In this review, we summarize our work for the computational study and design of functional materials.
by Sandra Luber
ZORA, University of Zurich (2019)
Exerpt: pp. 8-9
3.1 Methodological aspects (excerpt)
A prerequisite for smart design of more efficient WOCs is the understanding of the entire water oxidation process. The catalyst and its water oxidation behaviour have thus to be elucidated thoroughly. This includes the detailed structure of the catalyst as well as the mechanism of water oxidation and related reaction networks such as side, deactivation, and decomposition pathways. We have shown that environmental effects can have a decisive influence on the structure and reactivity of the catalyst. This has, for instance, been elucidated for the generation of the active species for water oxidation (catalytic ground state), which has significantly been affected by the solvent environment [7, 45, 46]. The solvent environment can be included into the calculations in several ways: A solvent continuum model can be used, which mimics “average” solvent effects (fitted for certain test set and thermodynamic conditions) but has shortcomings, e.g., for description of directed bonds such as hydrogen bonds.
In order to ameliorate the latter, explicit solvent molecules may be included into the model, possibly in combination with a solvent continuum model. Subsequent optimization of the model can lead to an improved description of the system but the outcome of the optimization is dependent on the initial guess for the optimization process and may thus not adequately represent the system. In contrast to that, the computationally more expensive AIMD approach allows exploration of the conformational phase space at ambient conditions, thus naturally accounting for aspects like hydrogen-bonding networks and conformational dynamics. This is especially important since water is essential for water oxidation, and its dynamics, associated proton transfers, and hydrogen bonding networks play a vital role. Other ingredients in the reaction mixture, which are usually neglected in the simulations, may also directly interact with the catalyst as shown for possible inhibitory effects of buffer molecules [7].
Abbreviation key
WOC = water oxidation catalyst (Luber 2019: 8)
AIMD = ab initio (DFT-based) molecular dynamics (Luber 2019: 2)
DFT = density functional theory (Lber 2019: 2)
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