the high accuracy of our model and its high robustness.During the interpretability analysis of the model,it was found that the electronegativity,melting point,and sintering temperature of the dopant contribute highly to the formation of the core-shell structure,and based on these characteristics,specific ranges were delineated and twelve elements were finally obtained that met all the requirements,namely Si,Sc,Mn,Fe,Co,Ni,Pd,Er,Tm,Lu,Pa,and Cm.In the process of exploring the structure of the core-shell,the doping elements can be effectively localized to be selected by choosing the range of features.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.51761145024)the Key Research and Development Program of Shaanxi(Program No.2022KWZ-22)+3 种基金the Natural Science Basic Research Program of Shaanxi(Program No.2023-JC-YB-441)the Youth Innovation Team of Shaanxi Universitiesthe Fundamental Research Funds of Shaanxi Key Laboratory of Artificially-Structured Functional Materials and Devices(AFMD-KFJJ-21203)The research was made possible by Russian Science Foundation(Project No.23-42-00116).
文摘The increasing awareness of environmental concerns has prompted a surge in the exploration of leadfree,high-power ceramic capacitors.Ongoing efforts to develop leadfree dielectric ceramics with exceptional energystorage performance(ESP)have predominantly relied on multicomponent composite strategies,often accomplished under ultrahigh electric fields.However,this approach poses challenges in insulation and system downsizing due to the necessary working voltage under such conditions.Despite extensive study,bulk ceramics of(Bi_(0.5)Na_(0.5))TiO_(3)(BNT),a prominent lead-free dielectric ceramic family,have seldom achieved a recoverable energy-storage(ES)density(Wrec)exceeding 7 J cm^(−3).This study introduces a novel approach to attain ceramic capacitors with high ESP under moderate electric fields by regulating permittivity based on a linear dielectric model,enhancing insulation quality,and engineering domain structures through chemical formula optimization.The incorporation of SrTiO_(3)(ST)into the BNT matrix is revealed to reduce the dielectric constant,while the addition of Bi(Mg_(2/3)Nb_(1/3))O_(3)(BMN)aids in maintaining polarization.Additionally,the study elucidates the methodology to achieve high ESP at moderate electric fields ranging from 300 to 500 kV cm^(−1).In our optimized composition,0.5(Bi_(0.5)Na_(0.4)K_(0.1))TiO_(3)–0.5(2/3ST-1/3BMN)(B-0.5SB)ceramics,we achieved a Wrec of 7.19 J cm^(−3) with an efficiency of 93.8%at 460 kV cm^(−1).Impressively,the B-0.5SB ceramics exhibit remarkable thermal stability between 30 and 140℃ under 365 kV cm^(−1),maintaining a Wrec exceeding 5 J cm^(−3).This study not only establishes the B-0.5SB ceramics as promising candidates for ES materials but also demonstrates the feasibility of optimizing ESP by modifying the dielectric constant under specific electric field conditions.Simultaneously,it provides valuable insights for the future design of ceramic capacitors with high ESP under constraints of limited electric field.
基金Funded by the National Key Research and Development Program of China(No.2023YFB3812200)。
文摘A machine learning(ML)-based random forest(RF)classification model algorithm was employed to investigate the main factors affecting the formation of the core-shell structure of BaTiO_(3)-based ceramics and their interpretability was analyzed by using Shapley additive explanations(SHAP).An F1-score changed from 0.8795 to 0.9310,accuracy from 0.8450 to 0.9070,precision from 0.8714 to 0.9000,recall from 0.8929 to 0.9643,and ROC/AUC value of 0.97±0.03 was achieved by the RF classification with the optimal set of features containing only 5 features,demonstrating the high accuracy of our model and its high robustness.During the interpretability analysis of the model,it was found that the electronegativity,melting point,and sintering temperature of the dopant contribute highly to the formation of the core-shell structure,and based on these characteristics,specific ranges were delineated and twelve elements were finally obtained that met all the requirements,namely Si,Sc,Mn,Fe,Co,Ni,Pd,Er,Tm,Lu,Pa,and Cm.In the process of exploring the structure of the core-shell,the doping elements can be effectively localized to be selected by choosing the range of features.
