首页|Investigators from University of Alabama Birmingham Report New Data on Machine Learning (Machine Learning the Relationship Between Debye Temperature and Superconducting Transition Temperature)
Investigators from University of Alabama Birmingham Report New Data on Machine Learning (Machine Learning the Relationship Between Debye Temperature and Superconducting Transition Temperature)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
Researchers detail new data in Machine Learning. According to news reporting out of Birmingham, Alabama, by NewsRx editors, research stated, "Recently a relationship between the Debye temperature OD and the superconducting transition temperature Tc of conventional superconductors has been proposed [Esterlis et al., npj Quantum Mater. 3, 59 (2018)]. The relationship indicates that Tc AOD for phonon-mediated BCS superconductors, with A being a prefactor of order -0.1." Funders for this research include National Science Foundation (NSF), UAB Blazer Fellowship, FTPP CERIF Graduate Research Assistantship, National Science Foundation (NSF), United States Department of Energy (DOE), ADECA.
BirminghamAlabamaUnited StatesNorth and Central AmericaCyborgsEmerging TechnologiesMachine LearningUniversity of Alabama Birmingham
NETL
NSTL
