Year: 2026
Type: preprint
Abstract: Diamond hosts optically active point defects central to quantum technologies, yet the carbon self-interstitials introduced during growth and irradiation compete with them and form new defects whose configurational landscape is poorly charted, as subtle energy differences govern the competing minima and pathways. Here we build an interstitial-focused dataset by active learning and benchmark three machine-learning interatomic potentials -- GAP, NEP and the equivariant MACE -- against density functional theory for energies, forces and migration barriers. MACE reproduces the reference energetics and relative stabilities, whereas the others can misorder the ground states. Annealing molecular dynamics with the validated potentials uncovers a series of previously unreported carbon interstitial clusters, from di- to octa-interstitials -- several introducing in-gap states of interest as colour centres -- and shows that their metastability is governed by kinetically accessible pathways rather than energetic ordering. These results chart the interstitial defect landscape and accelerate defect discovery for quantum technologies.
Source: arXiv (Cornell University)
Language: English
Subfield: Materials Chemistry
Field: Materials Science
Domain: Physical Sciences
Open Access status: green
Awards: G250002678, Spin based quantum computer and simulator (SPINUS), G4229847087, G4432934295, G4519342690, Multiscale Modeling of Structure and Dynamics of van der Waals Materials, Quantum technology with a spin-photon architecture for thousand-qubit chipsets at telecom wavelengths, Quantum reservoir computing for efficient signal processing, G87479140, G8914310889, Long-Term Thermal Energy Storage with Salt-Based Composite Materials
OpenAlex ID: W7165375478