AMaSiS 2018 Workshop: Abstracts

Time and space adaptive multidimensional simulation

of thin-film organic devices

Carlo de Falco${}^{\mathbf{\text{(1)}}}$, Pasquale Africa${}^{\mathbf{\text{(1)}}}$, and Dario Natali${}^{\mathbf{\text{(2,3)}}}$

(1) MOX - Modeling and Scientific Computing, Dipartimento di Matematica, Politecnico di Milano

(2) DEIB - Dipartimento di Elettronica, Informatica e Bioingegneria, Politecnico di Milano

(3) CNST - Center for Nano Science and Technology, IIT@PoliMI

The accurate knowledge of relevant physical parameters is crucial to determine the predictive accuracy of numerical models for organic semiconductor devices. We present a step-by-step procedure enabling to determine critical model parameters - such as the density of states width, the carrier mobility and the injection barrier - by fitting experimental data from a sequence of relatively simple measurements to 2D numerical simulations under different regimes. The current presentation extends the results of [3, 2] where 1D models were used both for transient simulation of Metal-Insulator-Semiconductor (MIS) capacitors and for the estimating the DC transfer characteristics of Organic Thin-Film Transistors in the linear regime. The newly developed 2D simulator allows to account in a more natural way for a set of inherently two-dimensional phenomena, such as: the non-planarity of the semiconductor/insulator interface (due to the solution processing of materials); parasitic capacitances due to coupling between metal layers; the boundary condition at the semiconductor/substrate interface; contact resistance due to current-crowding effects. In order to deal with the increased complexity of numerical simulations in the new 2D setting efficient numerical methods based on a suitable a-posteriori error estimator and adaptive mesh refinement have been implemented [1]. Our approach is tested on a benchmark semiconducting polymer: a very satisfactory fitting of experimental measurements is achieved and physically meaningful values for the extracted parameters are obtained, thus confirming the strategy effectiveness.