A Multi Objective Evolutionary Algorithm for the Parameters Extraction of Organic Thin Film Transistors Models

Thanks to their peculiar features, organic transistors are proving to be a valuable alternative to traditional semiconducting devices in several application fields; however, before releasing their exploitation, simulating their behaviour through adequate circuital models could be advisable during the design stage of electronic circuits and/or boards. Consequently, accurately extracting the parameter value of those models is fundamental to developing useful libraries for hardware design environments. To face the considered problem, the authors present a method based on successive application of Single- and Multi-Objective Evolutionary Algorithm for the optimal tuning of model parameters of organic transistors on thin film (OTFT). In particular, parameters are first roughly estimated to assure the best fit with the experimental transfer characteristics; the estimates are successively refined through the multi-objective strategy by also matching the values of the experimental mobility. The performance of the method has been assessed by estimating the parameters value of both P-type and N-type OTFTs characterized by different values of channel lengths; the obtained results evidence that the proposed method can obtain suitable parameters values for all the considered channel length