Calculation of crystal defects induced in CaWO₄ by 100 eV displacement cascades using a linear Machine Learning interatomic potential

2024/06/28 by G. Soum-Sidikov, Jean-Paul Crocombette, Soum-Sidikov, Gabrielle +9 · 1 citation
Physics and Astronomy · #Atomic and Subatomic Physics Research #Dark Matter and Cosmic Phenomena #FOS: Physical sciences #High Energy Physics - Experiment (hep-ex) #Instrumentation and Detectors (physics.ins-det) #Materials Science (cond-mat.mtrl-sci) #Nuclear Experiment (nucl-ex) #Particle physics theoretical and experimental studies

paper · pdf · doi:10.48550/arxiv.2407.00133

openalex publication_date 2024/06/28 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We determine the energy stored in the crystal defects induced by O(10-100) eV nuclear recoils in low-threshold CaWO₄ cryogenic detectors. A Machine Learning interatomic potential is developed to perform molecular dynamics simulations. We show that the energy spectra expected from Dark Matter and neutrino coherent scattering are affected by the crystal defects and we provide reference predictions. We discuss the special case of the spectrum of nuclear recoils induced by neutron capture, which could offer a unique sensitivity to the calculated stored energies.

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• Observation of a low energy nuclear recoil peak in the neutron calibration data of an Al₂O₃ crystal in CRESST-III

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