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Super-exchange mechanism and quantum many body excitations in the archetypal hemocyanin/tyrosinase di-Cu oxo-bridge

Accepted version
Peer-reviewed

Type

Article

Change log

Authors

al-Badri, Mohamed Ali 
Georges, Antoine 
Cole, Daniel J 
Weber, Cédric 

Abstract

We perform first-principles quantum mechanical studies of dioxygen ligand binding to the hemocyanin protein. Electronic correlation effects in the functional site of hemocyanin are investigated using a state-of-the-art approach, treating the localised copper 3\emph{d} electrons with cluster dynamical mean field theory (DMFT) for the first time. This approach has enabled us to account for dynamical and multi-reference quantum mechanics, capturing valence and spin fluctuations of the 3\emph{d} electrons. Our approach explains the stabilisation of the experimentally observed di-Cu singlet for the butterflied Cu2O2 core, with localised charge and incoherent scattering processes across the oxo-bridge that prevent long-lived charge excitations, suggesting that the magnetic structure of hemocyanin is largely influenced by the many-body corrections. Our computational model is supported by agreement with experimental optical absorption data, and provides a revised understanding of the bonding of the peroxide to the di-Cu system \emph{in vivo}.

Description

Keywords

cond-mat.str-el, cond-mat.str-el

Journal Title

Communcations Physics

Conference Name

Journal ISSN

2399-3650
2399-3650

Volume Title

3

Publisher

Nature
Sponsorship
Engineering and Physical Sciences Research Council (EP/L015552/1)
This work was supported by BBSRC (grant BB/M009513/1), EPSRC (grants EP/N02396X/1, EP/L015552/1) and the Rutherford Foundation Trust. The Flatiron Institute is a division of the Simons Foundation. C.W. gratefully acknowledges the support of NVIDIA Corporation with the donation of the Tesla K40 GPUs used for this research. For computational resources, we were supported by the ARCHER UK National Supercomputing Service and the UK Materials and Molecular Modelling Hub for computational resources (EPSRC Grant No. EP/P020194/1).