- Open Access
Unveiling thermal transport mechanisms in alumina laser crystal using machine learning potential
Phys. Rev. Research 8, 033238 – Published 27 August, 2026
DOI: https://doi.org/10.1103/ld32-gzc3
Abstract
Heat dissipation capability of laser gain media is critical for ensuring the performance and stability of high-power laser systems. However, the thermal transport mechanisms in these materials, particularly in rare-earth ion-doped laser crystals under high-power heating conditions, remain largely elusive. In this study, we employ molecular dynamics simulations combined with a neuroevolution machine learning potential to investigate the effects of temperature and Ce doping on thermal transport in alumina. Our simulations reveal a significant reduction in thermal conductivity under uniform elevated temperatures and finite Ce doping concentrations, providing quantitative insight into thermal transport in Ce-doped under conditions relevant to laser operation. Simulation results demonstrate that elevated temperature causes a broad-spectrum suppression of thermal transport, while Ce doping predominantly affects specific low-frequency acoustic phonon modes and a few optical modes. Further analysis uncovers a mode-selective phonon-dopant scattering mechanism, where resonant and polarization-dependent coupling leads to the selective suppression of distinct phonon modes. This mechanism is in sharp contrast with the conventional understanding of phonon-dopant scattering observed in typical crystals. These findings provide valuable insights into the atomic-level mechanisms governing heat dissipation in alumina laser crystal, thus paving the way for the design of laser materials with optimized thermal properties for high-power applications.
Physics Subject Headings (PhySH)
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