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会议网站：http://mtt2024.csmnt.org.cn
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Xin Qian is currently a professor of engineering thermophysics at Huazhong University of Science and Technology. He graduated from University of Colorado Boulder in 2019, and was a postdoctoral associate at MIT in NanoEngineering Group led by Gang Chen from 2019 to 2021. His research focuses on energy transport and conversion physics at nanoscale, including machine-learning-aided modeling of phonon and ion transport, thermoreflectance microscopy for thermal property of materials, and low-grade heat harvesting technologies. Xin Qian is currently the PI of NSFC project and NSFC awards for excellent young scholars (overseas), and a co-PI of National Key R&D Project. Modeling phonon dynamics is crucial for development of functional materials for thermal barrier coating, thermoelectric energy conversion, and thermal management. While the past decade has witnessed significant advancements in ab initio calculations and atomistic simulations for thermal conductivity prediction, complicated modeling tasks remains challenging, such as modeling transient thermal responses, studying high-order anharmonicity, and wavelike transport of phonons and so on. Here, we present API Phonons, a Python software package for predicting the transport dynamics of heat-carrying phonons. Using the powerful syntax of Python, this package provides modules and functions interfacing between different packages for atomistic simulations, lattice dynamics, and phonon-phonon interaction calculations including LAMMPS, Quippy, Phonopy, and ShengBTE. API Phonons have streamlined complex phonon calculations, including (1) extracting harmonic and anharmonic force constants from arbitrary interatomic potentials, which can be used as inputs for solving Boltzmann transport equations; (2) predicting thermal conductivity using Kubo’s linear response theory, which captures both quasiparticle transport and inter-band coherent transport; and (3) modeling of ultrafast pump-probe thermal responses using a Green’s function approach based on mode-resolved phonon properties for studying ballistic, hydrodynamic, and diffusive transport dynamics. The package provides a flexible, easy-to-use, and extensive platform for modeling phonon transport physics through Python programming.（一）欢迎登录mTT2024官方网站：http://mtt2024.csmnt.org.cn 注册参会。
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【学会会员】张倩倩：18811456626
【会议通知】微纳热输运理论、材料与器件国际研讨会
【mTT2024】邀请报告人——曹炳阳
【mTT2024】邀请报告人——焦斌斌
【mTT2024】邀请报告人——马儒军
【mTT2024】邀请报告人——Pawel Keblinski
【mTT2024】邀请报告人——魏进家
