Supervisors: James Kermode, Richard Beanland, Thomas Hudson
If a dislocation is present in a light emitting device, it causes failure by acting as a carrier recombination pathway and grows through the material by emitting atoms, eventually shutting of all luminescence. This is a long-standing and significant problem for industrial applications; however, despite the significant technological progress improved knowledge would generate, the atomistic mechanisms underlying recombination-enhanced dislocation climb and its interaction with vacancies and interstitials are poorly understood, with no first principles work reported to date. This PhD project will address this deficiency for the first time using simulation methods that combine quantum mechanical (QM) calculations with machine learning.
You will carry out computational simulations to study dislocations found in semiconductors and FCC metals, which commonly split into two parts or “partials”. Experimental observations of climb of dislocations in semiconductors show that these partials climb by adsorbing interstitial defects (extra atoms in the crystal); however, the details of the atomistic mechanism has not been identified.
Dislocation climb is extremely challenging to address with conventional QM approaches due to the simultaneous need for highly accurate models and large model systems, which have restricted theoretical work to individual dislocation cores . Here, you will overcome this limitation using new theoretical tools that use machine learning and other advanced algorithms to allow dislocations to be modelled at close to quantum mechanical precision but in a much larger simulation box [2, 3].
The project would suit students with strong solid state/theoretical physics, computational chemistry or materials science backgrounds and an interest in computing (no prior experience of programming is required). The project will involve close interaction with an industrial partner and with atomic-resolution TEM experiments carried out in Richard Beanland’s group. Data is already available for dislocation systems in III-V optical devices and diamond.
The project is embedded in the EPSRC Centre for Doctoral Training in Modelling of Heterogeneous Systems (HetSys) at the University of Warwick. Full funding is available for students of any nationality for a 4 year PhD with integrated training, including modules to provide the strong background in electronic structure, continuum mechanics, robust software engineering and predictive modelling needed for this project.
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 P. Grigorev, T. D. Swinburne, and J. R. Kermode, Phys. Rev. Materials 4, 023601 (2020).
 A. P. Bartók, J. R. Kermode, N. Bernstein, and G. Csányi, Phys. Rev. X 8, 041048 (2018).