Brandt, R.E.; Kurchin, R.C.; Steinmann, V.; Kitchaev, D.; Roat, C.; Levcenco, S.; Ceder, G.; Unold, T.; Buonassisi, T.: Rapid photovoltaic device characterization through Bayesian parameter estimation. Joule 1 (2017), p. 843-856
10.1016/j.joule.2017.10.001
Open Access Version (externer Anbieter)
Abstract:
In photovoltaic (PV) materials development, the complex relationship between device performance and underlying materials parameters obfuscates experi- mental feedback from current-voltage (J-V) characteristics alone. Here, we address this complexity by adding temperature and injection dependence and applying a Bayesian inference approach to extract multiple device-relevant ma- terials parameters simultaneously. Our approach is an order of magnitude faster than the cumulative time of multiple individual spectroscopy techniques, with added advantages of using device-relevant materials stacks and interface con- ditions. We posit that this approach could be broadly applied to other semicon- ductor- and energy-device problems of similar complexity, accelerating the pace of experimental research.