Strong scientific interests focus on the investigation of iodine-free redox couples for their application in dye-sensitized solar cells (DSCs). Recently, a disulfide/thiolate-based redox electrolyte has been proposed as a valuable alternative to the conventional I 3 À /I À system due to its transparent and noncorrosive nature. In the work presented herein, we systematically studied the influence of different counter electrode materials on the photovoltaic performance of DSCs employing this promising organic redox electrolyte. Our investigations focused on understanding the importance of electrocatalytic activity and surface area of the electroactive material on the counter electrode, comparing the conventional platinum to cobalt sulfide (CoS) and poly(3,4-ethylenedioxythiophene) (PEDOT). Electrochemical Impedance Spectroscopy has been used to study in detail the interfacial charge transfer reaction at the counter electrode. By using a high surface area PEDOT-based counter electrode, we finally achieved an unprecedented power conversion efficiency of 7.9% under simulated AM1.5G solar irradiation (100 mW cm À2 ) which, to the best of our knowledge, represents the highest efficiency that has so far been reported for an organic redox couple.
This paper is dealing with estimation and model selection in the Latent Block Model (LBM) for categorical data. First, after providing sufficient conditions ensuring the identifiability of this model, it generalises estimation procedures and model selection criteria derived for binary data. Secondly, it develops Bayesian inference through Gibbs sampling. And, with a well calibrated non informative prior distribution, Bayesian estimation is proved to avoid the traps encountered by the LBM with the maximum likelihood methodology. Then model selection criteria are presented. In particular an exact expression of the integrated completed likelihood (ICL) criterion requiring no asymptotic approximation is derived. Finally numerical experiments on both simulated and real data sets highlight the interest of the proposed estimation and model selection procedures.
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