Structure and energetics of dye-sensitized NiO interfaces in water from ab-initio MD and large-scale GW calculations

The energy level alignment across solvated molecule/semiconductor interfaces is a crucial property for the correct functioning of dye-sensitized photo-electrodes, where, following the absorption of solar light, a cascade of interfacial hole/electron transfer processes has to efficiently take place. In light of the difficulty of performing X-ray photoelectron spectroscopy measurements at the molecule/solvent/metal-oxide interface, being able to accurately predict the level alignment by first-principles calculations on realistic structural models would represent an important step toward the optimization of the device. In this respect dye/NiO surfaces, employed in p-type dye-sensitized solar cells, are undoubtedly challenging for ab initio methods and, also for this reason, much less investigated than the n-type dye/TiO2 counterpart. Here we consider the C343-sensitized NiO surface in water and combine ab initio Molecular Dynamics (AIMD) simulations with GW (G0W0) calculations, performed along the MD trajectory, to reliably describe the structure and energetics of the interface when explicit solvation and finite temperature effects are accounted for. We show that the differential perturbative correction on the NiO and molecule states obtained at GW level is mandatory to recover the correct (physical) interfacial energetics, allowing hole transfer from the semiconductor valence band to the HOMO of the dye. Moreover, the calculated average driving force quantitatively agrees with the experimental estimate.

Identifier
Source https://archive.materialscloud.org/record/2021.108
Metadata Access https://archive.materialscloud.org/xml?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai:materialscloud.org:927
Provenance
Creator Segalina, Alekos; Lèbegue, Sébastien; Rocca, Dario; Piccinin, Simone; Pastore, Mariachiara
Publisher Materials Cloud
Publication Year 2021
Rights info:eu-repo/semantics/openAccess; Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode
OpenAccess true
Contact archive(at)materialscloud.org
Representation
Language English
Resource Type Dataset
Discipline Materials Science and Engineering