A comprehensive review on the effects of doping process on the thermoelectric properties of Bi2Te3 based alloys

Saberi, Yasaman; Sajjadi, Seyed Abdolkarim

doi:10.1016/j.jallcom.2022.163918

Cited by 53 publications

(19 citation statements)

References 150 publications

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“…In the high-temperature range (above 600 K), GeTe-based thermoelectric materials exhibit optimized band structure, efficient electronic transport, and low lattice thermal conductivity, thereby positively influencing the ZT value. However, in the low-temperature range approaching room temperature, the thermoelectric performance of GeTe is poor due to the high intrinsic carrier concentration . Nevertheless, the thermoelectric performance of GeTe materials can be optimized through methods such as alloying and doping.…”

Section: Resultsmentioning

confidence: 99%

“…However, in the low-temperature range approaching room temperature, the thermoelectric performance of GeTe is poor due to the high intrinsic carrier concentration. 41 Nevertheless, the thermoelectric performance of GeTe materials can be optimized through methods such as alloying and doping. For example, doping with Sn can modify the band structure to enhance the power factor, while doping with Sb can adjust the carrier concentration to optimize the electrical conductivity and Seebeck coefficient.…”

Section: ■ Results and Discussionmentioning

confidence: 99%

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Interpretable Machine Learning Workflow for Evaluating and Analyzing the Performance of High-Entropy GeTe-Based Thermoelectric Materials

Li,

Liu

2023

ACS Appl. Electron. Mater.

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To guide the development of high-performance thermoelectric materials, it is essential to design appropriate material compositions and temperature environments. This study focuses on analyzing the properties of high-entropy GeTe-based thermoelectric materials under different temperature environments and chemical compositions using an interpretable machine learning workflow. First, an experimental dataset from previous research on thermoelectric materials is constructed, and descriptors based on atomic features are established. Feature selection techniques, such as Pearson correlation, univariate feature selection, and exhaustive feature selection, are applied to select relevant features. The selected features are then used in conjunction with the target variable, the ZT value, for training and testing. The effectiveness of the training is demonstrated by comparing the performance on the testing set and using cross-validation to identify the best machine learning model. Furthermore, the SHAP (SHapley Additive exPlanations) method is employed to interpret the best model. Through global interpretability, analysis of interactive variables' contributions to the target variable, and local interpretability methods, material selection, and performance optimization are carried out. The results reveal that temperature has the greatest impact on the ZT value of thermoelectric materials, while the effects of molar volume and electronegativity sequentially diminish. By utilizing interpretable machine learning methods, we are able to predict and optimize the performance of thermoelectric materials based on known samples. This not only facilitates the evaluation and prediction of the thermoelectric properties of materials but also provides a comprehensive research workflow design approach for guiding the selection and development of high-performance GeTe-based thermoelectric materials.

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Section: Resultsmentioning

confidence: 99%

Section: ■ Results and Discussionmentioning

confidence: 99%

Interpretable Machine Learning Workflow for Evaluating and Analyzing the Performance of High-Entropy GeTe-Based Thermoelectric Materials

Li,

Liu

2023

ACS Appl. Electron. Mater.

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“…Bi 2 Te 3 -based alloys were first investigated as promising thermoelectric materials in the 1960s, and so far they are still the most popular near-room-temperature thermoelectric materials. − In the past few decades, great improvement in thermoelectric performance has been achieved in p-type Bi 2 Te 3 . A maximum ZT of ∼2.4 for a p-type Bi 2 Te 3 superlattice thin film has been reached by controlling the transport of phonons and electrons .…”

Section: State-of-the-art Te Materials In Contact Designmentioning

confidence: 99%

Research Progress of Interfacial Design between Thermoelectric Materials and Electrode Materials

Yang

Sheng

et al. 2023

ACS Appl. Mater. Interfaces

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Intensive efforts have been conducted to realize the reliable interfacial joining of thermoelectric materials and electrode materials with low interfacial contact resistance, which is an essential step to make thermoelectric materials into thermoelectric devices for industrial application. In this review, the roles of structural integrity, interdiffusion, and contact resistance in long-term reliabilities of thermoelectric modules are outlined first. Then interfacial reactions of near-room-temperature Bi2Te3-based thermoelectric materials and various electrode materials are reviewed comprehensively. We also summarized the joining behavior of the mid-temperature PbTe-based thermoelectric materials and commonly used electrode materials. Subsequently, for other thermoelectric materials systems, i.e., SiGe, CoSb3, and Mg3Sb2, previous attempts to join with some electrode materials are also recapitulated. Finally, some future prospects to further improve the joint reliability in thermoelectric device manufacturing are proposed. We believe that this review will provide guidance for preparing thermoelectric devices and optimizing thermoelectric device design.

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“…1,2 The efficiency of thermoelectric materials is directly related to the so-called figure of merit zT, defined as zT = α 2 T/ρκ, where α is the thermopower, T is the absolute temperature, ρ is the electrical resistivity, and κ is the thermal conductivity which includes the contributions of both carriers (electronic thermal conductivity κ e ) and phonons (lattice thermal conductivity κ l ), κ = κ e + κ l . 3 Achieving high values of zT requires increasing α and at the same time decreasing κ, a challenging task, since these variables are strongly coupled and depend on the carrier concentration n. 4 Bi 2 Te 3 -based compounds are pioneer thermoelectric materials for room-temperature applications, 5 and many attempts have been made to improve their efficiency over a wide temperature range. Several key strategies that stand out include optimization of the charge carrier concentration; 6,7 widening the band gap 8−10 to suppress the bipolar effect; enhancing the thermopower and thermal conductivity by alloying Bi 2 Te 3 with Sb 11−14 and Se; 15,16 nanostructuring to reduce the thermal conductivity; 17,18 and utilizing the convergence of electronic bands in alloys to further increase the zT.…”

Section: ■ Introductionmentioning

confidence: 99%

Thermoelectric Properties of Single-Phase n-Type Bi₁₄Te₁₃S₈

Fortulan,

Aminorroaya Yamini,

Juri

et al. 2024

ACS Appl. Electron. Mater.

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Bismuth telluride (Bi 2 Te 3 ) and its alloys are among the best thermoelectric materials at room temperature. Bi 14 Te 13 S 8 , a material with a similar crystal structure, contains sulfur that can potentially improve the thermoelectric performance through widening the band gap and reducing the lattice thermal conductivity. This compound forms in sulfur-added Bi 2 Te 3 alloys. Here, a polycrystalline iodine-doped Bi 14 Te 13 S 8 sample is investigated; an optimum iodine concentration of 1 at. % resulted in the power factor of 3.5 mW 2 •m −1 •K −1 at room temperature. Iodine doping reduced the lattice thermal conductivity by more than 30% by enhancing the phonon scattering. An improved thermoelectric figure of merit zT of ∼0.29 at 520 K was obtained for 1−1.5 at. % iodine-doped Bi 14 Te 13 S 8 . First-principles calculations indicate that Bi 14 Te 13 S 8 has a larger band gap compared to bismuth telluride, which allows for a reduction in the bipolar effect; however, a lower effective mass reduced the thermopower for a similar carrier concentration. This study demonstrates that tuned iodine doping can effectively optimize the thermoelectric performance of Bi 14 Te 13 S 8 , highlighting its contribution in multiphase sulfur-alloyed Bi 2 Te 3 -based materials.

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A comprehensive review on the effects of doping process on the thermoelectric properties of Bi2Te3 based alloys

Cited by 53 publications

References 150 publications

Interpretable Machine Learning Workflow for Evaluating and Analyzing the Performance of High-Entropy GeTe-Based Thermoelectric Materials

Interpretable Machine Learning Workflow for Evaluating and Analyzing the Performance of High-Entropy GeTe-Based Thermoelectric Materials

Research Progress of Interfacial Design between Thermoelectric Materials and Electrode Materials

Thermoelectric Properties of Single-Phase n-Type Bi₁₄Te₁₃S₈

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A comprehensive review on the effects of doping process on the thermoelectric properties of Bi2Te3 based alloys

Cited by 53 publications

References 150 publications

Interpretable Machine Learning Workflow for Evaluating and Analyzing the Performance of High-Entropy GeTe-Based Thermoelectric Materials

Interpretable Machine Learning Workflow for Evaluating and Analyzing the Performance of High-Entropy GeTe-Based Thermoelectric Materials

Research Progress of Interfacial Design between Thermoelectric Materials and Electrode Materials

Thermoelectric Properties of Single-Phase n-Type Bi14Te13S8

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Product

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Thermoelectric Properties of Single-Phase n-Type Bi₁₄Te₁₃S₈