High Thermoelectric Performance of Cu-Doped PbSe-PbS System Enabled by High-Throughput Experimental Screening

Recent advances in high-throughput (HTP) computational power and machine learning have led to great achievements in exploration of new thermoelectric materials. However, experimental discovery and optimization of thermoelectric materials have long relied on the traditional Edisonian trial and error...

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Main Authors: Li You, Zhili Li, Quanying Ma, Shiyang He, Qidong Zhang, Feng Wang, Guoqiang Wu, Qingyi Li, Pengfei Luo, Jiye Zhang, Jun Luo
Format: Article
Language:English
Published: American Association for the Advancement of Science (AAAS) 2020-01-01
Series:Research
Online Access:http://dx.doi.org/10.34133/2020/1736798
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author Li You
Zhili Li
Quanying Ma
Shiyang He
Qidong Zhang
Feng Wang
Guoqiang Wu
Qingyi Li
Pengfei Luo
Jiye Zhang
Jun Luo
author_facet Li You
Zhili Li
Quanying Ma
Shiyang He
Qidong Zhang
Feng Wang
Guoqiang Wu
Qingyi Li
Pengfei Luo
Jiye Zhang
Jun Luo
author_sort Li You
collection DOAJ
description Recent advances in high-throughput (HTP) computational power and machine learning have led to great achievements in exploration of new thermoelectric materials. However, experimental discovery and optimization of thermoelectric materials have long relied on the traditional Edisonian trial and error approach. Herein, we demonstrate that ultrahigh thermoelectric performance in a Cu-doped PbSe-PbS system can be realized by HTP experimental screening and precise property modulation. Combining the HTP experimental technique with transport model analysis, an optimal Se/S ratio showing high thermoelectric performance has been efficiently screened out. Subsequently, based on the screened Se/S ratio, the doping content of Cu has been subtly adjusted to reach the optimum carrier concentration. As a result, an outstanding peak zT~1.6 is achieved at 873 K for a 1.8 at% Cu-doped PbSe0.6S0.4 sample, which is the superior value among the n-type Te-free lead chalcogenides. We anticipate that current work will stimulate large-scale unitization of the HTP experimental technique in the thermoelectric field, which can greatly accelerate the research and development of new high-performance thermoelectric materials.
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spelling doaj.art-af29944f3bab4a9fb54718e542b155202024-03-02T05:27:11ZengAmerican Association for the Advancement of Science (AAAS)Research2639-52742020-01-01202010.34133/2020/1736798High Thermoelectric Performance of Cu-Doped PbSe-PbS System Enabled by High-Throughput Experimental ScreeningLi You0Zhili Li1Quanying Ma2Shiyang He3Qidong Zhang4Feng Wang5Guoqiang Wu6Qingyi Li7Pengfei Luo8Jiye Zhang9Jun Luo10School of Materials Science and Engineering, Shanghai University, 99 Shangda Road, Shanghai 200444, ChinaSchool of Materials Science and Engineering, Shanghai University, 99 Shangda Road, Shanghai 200444, ChinaSchool of Materials Science and Engineering, Shanghai University, 99 Shangda Road, Shanghai 200444, ChinaSchool of Materials Science and Engineering, Shanghai University, 99 Shangda Road, Shanghai 200444, ChinaSchool of Materials Science and Engineering, Shanghai University, 99 Shangda Road, Shanghai 200444, ChinaSchool of Materials Science and Engineering, Shanghai University, 99 Shangda Road, Shanghai 200444, ChinaSchool of Materials Science and Engineering, Shanghai University, 99 Shangda Road, Shanghai 200444, ChinaSchool of Materials Science and Engineering, Shanghai University, 99 Shangda Road, Shanghai 200444, ChinaSchool of Materials Science and Engineering, Shanghai University, 99 Shangda Road, Shanghai 200444, ChinaSchool of Materials Science and Engineering, Shanghai University, 99 Shangda Road, Shanghai 200444, ChinaSchool of Materials Science and Engineering, Shanghai University, 99 Shangda Road, Shanghai 200444, China; Materials Genome Institute, Shanghai University, 99 Shangda Road, Shanghai 200444, ChinaRecent advances in high-throughput (HTP) computational power and machine learning have led to great achievements in exploration of new thermoelectric materials. However, experimental discovery and optimization of thermoelectric materials have long relied on the traditional Edisonian trial and error approach. Herein, we demonstrate that ultrahigh thermoelectric performance in a Cu-doped PbSe-PbS system can be realized by HTP experimental screening and precise property modulation. Combining the HTP experimental technique with transport model analysis, an optimal Se/S ratio showing high thermoelectric performance has been efficiently screened out. Subsequently, based on the screened Se/S ratio, the doping content of Cu has been subtly adjusted to reach the optimum carrier concentration. As a result, an outstanding peak zT~1.6 is achieved at 873 K for a 1.8 at% Cu-doped PbSe0.6S0.4 sample, which is the superior value among the n-type Te-free lead chalcogenides. We anticipate that current work will stimulate large-scale unitization of the HTP experimental technique in the thermoelectric field, which can greatly accelerate the research and development of new high-performance thermoelectric materials.http://dx.doi.org/10.34133/2020/1736798
spellingShingle Li You
Zhili Li
Quanying Ma
Shiyang He
Qidong Zhang
Feng Wang
Guoqiang Wu
Qingyi Li
Pengfei Luo
Jiye Zhang
Jun Luo
High Thermoelectric Performance of Cu-Doped PbSe-PbS System Enabled by High-Throughput Experimental Screening
Research
title High Thermoelectric Performance of Cu-Doped PbSe-PbS System Enabled by High-Throughput Experimental Screening
title_full High Thermoelectric Performance of Cu-Doped PbSe-PbS System Enabled by High-Throughput Experimental Screening
title_fullStr High Thermoelectric Performance of Cu-Doped PbSe-PbS System Enabled by High-Throughput Experimental Screening
title_full_unstemmed High Thermoelectric Performance of Cu-Doped PbSe-PbS System Enabled by High-Throughput Experimental Screening
title_short High Thermoelectric Performance of Cu-Doped PbSe-PbS System Enabled by High-Throughput Experimental Screening
title_sort high thermoelectric performance of cu doped pbse pbs system enabled by high throughput experimental screening
url http://dx.doi.org/10.34133/2020/1736798
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