Discovering the ultralow thermal conductive A_(2)B_(2)O_(7)-type high-entropy oxides through the hybrid knowle dge-assiste d data-driven machine learning  

作　　者：Ying Zhang Ke Ren William Yi Wang Xingyu Gao Ruihao Yuan Jun Wang Yiguang Wang Haifeng Song Xiubing Liang Jinshan Li 

机构地区：[1]State Key Laboratory of Solidification Processing,Northwestern Polytechnical University,Xi’an 710072,China [2]Innovation Center,NPU Chongqing,Chongqing 401135,China [3]Institute of Advanced Structure Technology,Beijing Institute of Technology,Haidian District,Beijing 100081,China [4]Laboratory of Computational Physics,Institute of Applied Physics and Computational Mathematics,Beijing 100088,China [5]Defense Innovation Institute,Academy of Military Sciences of the PLA of China,Beijing 100071,China

出　　处：《Journal of Materials Science & Technology》2024年第1期131-142,共12页材料科学技术（英文版）

基　　金：supported by National defense ba-sic scientific research(Grant Nos.2022-JCKY-JJ-1086 and 211-CXCY-N103-03-04-00).

摘　　要：Lattice engineering and distortion have been considered one kind of effective strategies for discovering advanced materials.The instinct chemical flexibility of high-entropy oxides(HEOs)motivates/accelerates to tailor the target properties through phase transformations and lattice distortion.Here,a hybrid knowledge-assisted data-driven machine learning(ML)strategy is utilized to discover the A_(2)B_(2)O_(7)-type HEOs with low thermal conductivity(κ)through 17 rare-earth(RE=Sc,Y,La-Lu)solutes optimized A-site.A designing routine integrating the ML and high throughput first principles has been proposed to predict the key physical parameter(KPPs)correlated to the targetedκof advanced HEOs.Among the smart-designed 6188(5RE_(0.2))_(2)Zr_(2)O_(7)HEOs,the best candidates are addressed and validated by the princi-ples of severe lattice distortion and local phase transformation,which effectively reduceκby the strong multi-phonon scattering and weak interatomic interactions.Particularly,(Sc_(0.2)Y_(0.2)La_(0.2)Ce_(0.2)Pr_(0.2))_(2)Zr_(2)O_(7)with predictedκbelow 1.59 Wm^(−1)K^(−1)is selected to be verified,which matches well with the ex-perimentalκ=1.69 Wm^(−1)K^(−1)at 300 K and could be further decreased to 0.14 Wm^(−1)K^(−1)at 1473 K.Moreover,the coupling effects of lattice vibrations and charges on heat transfer are revealed by the cross-validations of various models,indicating that the weak bonds with low electronegativity and few bond-ing charge density and the lattice distortion(r∗)identified by cation radius ratio(r A/r B)should be the KPPs to decreaseκefficiently.This work supports an intelligent designing strategy with limited atomic and electronic KPPs to accelerate the development of advanced multi-component HEOs with proper-ties/performance at multi-scales.

关 键 词：High-entropy oxides Thermal conductivity PYROCHLORE Key physical parameter FIRST-PRINCIPLES 

分 类 号：TG1[金属学及工艺—金属学]