2021
DOI: 10.1063/5.0054532
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Data-driven thermoelectric modeling: Current challenges and prospects

Abstract: Recent advancements in computing technologies coupled with the need to make sense of large amounts of raw data have renewed much interest in data-driven materials design and discovery. Traditional materials science research relies heavily on experimental data to gauge the properties of materials. However, this paradigm is purely based on trial and error and ongoing research can take decades to discover new materials. Data-driven modeling tools such as machine learning and its proven libraries can help speed up… Show more

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Cited by 14 publications
(10 citation statements)
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“…As noted, several of the most significant results achieved on silicon (and on other thermoelectric materials as well) have taken advantage of theoretical and computational investigations [ 96 , 97 ]. Large computer-generated datasets might provide additional tools to accelerate the discovery of new performing thermoelectric materials—and of ways to modify known materials to increase their efficiency [ 98 , 99 ].…”
Section: Summary and Outlookmentioning
confidence: 99%
“…As noted, several of the most significant results achieved on silicon (and on other thermoelectric materials as well) have taken advantage of theoretical and computational investigations [ 96 , 97 ]. Large computer-generated datasets might provide additional tools to accelerate the discovery of new performing thermoelectric materials—and of ways to modify known materials to increase their efficiency [ 98 , 99 ].…”
Section: Summary and Outlookmentioning
confidence: 99%
“…The predictive power of quantum mechanics combined with the efficiency of density functional theory has revolutionized our ability to describe microscopic phenomena in materials. During past decades, first-principles computations have become an indispensable part of materials design, with applications ranging from energy harvesting, conversion, and storage, to quantum information and drug design. With the advancement of modern supercomputers, computational capacity today enables high-throughput screening and data-driven in silico exploration of novel materials. At the same time, there has been a corresponding increase in scientific publications and a remarkable amount of data which fuels the application of artificial intelligence to interpret patterns, predict properties, and steer the directions of materials design.…”
Section: Introductionmentioning
confidence: 99%
“…Thermoelectric technology is one of the most fantastic energy-conversion technologies that can convert heat energy and electrical energy into each other directly [ 1 , 2 , 3 ]. Thermoelectric materials have recently gained extensive attention as a critical factor for thermoelectric technology.…”
Section: Introductionmentioning
confidence: 99%