ZnO nanoparticles have numerous applications as photo catalysts, gas sensors, UV lasers, as optoelectronic and microelectronic devices or in cosmetic field. ZnO nanoparticles were synthesized by solvent free method using zinc nitrate hexahydrate as precursor and glycerol as dispersant, without solvent present. This method proved to be very simple, economic and ecofriendly. Zinc nitrate and glycerol were mixed in different ratio in order to avoid and overcome a possibility of agglomeration. Characterization of samples was performed by UV/VIS and FTIR spectrophotometry. The strongest absorption appeared at wavelength 206 nm. Using combination of UV/VIS spectrophotometry and hyperbolic band model (HBM) particles size of ZnO particles were evaluated to 2.06 nm. Additionally, using Tauc plot, a band gap energy was determined. Band gap energy of ZnO nanoparticles amounted to 5.00 eV. IR spectrum showed existence of ZnO in interval 600- 400 cm-1.
In a network, a k-plex represents a subset of n vertices where the degree of each vertex in the subnetwork induced by this subset is at least n − k. The maximum edge-weight k-plex partitioning problem (Max-EkPP) is to find the k-plex partitioning in edge-weighted network, such that the sum of edge weights is maximal. The Max-EkPP has an important role in discovering new information in large sparse biological networks. We propose a variable neighborhood search (VNS) algorithm for solving Max-EkPP. The VNS implements a local search based on the 1-swap first improvement strategy and the objective function that takes into account the degree of every vertex in each partition. The objective function favors feasible solutions, also enabling a gradual increase in terms of objective function value when moving from slightly infeasible to barely feasible solutions.A comprehensive experimental computation is performed on real metabolic networks and other benchmark instances from literature. Comparing to the integer linear programming method from literature, our approach succeeds to find all known optimal solutions. For all other instances, the VNS either reaches previous best known solution or improves it. The proposed VNS is also tested on a large-scaled dataset which was not previously considered in literature.
Zinc oxide is a highly applicable semiconductor material. Wide applica-tion of this nanomaterial is connected to wide spectrum of energy band gap, high bond en-ergy, great thermal conductivity, but also with its non-toxicity, antibacterial activity, bio-compatibility and biodegradability characteristics. The aim of this paper is synthesis and characterization of silver doped ZnO nanoparticles (ZnO:Ag NP) using sol-gel method. Ob-tained samples of silver doped ZnO nanoparticles were characterized by following tech-niques: Fourier-transform infrared spectroscopy (FTIR), UV/VIS spectrophotometry, X-ray diffraction (XRD), scanning electron microscopy (SEM) and energy-dispersive X-ray spec-troscopy (EDX). Efficiency of provided synthesis method was examined by FTIR spectros-copy. XRD determined the purity and crystallinity, and wurtzite structure of synthesized material. Surface morphology and the effect of doping were examined using SEM and EDX characterization methods. Results showed better conductivity after doping ZnO nanoparti-cles with silver. SEM micrographs showed ZnO:Ag NP in the form of nanorods with a par-ticle average size of 6 nm.
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