Project Level: Honours, Masters, PhD, Summer

Atomic defects in solids are one of the most promising single-photon sources or 'quantum emitters', an important building block for many quantum technologies. In order to design and engineer better quantum emitters, a fundamental understanding of their optical and electronic properties, as well as defect formation and migration, is essential. In this project, first-principles quantum mechanical calculations combined with machine-learning techniques are used in order to uncover key properties such as defect dynamics, formation mechanisms, free energies and stabilities at room and elevated temperatures. The theoretical insights gained in the project aim to inform the design of atomic defects systems for tailored applications as quantum emitters. The student will gain experience with high-performance computing and materials simulation methods, in particular first-principles methods and machine-learned potentials.

Project members

Dr Carla Verdi

ARC DECRA Fellow
Physics