A method to rapidly predict the charge injection rate in dye sensitized solar cells

文献情報

出版日 2010-03-16

DOI 10.1039/B926157E

インパクトファクター 3.676

著者

Daniel R. Jones, Alessandro Troisi

原文を見る

要旨

A technique to predict the rate of electron transfer between a chromophore and the TiO2 semiconductor surface in dye sensitized solar cells (DSSC) is presented. The rate is computed by partitioning the system into molecular and semiconductor states and computing the retarded Green's function for the system. A number of recently reported organic chromophores are considered and the results are rationalized in terms of the orbital shape and the energy alignment between molecular and semiconductor states. The method is designed to allow a rapid scanning of potential chromophores as the expensive components of the calculation (computing the density of states on the TiO2 surface and the coupling between these states and the molecule) are performed once for all chromophores with similar adsorption chemistry. With this technique it is possible to predict the rate of injection of a new chromophore in a few hours using a desktop computer and routine quantum chemistry packages.

掲載誌

Physical Chemistry Chemical Physics

CiteScore: 5.5

自己引用率: 10.3%

年間論文数: 3036

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.