Two advanced fabrication methods are introduced: the hydrogen peroxide (H₂O₂)-added chemical bath deposition technique and molybdenum (Mo) back-contact formation under 3 kW sputter power. The parameters of the short circuit current density (J _SC) and conversion efficiency (η) were improved over standard cells when the ZnS buffer layer was deposited in the H₂O₂-added chemical solution. Otherwise, the fill-factor and η were best at 3 kW Mo sputtering power conditions. Advanced fabrication methods are realised to improve cell performance without modifying the chemical composition of the Cu(In,Ga)Se₂ absorption layer.

The novel structure of a solar cell is presented that has the metal–oxide-semiconductor diode at the side wall of the power generation layer. The influence of the field-effect on the recombination of carriers is simulated and the increase of the conversion efficiency of the solar cell by the gate voltage application is discussed. In addition, the relationship between the effect of the gate voltage application on the conversion efficiency, the lifetime and the surface recombination velocity is discussed.

Presented is a silicon solar cell model with fully passivated radial junction nanowire surface decoration and submerged nickel-silicide contact. Numerical simulations using a finite-difference time-domain method have been done to investigate the spectral responses of the solar cell model. The experimental results indicate that, with proper nickel-silicide thickness, the fill factor of the cell can be improved considerably without much degradation on short circuit current density. Under AM 1.5G illumination, the silicon nanowire solar cell device with 50 Å nickel-silicide contact has short circuit current density of 26.3 mA/cm2, open circuit voltage of 586 mV and fill factor of 70.0%, contributing to power conversion efficiency of 10.8%, which is 19% higher than the control device without the nickel-silicide contact.

Nanocrystalline TiO2 was prepared through hydrothermal synthesis using tetrabutyl titanate as starting material. With a constant reaction time of 12 h, the reaction temperature was changed from 120 to 160°C and the pH value of the reaction medium was ranged from 1 to 9. Every specimen of the as-prepared TiO2 powder was characterised by X-ray diffraction, a scanning electron microscope, transmission electron microscopy, high-resolution transmission electron microscopy, selected area electron diffraction and was also used to fabricate dye sensitised solar cells (DSSCs). The experimental results showed that the phase of the powder was affected by the pH value, whereas the particle size depended on the reaction temperature. Pure anatase TiO2 was obtained with the pH value of 3. The solar energy conversion efficiency (η) of the DSSC fabricated with the pure anatase TiO2 prepared at 140°C was 3.64%, which was higher than those with the TiO2 prepared under any other conditions. The purchased TiO2 (P25) was used to make a DSSC for comparison. It turned out that the performance of all the DSSCs with TiO2 prepared by hydrothermal synthesis was higher than that with the P25.

With the aim of improving energy conversion efficiency of dye-sensitised solar cells (DSCs), three evolutionary algorithms (EAs), namely genetic algorithm, particle swarm optimisation (PSO) and differential evolution, are investigated the first time to extract the DSCs parameters based on the single-diode photovoltaic (PV) equivalent circuit model. By comparing the accuracy, calculation speed and anti-noise ability of the three EA techniques, PSO shows the highest accuracy and the best anti-noise property. To evaluate the parameters, especially the series-internal resistance (R s) that is important for DSCs energy conversion efficiency, a batch of DSCs devices were made and the R s obtained by changing the series resistance value connected with the DSCs. The two methods give the R s approximately equal value, and almost same current–voltage figures based on PSO simulation with measured characteristics, which prove PSO is an efficient computational method and can be used to extract the parameters for the DSCs PV model.