Numerical and experimental investigation of Process Structure Property relationship in Organic Photovoltaics

Abstract

Organic Photovoltaics (OPVs) are considered to be potential contenders amongst the third-generation solar technologies. The primary reason for their popularity has been the possibility of applying various cost-effective solvent-based techniques for active layer deposition such as spin-coating, ink-jet and flexographic printing. The processing parameters influence the underlying Bulk-Heterojunction (BHJ) morphology and, subsequently, the device performance. Therefore, optimum OPV performance depends on understanding the Process-Structure-Property (PSP) correlation in organic-semiconductors. In this thesis, experiments were carried out on model P3HT:PCBM (donor-acceptor) system to study the effect of blend ratio between polymer (P3HT) and fullerene derivative (PCBM) as well as the influence of annealing time on device performance. However, since the optimization of the processing parameters, particularly for deriving active-layer BHJ morphologies with high efficiencies is non-trivial as the parameter space is large, the adoption of a theoretical framework becomes necessary. In the theoretical framework, we present an approach for deriving both the process-structure and structure-property correlations based on the diffuse-interface method. Herein, we derive process-structure correlations using phase-field simulations based on the Cahn-Hilliard formalism for modelling phase-separation. Utilizing the process-structure model, a range of morphologies as a result of processing parameters such as blend ratio, annealing time, and evaporation rate of solvent are generated. Thereafter, we derive the structure-property correlations again using a diffuse interface approach for calculating the electronic properties such as the efficiency, fill-factor, short-circuit current, and the open-circuit voltages for the simulated microstructures. Thus, using a combination of the process--structure and structure-property correlations, optimal compositions can be determined...