Effect of selenization conditions on the growth and properties of Cu2ZnSn(S,Se)4 thin films

The opto-electronic properties of copper zinc tin sulfide can be tuned to achieve better cell efficiencies by controlled incorporation of selenium. In this paper we report the growth of Cu2ZnSn(S,Se)4 (CZTSSe) using a hybrid process involving the sequential evaporation of Zn and sputtering of the sulfide precursors of Cu and Sn, followed by a selenization step. Two approaches for selenization were followed, one using a tubular furnace and the other using a rapid thermal processor. The effects of annealing conditions on the morphological and structural properties of the films were investigated. Scanning electron microscopy and energy dispersive spectroscopy were employed to investigate the morphology and composition of the films. Structural analyses were done using X-ray diffraction (XRD) and Raman spectroscopy. Structural analyses revealed the formation of CZTSSe. This study shows that regardless of the selenization method a temperature above 450 °C is required for conversion of precursors to a compact CZTSSe layer. XRD and Raman analysis suggests that the films selenized in the tubular furnace are selenium rich whereas the samples selenized in the rapid thermal processor have higher sulfur content.

A filter inexact-restoration method for nonlinear programming

A new iterative algorithm based on the inexact-restoration (IR) approach combined with the filter strategy to solve nonlinear constrained optimization problems is presented. The high level algorithm is suggested by Gonzaga et al. (SIAM J. Optim. 14:646–669, 2003) but not yet implement—the internal algorithms are not proposed. The filter, a new concept introduced by Fletcher and Leyffer (Math. Program. Ser. A 91:239–269, 2002), replaces the merit function avoiding the penalty parameter estimation and the difficulties related to the nondifferentiability. In the IR approach two independent phases are performed in each iteration, the feasibility and the optimality phases. The line search filter is combined with the first one phase to generate a “more feasible” point, and then it is used in the optimality phase to reach an “optimal” point. Numerical experiences with a collection of AMPL problems and a performance comparison with IPOPT are provided.