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JAX-BTE: a GPU-accelerated differentiable solver for phonon Boltzmann transport equations

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Publikašuvnnas:NPJ Computational Materials vol. 11, no. 1 (2025), p. 129
Almmustuhtton:
Nature Publishing Group
Fáttát:
Boltzmann transport equation
Solvers
Thermal analysis
Semiconductor devices
Graphics processing units
Phonons
Machine learning
Simulation
Programming languages
Accuracy
Physics
Back propagation
Inverse problems
Optimization
Neural networks
Efficiency
Parameter estimation
Liŋkkat:Citation/Abstract
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Abstrákta:This paper introduces JAX-BTE, a GPU-accelerated, differentiable solver for the phonon Boltzmann Transport Equation (BTE) based on differentiable programming. JAX-BTE enables accurate, efficient and differentiable multiscale thermal modeling by leveraging high-performance GPU computing and automatic differentiation. The solver efficiently addresses the high-dimensional and complex integro-differential nature of the phonon BTE, facilitating both forward simulations and data-augmented inverse simulations through end-to-end optimization. Validation is performed across a range of 1D to 3D simulations, including complex FinFET structures, in both forward and inverse settings, demonstrating excellent performance and reliability. JAX-BTE significantly outperforms state-of-the-art BTE solvers in forward simulations and uniquely enables inverse simulations, making it a powerful tool for multiscale thermal analysis and design for semiconductor devices.
ISSN:2057-3960
DOI:10.1038/s41524-025-01635-0
Gáldu:Health & Medical Collection