ZT Optimization: An Application Focus
AbstractSignificant 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. View Full-Text
- Supplementary File 1:
PDF-Document (PDF, 98 KB)
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Tuley, R.; Simpson, K. ZT Optimization: An Application Focus. Materials 2017, 10, 309.
Tuley R, Simpson K. ZT Optimization: An Application Focus. Materials. 2017; 10(3):309.Chicago/Turabian Style
Tuley, Richard; Simpson, Kevin. 2017. "ZT Optimization: An Application Focus." Materials 10, no. 3: 309.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.