AI 中文总结
本研究提出基于波动力学的框架，结合NSGA-II遗传算法，识别出热阻达此前超晶格3000倍的新型超晶格，可用于极低温热绝缘及声子阻塞组件等技术。
AI 中文摘要
在低温下，声子成为主要的能量载流子之一，因此会强烈影响电子器件和传感器件的性能。本研究提出一种基于波动力学的框架，该框架可预测任意厚度超晶格的声子透射率和热阻，同时保留所有声学支、模式转换路径和入射角。通过强制相位相干性，该模型可预测任意多层结构的频率相关透射率。我们采用遗传算法（NSGA-II）高效选择材料和层厚，成功准则是构成层满足目标温度下主导声子频率的四分之一波长条件。该策略识别出新型双层组合，其热阻可达此前报道超晶格的3000倍。所识别的超晶格有望推动任何依赖相干声子散射的技术发展，从超导倒装芯片组件中的极低温热绝缘到微纳机电系统中的声子阻塞组件。
英文摘要
At cryogenic temperatures, phonons become one of the dominant energy carriers and thus can strongly influence the performance of electronic and sensing devices. In this work, we present a wave-mechanics based framework that predicts phonon transmission and thermal resistance of arbitrarily thick superlattices while retaining all acoustic branches, mode-conversion pathways, and angles of incidence. By enforcing phase coherence, our model predicts frequency-dependent transmission through arbitrary multi-layered structures.We use a genetic algorithm (NSGA-II) to efficiently select both materials and layer thicknesses. Our success criterion is that constituent layers satisfy the quarter-wavelength condition of the dominant phonon frequencies at a target temperature. This strategy identifies novel bilayer combinations that achieve thermal resistance of up to 3000 times greater than previously reported superlattices. The identified superlattices are poised to advance any technology that relies on coherent acoustic scattering, from ultra-low-temperature thermal insulation in superconducting flip-chip assemblies to phonon-blocking components in micro- and nano-electromechanical systems.
Comments21 pages, 9 figures, The following article has been submitted to the Journal of Applied Physics. After it is published, it will be found at (https://publishing.aip.org/resources/librarians/products/journals/)
