What is it about?
The frontier of physical theories and computational methods for predicting heat-to-electricity conversion (thermoelectric) properties of materials from atomistic modeling without any experimental input, enabling simultaneously large-scale screening and targeted identification of promising thermoelectric materials to guide experimental efforts.
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Why is it important?
Thermoelectrics can be a niche and useful technology. It is currently mainly used to power spacecrafts but with more efficient materials it can recover waste heat for electricity and be a unique cooling solution. Efficient materials for thermoelectric conversion is extremely hard to come by, and the task is to identify a promising material in a sea of poor materials. Experiments are slow and costly, and one wouldn't want to try thousands of materials in the lab, especially when predictive calculations can be done. To screen through the vast number of materials, calculations must be highly efficient (to cover a lot of ground) but also accurate such that predictions are reliable. Development in theories, computational methods and infrastructure has made this possible and is poised to enable finding the needle in the haystack.
Perspectives
Writing this article was a great pleasure as it has co-authors with whom I have had long standing collaborations. It also is a compendium of what I've learned and what perspectives I gained about the topic through the past decade of research. I feel that thermoelectrics is a technology of high potential and wide-ranging applicability but pinned down mainly by insufficient efficiencies of usable materials that require not just incremental improvements but decisive improvements. I hope (and believe) the recent developments theory and computation can change that landscape.
Junsoo Park
NASA
Read the Original
This page is a summary of: Advances in theory and computational methods for next-generation thermoelectric materials, Applied Physics Reviews, March 2025, American Institute of Physics,
DOI: 10.1063/5.0241645.
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