Growth and Raman scattering characterization of Cu2ZnSnS4 thin films

In the present work we report the results of the growth, morphological and structural characterization of Cu2ZnSnS4 (CZTS) thin films prepared by sulfurization of DC magnetron sputtered Cu/Zn/Sn precursor layers. The adjustment of the thicknesses and the properties of the precursors were used to control the final composition of the films. Its properties were studied by SEM/EDS, XRD and Raman scattering. The influence of the sulfurization temperature on the morphology, composition and structure of the films has been studied. With the presented method we have been able to prepare CZTS thin films with the kesterite structure.

Cu2ZnSnS4 solar cells prepared with sulphurized dc-sputtered stacked metallic precursors

In the present work we report the details of the preparation and characterization results of Cu2ZnSnS4 (CZTS) based solar cells. The CZTS absorber was obtained by sulphurization of dc magnetron sputtered Zn/Sn/Cu precursor layers. The morphology, composition and structure of the absorber layer were studied by scanning electron microscopy, energy dispersive spectroscopy, X-ray diffraction and Raman scattering. The majority carrier type was identified via a hot point probe analysis. The hole density, space charge region width and band gap energy were estimated from the external quantum efficiency measurements. A MoS2 layer that formed during the sulphurization process was also identified and analyzed in this work. The solar cells had the following structure: soda lime glass/Mo/CZTS/CdS/i-ZnO/ZnO:Al/Al grid. The best solar cell showed an opencircuit voltage of 345 mV, a short-circuit current density of 4.42 mA/cm2, a fill factor of 44.29% and an efficiency of 0.68% under illumination in simulated standard test conditions: AM 1.5 and 100 mW/cm2.

Study of polycrystalline Cu2ZnSnS4 films by Raman scattering

Cu2ZnSnS4 (CZTS) is a p-type semiconductor that has been seen as a possible low-cost replacement for Cu(In,Ga)Se2 in thin film solar cells. So far compound has presented difficulties in its growth, mainly, because of the formation of secondary phases like ZnS, CuxSnSx+1, SnxSy, Cu2−xS and MoS2. X-ray diffraction analysis (XRD), which is mostly used for phase identification cannot resolve some of these phases from the kesterite/stannite CZTS and thus the use of a complementary technique is needed. Raman scattering analysis can help distinguishing these phases not only laterally but also in depth. Knowing the absorption coefficient and using different excitation wavelengths in Raman scattering analysis, one is capable of profiling the different phases present in multi-phase CZTS thin films. This work describes in a concise form the methods used to grow chalcogenide compounds, such as, CZTS, CuxSnSx+1, SnxSy and cubic ZnS based on the sulphurization of stacked metallic precursors. The results of the films’ characterization by XRD, electron backscatter diffraction and scanning electron microscopy/energy dispersive spectroscopy techniques are presented for the CZTS phase. The limitation of XRD to identify some of the possible phases that can remain after the sulphurization process are investigated. The results of the Raman analysis of the phases formed in this growth method and the advantage of using this technique in identifying them are presented. Using different excitation wavelengths it is also analysed the CZTS film in depth showing that this technique can be used as non destructive methods to detect secondary phases.

Quantum-based Particle Swarm Optimization Application to Studies of Aggregated Consumption Shifting and Generation Scheduling in Smart Grids

Demand response programs and models have been developed and implemented for an improved performance of electricity markets, taking full advantage of smart grids. Studying and addressing the consumers’ flexibility and network operation scenarios makes possible to design improved demand response models and programs. The methodology proposed in the present paper aims to address the definition of demand response programs that consider the demand shifting between periods, regarding the occurrence of multi-period demand response events. The optimization model focuses on minimizing the network and resources operation costs for a Virtual Power Player. Quantum Particle Swarm Optimization has been used in order to obtain the solutions for the optimization model that is applied to a large set of operation scenarios. The implemented case study illustrates the use of the proposed methodology to support the decisions of the Virtual Power Player in what concerns the duration of each demand response event.