Multifractal analysis of Mg-doped ZnO thin films deposited by sol–gel spin coating method

A multifractal analysis has been performed on the 3D (three-dimensional) surface microtexture of magnesium-doped zinc oxide (ZnO:Mg) thin films with doping concentration of 0, 2, 4, and 5%. Thin films were deposited onto the glass substrates via the sol–gel spin coating method. The effect of magnesium doping, on the crystal structure, morphology, and band gap for ZnO:Mg thin films has been analyzed by X-ray diffraction (XRD), scanning electron microscopy (SEM), atomic force microscopy (AFM), and UV–Vis spectroscopy. It has been observed that the surface of ZnO thin films is multifractal in nature. However, multifractality and complexity observed to decrease with increasing content of Mg in ZnO thin films due to formation of islands on the surface in accordance with Volmer–Weber growth mechanism. The investigations revealed that crystallinity, microtexture, morphology, and optical properties of the thin films can be tuned by controlling the Mg content within the ZnO lattice. In particular, their optical band gap energies were 3.27, 3.31, 3.34, and 3.33 eV at 0, 2, 4, and 5%, respectively. The prepared thin films of ZnO:Mg with tuned characteristics would have promising applications in optoelectronic devices.     

Supply chain network optimization considering assembly line balancing and demand uncertainty

In supply chain optimisation problems, determining the location, number and capacity of facilities is concerned as strategic decisions, while mid-term and short-term decisions such as assembly policy, inventory levels and scheduling are considered as the tactical and operational decision levels. This paper addresses the optimisation of strategic and tactical decisions in the supply chain network design (SCND) under demand uncertainty. In this respect, a two-stage stochastic programming model is developed in which strategic location decisions are made in the first-stage, while the second-stage contains SCND problem and the assembly line balancing as a tactical decision. In the solution scheme, the combination of sample average approximation and Latin hypercube sampling methods is utilised to solve the developed two-stage mixed-integer stochastic programming model. Finally, computational experiments on randomly generated problem instances are presented to demonstrate the performance and power of developed model in handling uncertainty. Computational experiments showed that stochastic model yields better results compared with deterministic model in terms of objective function value, i.e. the sum of the first-stage costs and the expected second-stage costs. This issue proved that uncertainty would be a significant and fundamental element of developed model and improve the quality of solutions.     

Microstructure and thermoelectric performance evaluation of p-type (Bi,Sb)2Te3 materials synthesized using mechanical alloying and spark plasma sintering process

Journal of Materials Science: Materials in Electronics - In this paper, three p-type thermoelectric compounds, namely Bi0.5Sb1.5Te3, Bi0.3Sb1.7Te3, and Bi0.2Sb1.8Te3 were manufactured by mechanical...