dc.contributor.author Linscott, Edward dc.date.accessioned 2019-10-11T15:39:12Z dc.date.available 2019-10-11T15:39:12Z dc.date.issued 2019-10-26 dc.date.submitted 2019-08-02 dc.identifier.uri https://www.repository.cam.ac.uk/handle/1810/297751 dc.description.abstract Metalloproteins play a crucial role in many key biological processes, from oxygen transport to photosynthesis. In the case of photosynthesis, the oxygen evolving complex (OEC) --- a CaMn\textsubscript{4}O\textsubscript{5} cluster --- catalyses water-to-oxygen-gas conversion. From a computational standpoint, accurately modelling the electronic structure of the OEC and other metalloproteins \emph{ab initio} is difficult, due to two challenges. Firstly, there is that of the strong electronic correlation present due to the partially-filled $3d$-subshells of the transition metal atoms, a classic example of where semi-local density functional theory (DFT) --- a go-to method for computational physicists --- fails. The second challenge is that of size: as this thesis will demonstrate, we must consider large cluster models that are thousands of atoms in size, which takes us beyond the reach of both plane-wave DFT and quantum chemistry methods. This thesis explores the capacity of density functional theory-plus-$U$ (DFT+$U$) and dynamical mean field theory (DMFT) to meet both of these challenges. It will demonstrate how both DFT+$U$ and DMFT can be readily married with linear-scaling DFT, meaning that these theories can be applied to protein systems containing thousands of atoms. In particular, this thesis presents the unification of ONETEP (a linear-scaling DFT code) and TOSCAM (a DMFT solver). It also presents a novel approach for determining Hubbard and Hund's parameters via linear response that is compatible with linear-scaling DFT and resolves inconsistencies between the linear response method and the DFT+$U$ corrective functional. These techniques are then applied to haem, haemocyanin, and the OEC, providing insight into the role of strong correlation in their electronic structure and function. In so doing, this thesis demonstrates how one can perform large-scale simulations of metalloproteins that account for strong electronic correlation. The results of this thesis are of significant interest due to both the importance of metalloproteins in nature, and the wealth of potential applications that would spring from a thorough understanding of their catalytic and binding properties. dc.description.sponsorship Cambridge Rutherford Memorial Scholarship dc.language.iso en dc.rights Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) dc.rights.uri https://creativecommons.org/licenses/by-nc-sa/4.0/ dc.subject density functional theory dc.subject dynamical mean field theory dc.subject strong electronic correlation dc.subject ONETEP dc.subject DFT+U dc.subject haemocyanin dc.subject oxygen evolving complex dc.subject haem dc.subject photosynthesis dc.subject metalloproteins dc.subject manganese oxide dc.subject hexahydrated transition metals dc.subject heme dc.subject hemocyanin dc.title Accounting for Strong Electronic Correlation in Metalloproteins dc.type Thesis dc.type.qualificationlevel Doctoral dc.type.qualificationname Doctor of Philosophy (PhD) dc.publisher.institution University of Cambridge dc.publisher.department Physics dc.date.updated 2019-10-10T15:08:43Z dc.identifier.doi 10.17863/CAM.44803 dc.contributor.orcid Linscott, Edward [0000-0002-4967-9873] dc.publisher.college Corpus Christi dc.type.qualificationtitle PhD in Physics cam.supervisor Payne, Michael cam.supervisor Cole, Daniel cam.thesis.funding false
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