Synergy of the ray tracing+carrier transport approach: On efficiency of perovskite solar cells with a back reflector

Enhanced performance of ultrathin n-i-p and p-i-n perovskite solar cells via light trapping: a simulation study employing Lambertian back reflector

“…For the p-i-n configuration, the absorption coefficient for active layer thickness 200 nm in the presence of LBR is seen to be comparable to that for active layer thickness 600 nm in the presence of MBR. While the possibility of two-fold reduction in thickness of active layer with the use of LBR in place of MBR in n-i-p configuration has been reported previously [28], to the best of knowledge of authors the more profound three-fold possible decrease in thickness of active layer for the p-i-n configuration has not been reported. It is worth reiterating that this enhanced absorption seen in the case of p-i-n configuration is due to the larger light scattering angles for the diffuse scattered light in the active layer compared to that seen in n-i-p configuration.…”

“…Different light trapping approaches have been proposed in the last few years for PSCs, such as textured front and rear surfaces [16], fibre array based anti-reflection front electrodes [12], UV downshifting and light trapping [17], nanophotonic front and back electrodes [18], design of nano prism structures at perovskite-CIGS interface [19], utilization of Lambertian back reflector (LBR) [20], as well as exploitation of carbon dot-wrapped perovskites [21]. Among these, of particular importance is the utility of LBR in light trapping vis-à-vis texturing of surfaces.…”

“…The performance is compared with that of a standard PSC configuration with metallic back reflector (MBR). Similar studies [27,28] have explored the use of LBR in MAPbI 3 PSCs in the standard n-i-p configuration combining Monte-Carlo technique and transfer-matrix method to model the diffuse and coherent light propagation respectively. We extend these works to explore optimization in both n-i-p and p-i-n (inverted) structures, and also study the effect of photon recycling in these cells.…”

OTSun, a python package for the optical analysis of solar-thermal collectors and photovoltaic cells with arbitrary geometry

“…We discuss here two experiments showing how the results obtained with OTSun are compared with those obtained using other software tools, hence providing a validation for both our model and our implementation. A third validation example, related to the optical behaviour of perovskite solar cells, can be found in [2]. In each case, we have compared the results obtained by OTSun with a reference model using both the mean error (ME), so that we can determine if OTSun has an overall tendency to overestimate or underestimate the results, and the root mean square error (RMSE), to evaluate the global accuracy.…”

“…Furthermore, and regardless of the solar collector technology, the solar energy device can also be considered as an optical system, designed to maximize the absorption of solar radiation. Thus, the optical characterization of such devices is the key underpinning for improving solar energy conversion technologies [2].…”