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Home/e-Resources/Electronics & Telecommunication Engineering/Solcore: a multi-scale, Python-based library for modelling solar cells and semiconductor materials
PeriodicalsElectronics & Telecommunication Engineering

Solcore: a multi-scale, Python-based library for modelling solar cells and semiconductor materials

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Abstract & Overview

Computational models can provide significant insight into the operation mechanisms and deficiencies of photovoltaic solar cells. Solcore is a modular set of computational tools, written in Python 3, for the design and simulation of photovoltaic solar cells. Calculations can be performed on ideal, thermodynamic limiting behaviour, through to fitting experimentally accessible parameters such as dark and light IV curves and luminescence. Uniquely, it combines a complete semiconductor solver capable of modelling the optical and electrical properties of a wide range of solar cells, from quantum well devices to multi-junction solar cells. The model is a multi-scale simulation accounting for nanoscale phenomena such as the quantum confinement effects of semiconductor nanostructures, to micron level propagation of light through to the overall performance of solar arrays, including the modelling of the spectral irradiance based on atmospheric conditions. In this article, we summarize the capabilities in addition to providing the physical insight and mathematical formulation behind the software with the purpose of serving as both a research and teaching tool.

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Diego Alonso‐Álvarez, Tom Wilson, Phoebe Pearce, M. Führer, Daniel Farrell, Nicholas John Ekins‐Daukes (2018). Solcore: a multi-scale, Python-based library for modelling solar cells and semiconductor materials. Journal of Computational Electronics, 17(3), 1099–1123. https://doi.org/10.1007/s10825-018-1171-3

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Alonso‐Álvarez, D., Wilson, T., Pearce, P., Führer, M., Farrell, D., & Ekins‐Daukes, N. J. (2018). Solcore: a multi-scale, Python-based library for modelling solar cells and semiconductor materials. Journal of Computational Electronics, 17(3), 1099–1123. https://doi.org/10.1007/s10825-018-1171-3
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