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ZT Optimization: An Application Focus
Significant research has been performed on the challenge of improving thermoelectric materials, with maximum peak figure of merit, ZT, the most common target. We use an approximate thermoelectric material model, matched to real materials, to demonstrate that when an application is known, average ZT...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5503391/ https://www.ncbi.nlm.nih.gov/pubmed/28772668 http://dx.doi.org/10.3390/ma10030309 |
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author | Tuley, Richard Simpson, Kevin |
author_facet | Tuley, Richard Simpson, Kevin |
author_sort | Tuley, Richard |
collection | PubMed |
description | Significant research has been performed on the challenge of improving thermoelectric materials, with maximum peak figure of merit, ZT, the most common target. We use an approximate thermoelectric material model, matched to real materials, to demonstrate that when an application is known, average ZT is a significantly better optimization target. We quantify this difference with some examples, with one scenario showing that changing the doping to increase peak ZT by 19% can lead to a performance drop of 16%. The importance of average ZT means that the temperature at which the ZT peak occurs should be given similar weight to the value of the peak. An ideal material for an application operates across the maximum peak ZT, otherwise maximum performance occurs when the peak value is reduced in order to improve the peak position. |
format | Online Article Text |
id | pubmed-5503391 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-55033912017-07-28 ZT Optimization: An Application Focus Tuley, Richard Simpson, Kevin Materials (Basel) Article Significant research has been performed on the challenge of improving thermoelectric materials, with maximum peak figure of merit, ZT, the most common target. We use an approximate thermoelectric material model, matched to real materials, to demonstrate that when an application is known, average ZT is a significantly better optimization target. We quantify this difference with some examples, with one scenario showing that changing the doping to increase peak ZT by 19% can lead to a performance drop of 16%. The importance of average ZT means that the temperature at which the ZT peak occurs should be given similar weight to the value of the peak. An ideal material for an application operates across the maximum peak ZT, otherwise maximum performance occurs when the peak value is reduced in order to improve the peak position. MDPI 2017-03-17 /pmc/articles/PMC5503391/ /pubmed/28772668 http://dx.doi.org/10.3390/ma10030309 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Tuley, Richard Simpson, Kevin ZT Optimization: An Application Focus |
title | ZT Optimization: An Application Focus |
title_full | ZT Optimization: An Application Focus |
title_fullStr | ZT Optimization: An Application Focus |
title_full_unstemmed | ZT Optimization: An Application Focus |
title_short | ZT Optimization: An Application Focus |
title_sort | zt optimization: an application focus |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5503391/ https://www.ncbi.nlm.nih.gov/pubmed/28772668 http://dx.doi.org/10.3390/ma10030309 |
work_keys_str_mv | AT tuleyrichard ztoptimizationanapplicationfocus AT simpsonkevin ztoptimizationanapplicationfocus |