Professor Chris Groves chris.groves@durham.ac.uk
Professor
This Perspective discusses the physics, implementation and findings of Kinetic Monte Carlo (KMC) models applied to organic photovoltaic devices (OPVs). It is shown that KMC models can relate morphology and energy levels on the nano-scale to geminate and non-geminate recombination, charge transport, charge injection and charge extraction measured in macro-scale OPVs. In particular, KMC investigations probing the circumstances under which geminate recombination is, and is not, a significant loss mechanism in OPVs are reviewed. Furthermore, the mechanisms which yield non-geminate (bimolecular) recombination in OPVs that is both slower than the predictions of Langevin, and charge density dependent, are discussed. It is also shown how KMC models can predict average mobility, as well as spatial heterogeneity and temporal dispersion around this average value in disordered bulk heterojunctions. Finally, it is shown how KMC can be used to quantify the effect of non-ideal electrodes, interlayers and surface wetting layers on OPV performance.
Groves, C. (2013). Developing understanding of organic photovoltaic devices: kinetic Monte Carlo models of geminate and non-geminate recombination, charge transport and charge extraction. Energy & Environmental Science, 6(11), 3202-3217. https://doi.org/10.1039/c3ee41621f
Journal Article Type | Article |
---|---|
Publication Date | Nov 1, 2013 |
Deposit Date | Oct 9, 2013 |
Journal | Energy & Environmental Science |
Print ISSN | 1754-5692 |
Electronic ISSN | 1754-5706 |
Publisher | Royal Society of Chemistry |
Peer Reviewed | Peer Reviewed |
Volume | 6 |
Issue | 11 |
Pages | 3202-3217 |
DOI | https://doi.org/10.1039/c3ee41621f |
Public URL | https://durham-repository.worktribe.com/output/1476292 |
Decarbonising electrical grids using photovoltaics with enhanced capacity factors
(2023)
Journal Article
Modelling the effect of dipole ordering on charge-carrier mobility in organic semiconductors
(2023)
Journal Article
In-Materio Extreme Learning Machines
(2022)
Book Chapter
Towards Intelligently Designed Evolvable Processors
(2022)
Journal Article
Single event burnout sensitivity of SiC and Si
(2022)
Journal Article
About Durham Research Online (DRO)
Administrator e-mail: dro.admin@durham.ac.uk
This application uses the following open-source libraries:
Apache License Version 2.0 (http://www.apache.org/licenses/)
Apache License Version 2.0 (http://www.apache.org/licenses/)
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search