首页|Findings from Hainan Normal University Has Provided New Data on Machine Learning (Thermal and Electronic Properties of Borophene In Two-dimensional Lateral Grap hene-borophene Heterostructures Empowered By Machine-learning Approach)
Findings from Hainan Normal University Has Provided New Data on Machine Learning (Thermal and Electronic Properties of Borophene In Two-dimensional Lateral Grap hene-borophene Heterostructures Empowered By Machine-learning Approach)
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Researchers detail new data in Machine Learning. According to news reporting originating from Haikou, People's Republi c of China, by NewsRx correspondents, research stated, "Due to its electron-defi cient character and complicated banding mechanism, two-dimensional (2D) borophen e has gain more attentions recently. The polymorphism of 2D borophene provides m ore room for forming the 2D lateral heterostructures." Financial supporters for this research include National Natural Science Foundati on of China (NSFC), China's Central Government Funds for Guiding Local Scientifi c and Technological Development Projects. Our news editors obtained a quote from the research from Hainan Normal Universit y, "However, the effects of confined circumstance on many properties of the boro phene are unknown. In this work, using first-principles calculations and molecul ar simulations based on the machine learning interatomic potential, we investiga ted the electronic structures and thermal properties of 2D lateral graphene-boro phene heterostructures (GBHs). We found that the graphene-borophene heterostruct ure promotes the thermal transport of borophene, and different concentrations of borophene hardly affect the lattice thermal conductivity of the interface. We a lso found the charge transfer induced thermal conductivity change in borophene d omain of GBH, compared with that of bulk borophene."
HaikouPeople's Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningHainan Normal University
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