The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Dynamical Monte Carlo Modelling of Organic Solar Cells: The Dependence of Internal Quantum Efficiency on Morphology
Abstract
We present a dynamical Monte Carlo study of the dependence of the internal quantum efficiency (IQE) of an organic bulk heterojunction solar cell on the device morphology. The IQE is found to be strongly sensitive to the scale of phase separation in the morphology, with a peak at approximately 20 nm for the PFB/F8BT system studied. An ordered, checkered morphology exhibits a peak IQE 1.5 times higher than a disordered blend.
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Citations
Cites
Efficient bulk heterojunction photovoltaic cells using small-molecular-weight organic thin films
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A brief history of the development of organic and polymeric photovoltaics
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Efficient Monte Carlo methods for the simulation of catalytic surface reactions
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Cited by
Veldman, D., İpek, Ö., Meskers, S. C. J., Sweelssen, J., Koetse, M. M., Veenstra, S. C., Kroon, J. M., van Bavel, S. S., Loos, J., & Janssen, R. A. J. (2008) · Journal of the American Chemical Society · doi:10.1021/ja8012598 · Cited by 577
Gur, I., Fromer, N. A., Chen, C.-P., Kanaras, A. G., & Alivisatos, A. P. (2007) · Nano Letters · doi:10.1021/nl062660t · Cited by 451
Interpretable deep learning for guided microstructure-property explorations in photovoltaics
Pokuri, B. S. S., Ghosal, S., Kokate, A., Sarkar, S., & Ganapathysubramanian, B. (2019) · npj Computational Materials · doi:10.1038/s41524-019-0231-y · Cited by 73
Metadata
- Authors
- Watkins, P. K., Walker, A. B., & Verschoor, G. L. B.
- Venue
- Nano Letters
- Publisher
- American Chemical Society (ACS)
- Published
- 2005-08-10
- Volume
- 5
- Issue
- 9
- Pages
- 1814-1818
- ISSN
- 1530-6984 (ISSN-L)
- 1530-6992
- OpenAlex
- W2050415692
- Cited by
- 395
- References
- 15
- FWCI
- 11.12
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.