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Realizing record high performance in n-type Bi2Te3-based thermoelectric materials

  • Bin Zhu (Co-first Author)
  • , Xixi Liu (Co-first Author)
  • , Qi Wang (Co-first Author)
  • , Yang Qiu
  • , Zhong Shu
  • , Zuteng Guo
  • , Yao Tong
  • , Juan Cui
  • , Meng Gu
  • , Jiaqing He*
  • *Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

The application of Bi2Te3-based power generation is seriously hindered by the poor n-type samples, demonstrating a strong demand for high-performance n-type Bi2Te3-based thermoelectric (TE) materials. However, the strong relationship between thermal and electrical transport limits the improvement of the TE properties. Here, we propose a strategy to enhance the Seebeck coefficient while retaining a large electrical conductivity in n-type (Bi,Sb)2(Te,Se)3 materials through introducing electron transport potential wells and texturing. The thermal conductivity was also successfully decreased by constructing multi-scale phonon scattering structures. Consequently, a record maximum and average thermoelectric figure of merit (ZT) of ∼1.4 and ∼1.3 were achieved in the Bi1.8Sb0.2Te2.7Se0.3 + 15 wt% Te sample at a temperature of 300-575 K. A TE power generation module was fabricated with this n-type material and a home-made p-type Bi2Te3 sample. It demonstrated a record conversion efficiency of 6.6% at a temperature gradient of 235 K, representing about an 88% improvement compared with a commercial zone-melt Bi2Te3-based module. © 2020 The Royal Society of Chemistry.
Original languageEnglish
Pages (from-to)2106-2114
Number of pages9
JournalEnergy and Environmental Science
Volume13
Issue number7
Online published8 Jun 2020
DOIs
Publication statusPublished - 1 Jul 2020
Externally publishedYes

Funding

This contribution was supported by the Natural Science Foundation of China (Grant No. 11934007, 11874194, 51632005, and 51702150), the Leading Talents of the Guangdong Province Program (Grant No. 00201517), the Shenzhen DRC project [2018] 1433, and the Science, Technology and Innovation Commission of the Shenzhen Municipality (Grant No. KQTD2016022619565991 and ZDSYS20141118160434515). The authors acknowledge the assistance of SUSTech Core Research Facilities.

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