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 betwee...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 Ci and NV,showing that Ci can diffuse away or recombine with NV.The study yields new insight into the formation of NV defects in diamond for quantum technology applications.展开更多
基金the use of the University of Oxford Advanced Research Computing(ARC)facility in carrying out this work(https://doi.org/10.5281/zenodo.22558).Additionally,we acknowledge the use of NQIT computing nodes and the Quantum Computing and Simulation Hub.J.C.A.P.acknowledges the support of St.Edmund Hall,University of Oxford,through the Cooksey Early Career Teaching and Research Fellowship,and the embedded CSE programme of the ARCHER UK National Supercomputing Service.We extend our thanks to Yuxing Zhou for valuable suggestions on ML potential training,to Xingrui Cheng for providing experimental data,and to Jacx Chan for offering meaningful insights for this work.
文摘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 Ci and NV,showing that Ci can diffuse away or recombine with NV.The study yields new insight into the formation of NV defects in diamond for quantum technology applications.
