Semiconductor parameter extraction via current-voltage characterization and Bayesian inference methods
| Autor: | Ville Vähänissi, Hannu S. Laine, Gerbrand Ceder, Tonio Buonassisi, Jeremy R. Poindexter, Daniil A. Kitchaev, Carlos del Cañizo, Sergiu Levcenco, Liu Zhe, Chris Roat, Rachel C. Kurchin |
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| Přispěvatelé: | Massachusetts Institute of Technology, Aalto Nanofab, Technical University of Madrid, Department of Electronics and Nanoengineering, Helmholtz Centre Berlin for Materials and Energy, Alphabet Inc., Aalto-yliopisto, Aalto University |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Work (thermodynamics)
Computer science 020209 energy ta221 photovoltaic cells 02 engineering and technology Bayesian inference Set (abstract data type) 0202 electrical engineering electronic engineering information engineering Electronic engineering Limit (mathematics) Telecomunicaciones ta114 ta213 Estimation theory Scale (chemistry) charge carrier mobility silicon Inverse problem 021001 nanoscience & nanotechnology Bayes methods Characterization (materials science) Electrónica 0210 nano-technology charge carrier lifetime parameter estimation |
| Zdroj: | Proceedings of 7th World Conference on Photovoltaic Energy Conversion (WCPEC) IEEE 2018 | Proceedings of IEEE 7th World Conference on Photovoltaic Energy Conversion (WCPEC) | 10/06/2018-15/06/2018 | Waikoloa (USA) Archivo Digital UPM Universidad Politécnica de Madrid |
| Popis: | Defects in semiconductors, although atomistic in scale and often scarce in concentration,frequently represent the performance-limiting factor in optoelectronic devices such as solar cells. However, due to this scale and scarcity, direct experimental characterization of defectsis technically challenging, timeconsuming, and expensive. Even so, the fact that defects can limit device performance suggests that device-level characterization should be able to lend insight into their properties. In this work, we use Bayesian inference to demonstrate a way to relate experimental device measurements with defect properties (as well as other materials properties affected by the presence of defects, such as minority-carrier lifetime). We apply this method to solve the 'inverse problem' to a forward device model - namely, determining which input parameters to the model produce the measured electrical output. This approach has distinct advantages over direct characterization. First, a single set of measurements can beused to determine many parameters (the number of which, in principle, is limited only by the computingresources available), saving time and cost of facilities and equipment. Second, sincemeasurements are performed on materials and interfaces in their relevant device geometries (vs.separately prepared samples), the determined parameters are guaranteed to be physically relevant. We demonstrate application of this method to both tin monosulfide and silicon solar cellsand discuss potential for future application in a broader array of systems. |
| Databáze: | OpenAIRE |
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