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

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.