首页|Reports Summarize Machine Learning Findings from Indian Institute for Technology (Rattling Induced Bonding Hierarchy In Li-cu-ti Chalcotitanates for Enhanced Th ermoelectric Efficiency: a Machine Learning Potential Approach)
Reports Summarize Machine Learning Findings from Indian Institute for Technology (Rattling Induced Bonding Hierarchy In Li-cu-ti Chalcotitanates for Enhanced Th ermoelectric Efficiency: a Machine Learning Potential Approach)
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2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators discuss new findings in Machine Learning. According to news reporting out of Madhya Pradesh, India, by N ewsRx editors, research stated, "The nature of chemical bonding in crystalline s olids significantly influences heat conduction, impacting lattice thermal conduc tivity and, consequently, thermoelectric (TE) performance. In this study, we rep ort the development of the first principles-based machine learning interatomic p otentials to predict TE efficiency in chalcogenide-based materials." Funders for this research include Board of Research in Nuclear Sciences (BRNS), IIT Indore, Science Engineering Research Board (SERB), India, Council of Scienti fic & Industrial Research (CSIR) - India, Board of Research in Nuc lear Sciences (BRNS), University Grants Commission, India.
Madhya PradeshIndiaAsiaCyborgsEm erging TechnologiesMachine LearningIndian Institute for Technology
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