Elements: FourPhonon: A Computational Tool for Higher-Order Phonon Anharmonicity and Thermal Properties

元素：FourPhonon：高阶声子非谐性和热性质的计算工具

• 批准号: 2311848
• 负责人: Xiulin Ruan
• 金额: $ 60万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2026-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2311848&HistoricalAwards=false
• 关键词: Elements; FourPhonon; Computational; Tool; Higher

Thermal conductivity of materials is important in many emerging applications, such as thermal management of semiconductor devices, insulation materials for buildings, thermal barrier coatings, and thermoelectric waste heat recovery. Heat is carried by phonons, the quantum mechanical description of lattice vibration. Conventionally, thermal conductivity was considered to be controlled by the scattering processes that involve three phonons, but recently it has been discovered that the scattering processes that involve four phonons can play a significant or even leading role. Predicting four-phonon scattering and the resulting thermal conductivity, however, is extremely challenging due to the complex formulation and tremendous computational cost even for the simplest materials. To address these challenges, this project is aimed at the development and optimization of an open-source computational package, FourPhonon, to enable interested users to perform such calculations for their materials and applications. Approaches based on GPU and machine learning will also be developed to significantly accelerate the speed of computation. The project will transform four-phonon scattering from a breakthrough to a new routine capability for academia and industry in the coming decade.The objective of this project is to enhance FourPhonon, an open-source code that was deployed by a team led by the PI and can be used to predict four-phonon scattering rates and the resulting thermal conductivity. Since the release of the first version of FourPhonon, it has been used by many researchers worldwide for their materials and applications. However, upgrades in computational methods are needed to keep up with theoretical advances, and acceleration of computation is necessary considering the large or even unaffordable computational cost. In this proposal, the investigators will fulfill these needs by enhancing FourPhonon. For the base version, the project will: (1) develop an interface that can implement temperature-dependent force constants, which will enable the capability of the inclusion of phonon renormalization and phase transition phenomena, and (2) enable the full iterative scheme of both three- and four-phonon scattering channels. For the advanced features, the project will: (1) accelerate the computation of four-phonon scattering using GPU parallelization via heterogeneous computing, and (2) accelerate the computation via machine learning models that are trained on datasets of a small fraction of the scattering processes. The improved FourPhonon package will enable accurate and affordable prediction of thermal conductivity of a large number of materials that are technologically significant.This award by the Office of Advanced Cyberinfrastructure is jointly supported by the Division of Chemical, Bioengineering, Environmental, and Transport Systems within the Directorate for Engineering.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

材料的导热性在许多新兴应用中非常重要，例如半导体器件的热管理、建筑物的隔热材料、热障涂层和热电废热回收。热量由声子携带，声子是晶格振动的量子力学描述。传统上，热导率被认为是由涉及三个声子的散射过程控制的，但最近发现涉及四个声子的散射过程可以发挥重要甚至主导作用。然而，由于复杂的公式和巨大的计算成本（即使是最简单的材料），预测四声子散射和由此产生的热导率也极具挑战性。为了应对这些挑战，该项目旨在开发和优化开源计算包 FourPhonon，以使感兴趣的用户能够针对其材料和应用执行此类计算。还将开发基于 GPU 和机器学习的方法，以显着加快计算速度。该项目将在未来十年内将四声子散射从突破性转变为学术界和工业界的新常规能力。该项目的目标是增强 FourPhonon，这是由 PI 领导的团队部署的开源代码并可用于预测四声子散射率和由此产生的热导率。自从 FourPhonon 的第一个版本发布以来，它已被世界各地的许多研究人员用于其材料和应用。然而，需要计算方法的升级以跟上理论的进步，考虑到巨大甚至难以承受的计算成本，计算加速是必要的。在此提案中，研究人员将通过增强 FourPhonon 来满足这些需求。对于基础版本，该项目将：（1）开发一个可以实现与温度相关的力常数的接口，这将能够包含声子重正化和相变现象，以及（2）启用完整的迭代方案三声子和四声子散射通道。对于高级功能，该项目将：(1) 通过异构计算使用 GPU 并行化加速四声子散射的计算，(2) 通过在一小部分散射数据集上训练的机器学习模型加速计算流程。改进后的 FourPhonon 包将能够准确且经济地预测大量具有技术意义的材料的热导率。该奖项由高级网络基础设施办公室颁发，并得到了化学、生物工程、环境和运输系统部门的共同支持。工程理事会。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。