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Machine learning assisted discovering of new M_(2)X_(3)-type thermoelectric materials

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Rare Metals 2022年第5期41卷 1543-1553页

作者： Du Chen Feng Jiang Liang Fang Yong-Bin Zhu Cai-Chao Ye Wei-Shu Liu Department of materials Science and Engineering Southern University of Science and TechnologyShenzhen 518055China Department of Mechanical Engineering The University of Hong KongHong Kong 999077China Department of Physics & Guangdong Provincial Key Laboratory of Computational Science and Material Design Southern University of Science and TechnologyShenzhen 518055China Key Laboratory of Energy Conversion and Storage Technologies(Ministry of Education) Southern University of Science and TechnologyShenzhen 518055China

Recent years have witnessed a continuous discovering of new thermoelectric materials which has experienced a paradigm shift from try-and-error efforts to experience-based discovering and first-principles calculation. However, both the experiment and first-principles calculation deriving routes to determine a new compound are time and resources consuming. Here, we demonstrated a machine learning approach to discover new M_(2)X_(3)-type thermoelectric materials with only the composition information. According to the classic Bi_(2)Te_(3) material, we constructed an M_(2)X_(3)-type thermoelectric material library with 720 compounds by using isoelectronic substitution, in which only 101 compounds have crystalline structure information in the Inorganic Crystal Structure Database(ICSD) and materials Project(MP) database. A model based on the random forest(RF) algorithm plus Bayesian optimization was used to explore the underlying principles to determine the crystal structures from the known compounds. The physical properties of constituent elements(such as atomic mass, electronegativity, ionic radius) were used to define the feature of the compounds with a general formula ^(1)M^(2)M^(1)X^(2)X^(3)X(^(1)M +^(2)M:^(1)X +^(2)X+^(3)X = 2:3). The primary goal is to find new thermoelectric materials with the same rhombohedral structure as Bi_(2)Te_(3) by machine *** final trained RF model showed a high accuracy of 91% on the prediction of rhombohedral compounds. Finally, we selected four important features to proceed with the polynomial fitting with the prediction results from the RF model and used the acquired polynomial function to make further discoveries outside the pre-defined material library.

关键词： thermoelectric materials M_(2)X_(3)-type material library Random forest(RF)algorithm Bayesian optimization Machine learning

Polymer-based thermoelectric materials:A review of power factor improving strategies

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Journal of Materiomics 2022年第1期8卷 204-220页

作者： Jiang Li Alayna Brieann Huckleby Mei Zhang High-Performance materials Institute Florida State UniversityDepartment of Industrial and Manufacturing EngineeringFAMU-FSU College of Engineering2525 Pottsdamer StreetTallahasseeFL32310USA

thermoelectric(TE)materials are receiving increasing attention due to their ability to directly converting heat to *** are used to harvest electrical energy from the wasted heat in order to increase the efficiency of global ***-based TE materials are particularly fascinating to wearable and mobile devices due to their low density,good flexibility,and low *** review summarizes the recent breakthroughs and optimization strategies of polymer-based TE *** a large number of different organic TE materials,those with remarkable TE performance are selected and divided into three categories,which are poly(3,4-ethylenedioxythiophene)derivatives,carbon nanotube/conductive polymer composites,and inorganic semiconductive nanomaterial/polymer *** effect of components and structures on the power factor are presented and ***,some challenges are described and suggestions are provided for preparing the next-generation of polymer-based materials with high TE performance.

关键词： thermoelectric materials Conductive polymers poly(3,4-ethylenedioxythiophene) derivatives Carbon nanotubes Power factor

Accurate and explainable machine learning for the power factors of diamond-like thermoelectric materials

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Journal of Materiomics 2022年第3期8卷 633-639页

作者： Zhe Yang Ye Sheng Cong Zhu Jianyue Ni Zhenyu Zhu Jinyang Xi Wu Zhang Jiong Yang materials Genome Institute Shanghai UniversityShanghai200444China School of Computer Engineering and Science Shanghai UniversityShanghai200444China School of Mechanics and Engineering Science Shanghai UniversityShanghai200444China

The application of machine learning(ML)-based methods to the study of thermoelectric(TE)materials is *** conventional ML algorithms can achieve high prediction performance,their lack of interpretability severely obstructs researchers from extracting material-oriented insights from ML *** this work,high ML-based prediction performance was achieved with respect to TE power factors(PFs),and the results were well understood by the SHapley Additive exPlanations(SHAP),a method to identify the correlations between targets and *** designed a robust PF prediction model for diamond-like compounds via a stacking technique,and the model achieved a coefficient of determination value above 0.95 on the test *** the SHAP analysis,the PFs were negatively correlated with electronegativity and positively correlated with the descriptor“volume per atom”based on the previously reported *** domain knowledge was adopted to understand these *** work shows that ML models can achieve high accuracy while exhibiting good interpretability,making them useful for materials scientists.

关键词： Machine learning thermoelectric materials Interpretability Power factor

Room-temperature thermoelectric materials: Challenges and a new paradigm

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Journal of Materiomics 2022年第2期8卷 427-436页

作者： Zhijia Han Jing-Wei Li Feng Jiang Jiating Xia Bo-Ping Zhang Jing-Feng Li Weishu Liu The Beijing Municipal Key Laboratory of New Energy materials and Technologies School of Materials Science and EngineeringUniversity of Science and Technology BeijingBeijing100083China Department of materials Science and Engineering Southern University of Science and TechnologyShenzhen518055China State Key Laboratory of New Ceramics and Fine Processing School of Materials Science and EngineeringTsinghua UniversityBeijing100084China Shenzhen Engineering Research Center for Novel Electronic Information materials and Devices Southern University of Science and TechnologyShenzhenGuangdong518055China

Room-temperature thermoelectric materials provide promising solutions for energy harvesting from the environment,and deliver a maintenance-free power supply for the internet-of-things(IoTs).The currently available Bi_(2)Te_(3) family discovered in the 1950s,still dominates industrial applications,however,it has serious disadvantages of brittleness and the resource shortage of tellurium(1×10^(-3) ppm in the earth's crust).The novel Mg_(3)Sb_(2) family has received increasing attention as a promising alternative for room-temperature thermoelectric *** this review,the development timeline and fabrication strategies of the Mg 3 Sb 2 family are ***,an insightful comparison between the crystal-linity and band structures of Mg_(3)Sb_(2) and Bi_(2)Te_(3) is *** outlook is presented to discuss challenges and new paradigms in designing room-temperature thermoelectric materials.

关键词： thermoelectric materials Mg_(3)Sb_(2) Bi_(2)Te_(3) Chemical bond engineering

A general strategy for high-throughput experimental screening of promising bulk thermoelectric materials

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Science China materials 2021年第7期64卷 1751-1760页

作者： Shiyang He Yang Yang Zhili Li Jiye Zhang Chenyang Wang Wenqing Zhang Jun Luo School of materials Science and Engineering Shanghai UniversityShanghai 200444China School of Mechatronic Engineering and Automation Shanghai UniversityShanghai 200444China Department of Physics Shenzhen Institute for Quantum Science and EngineeringGuangdong Provincial Key-Lab for Computational Science and Materials DesignSouthern University of Science and TechnologyShenzhen 518055China materials Genome Institute Shanghai UniversityShanghai 200444China

High-throughput(HTP)experiments play key roles in accelerating the discovery of advanced materials,but the HTP preparation and characterization,especially for bulk samples,are extremely *** this work,we developed a novel and general strategy for HTP screening of high-performance bulk thermoelectric *** performed fullchain HTP experiments cover rapid synthesis of the bulk sample with quasi-continuous composition,microarea phase identification and structure analysis,and measurement of the spatial distribution of the sample composition,electrical and thermal transport *** to our experiments,bulk Bi_(2-x)Sb_(x)Te_(3)(x=1-2)and Bi_(2)Te_(3-x)Se_(x)(x=0-1.5)samples with quasi-continuous compositions have been rapidly fabricated by this HTP *** target thermoelectric materials with the best Sb/Bi and Te/Se ratios are successfully screened out based on subsequent HTP characterization results,demonstrating that this HTP technique is effective in speeding up the exploration of novel high-performance thermoelectric materials.

关键词： high-throughput experimental screening thermoelectric materials electrical transport properties thermal transport properties (Bi,Sb)_(2)(Te,Se)_(3)

Heat Conduction in Multilayered thermoelectric materials with Multiple Cracks

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Acta Mechanica Solida Sinica 2018年第4期31卷 512-522页

作者： Shenghu Ding Yueting Zhou School of Mathematics and Statistics Ningxia University Yinchuan 750021 China School of Aerospace Engineering and Applied Mechanics Tongji University Shanghai 200092 China

Multilayer thin-film thermoelectric materials are of technological importance. This paper describes a method to analyze the heat conduction in a multilayered thermoelectric plate containing some non-collinear cracks. The material properties in one layer may be different from those in another even though each layer may still be homogeneous. Using the Fourier integral transforms, the boundary value problem is reduced to a system of general singular integral equations. The model is sufficiently general to account for any number of layers and any number of cracks. As a numerical illustration, the electric flux intensity factor, energy flux intensity factor and thermal flux intensity factor for a three-layer plate specimen with two cracks are presented. The effects of strip width on the electric flux intensity factor and thermal flux intensity factor are studied.

关键词： Multilayer thermoelectric materials Crack Singular integral equation Intensityfactors

thermoelectric properties of porous (Bi_(0.15)Sb_(0.85))_2Te_3 thermoelectric materials

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Journal of University of Science and Technology Beijing 2003年第5期10卷 39-43页

作者： Guiying Xu, Tingjie Chen, Jianqiang Liu, and Zhangjian ZhouLaboratory of Special Ceramics and Powder Metallurgy, materials Science and Engineering School, University of Science and Technology Beijing, Beijing 100083, China Lab. of Special Ceramics Mat. Sci. and Eng. Sch. Univ. of Sci. and Technol. Beijing Beijing 100083 China

In order to obtain thermoelectric materials with high figure of merit, theconcept of Hollow (Vacuum) Quantum Structure or Effect and related thermoelectric materials designwere proposed. To demonstrate the theory, the materials of (Bi_(0.15)Sb_(0.85))_2Te_3 with porousstructure have been fabricated. Their thermoelectric properties and the microstructure wereinvestigated and compared with their density structure. It was found that the porous structure couldimprove their properties greatly.

关键词： thermoelectric materials Bi_xSb_(1-x) Bi_2Te_3 hollow quantum effect

Improving the Performance of thermoelectric materials by Atomic Layer Deposition-based Grain Boundary Engineering

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Chinese Journal of Structural Chemistry 2020年第5期39卷 831-837页

作者： LI Shuan-Kui ZHU Wei-Ming XIAO Yin-Guo PAN Feng School of Advanced materials Peking University Shenzhen Graduate SchoolShenzhen 518055China

thermoelectric materials can directly achieve the conversion between heat and electricity,providing a clean and reliable way to alleviate energy ***,the wide use of thermoelectric materials is subjected to their low energy conversion *** boundary engineering is considered as an effective strategy to improve thermoelectric performance,particularly for the most polycrystalline thermoelectric materials in bulk ***,the precise controlling over the microstructure and composition of grain boundary at atomic scale has been achieved by atomic layer deposition(ALD)technology,which has been confirmed in various thermoelectric materials,such as Bi2Te2.7Se0.3,Bi0.4Sb1.6Te3,and ***,it is demonstrated that the decoupling between three key thermoelectric parameters,*** coefficient,electrical conductivity and thermal conductivity,can be realized by ALD-based grain boundary ***,these key parameters can be optimized simultaneously toward the desired direction,which is extremely important for improving the thermoelectric *** this review,the relevant progress on the grain boundary engineering by ALD-based strategy is reviewed and some prospects are proposed.

关键词： grain boundary engineering atomic layer deposition thermoelectric materials

Strategies for discovery and optimization of thermoelectric materials： Role of real objects and local fields

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Frontiers of physics 2018年第3期13卷 9-16页

作者： Hao Zhu Chong Xiao Hefei National Laboratory for Physical Sciences at the Microscale University of Science & Technology of China Hefei 230026 China

thermoelectric materials provide a renewable and eco-friendly solution to mitigate energy shortages and to reduce environmental pollution via direct heat-to-electricity conversion. Discovery of the novel thermoelectric materials and optimization of the state-of-the-art material systems lie at the core of the thermoelectric society, the basic concept behind these being comprehension and manipulation of the physical principles and transport properties regarding thermoelectric materials. In this mini-review, certain examples for designing high-performance bulk thermoelectric materials are presented from the perspectives of both real objects and local fields. The highlights of this topic involve the Rashba effect, Peierls distortion, local magnetic field, and local stress field, which cover several aspects in the field of thermoelectric research. We conclude with an overview of future developments in thermoelectricity.

关键词： thermoelectric materials real objects local fields