2023
DOI: 10.1002/aelm.202300042
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Artificial Intelligence Guided Thermoelectric Materials Design and Discovery

Abstract: Materials discovery from the infinite earth repository is a major bottleneck for revolutionary technological progress. This labor-intensive and time-consuming process hinders the discovery of new materials. Although machine learning techniques show an excellent capability for speeding up materials discovery, obtaining effective material feature representations is still challenging, and making a precise prediction of the material properties is still tricky. This work focuses on developing an automatic material … Show more

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Cited by 4 publications
(1 citation statement)
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“…33,39,340 Lately, machine learning has demonstrated its potential for screening materials which possess the aforementioned structural descriptors, thus accelerating the discovery of new materials with potential high thermoelectric performance. 414–419 The incorporation of information pertaining to the previously mentioned local phenomena as a descriptor into machine learning can play a crucial role in the advancement of thermal insulators or in the field of thermoelectrics.…”
Section: Future Outlookmentioning
confidence: 99%
“…33,39,340 Lately, machine learning has demonstrated its potential for screening materials which possess the aforementioned structural descriptors, thus accelerating the discovery of new materials with potential high thermoelectric performance. 414–419 The incorporation of information pertaining to the previously mentioned local phenomena as a descriptor into machine learning can play a crucial role in the advancement of thermal insulators or in the field of thermoelectrics.…”
Section: Future Outlookmentioning
confidence: 99%