Nanostructured Ni2As2O7 semiconductor samples were synthesized by a solid state method among As2O3 and Ni(NO3)2.6H2O raw materials at 650oC (S1) and 750oC (S2) as reaction temperatures. The synthesized nanomaterials were characterized by powder X-ray Diffraction (PXRD) technique and Fourier-Transform Infrared (FTIR) spectroscopy. The Rietveld analysis showed that the obtained materials were Crystallized well in the triclinic Crystal structure with the space group P1. The data of Rietveld analysis showed that the purity of the synthesized nanomaterials was increased by increasing the reaction temperature. The morphologies of the synthesized materials were studied by field emission scanning electron microscope (FESEM). It was found that the morphology of the obtained materials was changed from homogeneous sponge to particles and somewhat porous structure, by increasing the reaction temperature. Besides, the average particle sizes were increased considerably by increasing the reaction temperature. Ultraviolet-visible spectra analysis showed that the synthesized Ni2As2O7 nanomaterials had strong light absorption in the ultraviolet light region. The direct optical band gap energies were 3.20, 3.90, 4.80 eV and 2.9, 3.40, 4.70 eV for S1 and S2, respectively. The data showed that the band gaps were decreased by increasing the reaction temperature that can be due to the increasing the Crystallite sizes of the targets.

Optimization is an act of decision-making to reach a point in which the overall behavior of the considered system is acceptable by the field's experts. In recent decades, construction companies have been willing to provide housing services with lower construction costs that people of different kinds can afford. Although academics have introduced form-dominant methods, using artificial intelligence (AI) in structural design has been one of the most critical challenges in recent years. In the current study, the applicability of the Crystal structure Algorithm (Crystal) as one of the recently developed metaheuristic algorithms is investigated in the optimum design of truss structures, in which the basic concepts of Crystals, including the lattice and basis, are in perspective. For numerical purposes, the 10-bar, 72-bar, and 200-bar truss structures are considered as design examples. Furthermore, for constraint-handling purposes, a simple penalty approach is implemented in Crystal. A complete statistical analysis is conducted through multiple optimization runs for comparative purposes; at the same time, other metaheuristic approaches have been derived from the literature. Based on the results of the Crystal and other methods in dealing with truss optimization problems, the utilized method can provide better and more competitive results in most cases.