Solution-processed CuInGaS2 (CIGS) thin-film solar cells are promising for large-scale commercialization due to their economic process although the efficiency still needs to be improved to compete with vacuum-based materials. Systematic studies were performed to optimize the series and shunt resistance of hydrazine-based CIGS solar cells. Optimization was achieved through compositional adjustment of copper (Cu) near the p–n junction and gallium (Ga) near the back contact. Cu adjustments optimized the shunt resistance between 4000 and 5000 Ω cm2. Ga adjustments optimized the series resistance to 2 Ω cm2. Shunt and series resistance play vital roles in the fill factor. Fill factor was hence improved upward of 0.80 with the optimization of Cu and Ga. Chemical etching was also conducted to investigate the durability of the materials and to remove small crystals near the interface. Device conversion efficiencies were improved up to 12.4%. This study provides the implications for improving the device performance of chalcogenide solar cell materials.

A large-signal model and a simulation technique based on non-sinusoidal voltage excitation are used to obtain the electric field snapshots from which the series resistance and related high-frequency properties of a 35 GHz Silicon Single-Drift Region (SDR) Impact Avalanche Transit Time (IMPATT) device have been estimated for different bias current densities. A novel method is proposed in this paper to determine the parasitic series resistance of a millimeter-wave IMPATT device from large-signal electric field snapshots at different phase angles of a full cycle of steady-state oscillation. The method is based on the depletion width modulation of the device under a large-signal condition. The series resistance of the device is also obtained from the large-signal admittance characteristics at threshold frequency. The values of series resistance of a 35 GHz SDR IMPATT diode obtained from the proposed method and the large-signal admittance method are compared with experimentally reported values. The results show that the proposed method provides better and closer agreement with the experimental value.