Work

Simulating the dynamics of NV− formation in diamond in the presence of carbon self-interstitials

Year: 2025

Type: article

Abstract: This study utilises linear-scaling density functional theory (DFT) and develops a new machine-learning potential for carbon and nitrogen (GAP-CN), based on the carbon potential (GAP20), to investigate the interaction between carbon self-interstitials and nitrogen-vacancy (NV) centres in diamond, focusing on their excited states and diffusion behaviour. From the simulated excited states, 'Bright', 'Spike', and 'Dark' defect configurations are classified based on their absorption spectrum features. Furthermore, machine learning molecular dynamics simulation provides insight into the possible diffusion mechanism of C i and NV, showing that C i can diffuse away or recombine with NV. The study yields new insight into the formation of NV defects in diamond for quantum technology applications.

Source: npj Computational Materials

DOI: 10.1038/s41524-025-01605-6

Authors: Guangzhao Chen, Joseph C. A. Prentice, Jason M. Smith

Institutions: Lawrence Berkeley National Laboratory, University of Oxford, Molecular Foundry, University of Manchester

Language: English

Topic: Diamond and Carbon-based Materials Research

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $3,490

Funders: St. Edmund Hall, University of Oxford, University of Oxford