基于第一性原理计算和机器学习的镁合金阴极腐蚀行为研究
日期：2024/01/16 - 2024/01/16
博士论文答辩：基于第一性原理计算和机器学习的镁合金阴极腐蚀行为研究
主讲人：Ao Wang, Ph.D. candidate at UM-SJTU Joint Institute
时间：2024年1月16日（周二）上午9:30
地点：龙宾楼415B会议室
讲座摘要
Thermal transport properties of metals are of great importance for the thermal management in various industrial applications. Despite great effort having been devoted to study the thermal transport mechanism, the understanding of thermal transport for metals, however, evolves relatively slowly. Recently, there has been growing interest in the electronic and phonon thermal transport in metals. The studies mainly focus on elemental metals. In comparison, this dissertation is aiming at developing deeper understandings of thermal transport properties of non-elemental metallic systems, including complex intermetallics, defective metals, and two-dimensional metals. In this dissertation, the relationship between the metallic crystal and its thermal transport properties is elaborated. In metals with a large primitive cell, electrons are the main heat carrier, and the phonon thermal conductivity is severely suppressed. The impact of a vacancy on electron thermal conductivity is related to the density of states contributed from the vacancy atom. Its effect on phonon thermal conductivity is highly related to the mass of the vacancy atom. The impact of functional groups on thermal conductivity is complex, because it is related to electron transport, phonon transport, and their interaction. Some specific functional groups can reduce electron-phonon coupling strength, providing the possibility for increasing the thermal conductivity. This dissertation extends the understanding of thermal transport in metals beyond those elemental metals, and the conclusions are important for the future predictive design of the thermal conductivity of metals.