An innovative cost-effective and lead-free polymer nanocomposite of polyvinyl alcohol/ polyvinyl pyrrolidone was developed. PVA/PVP nanocomposite film contained spherical AgCl and SnO₂ nanoparticles was facilely prepared via a one-pot synthesis method. The synthesis route affords uniform dispersion of the both nanoparticles and unique features of polymer nanocomposite of insoluble, dense, and nonporous properties. The new nanocomposite achieved an efficient gamma radiation attenuation capability. The attenuation capacity for gamma photons was investigated in terms of linear and mass attenuation coefficients (µ) and (µ_m), respectively, at low and high energies (using ⁶⁰Co and ¹³⁷Cs sources). Other parameters such as half value layer (HVL), tenth value layer (TVL), and mean free path (MFP) were used to evaluate the shielding capacity. Theoretical calculation (XCOM program) results were consistent with the obtained experimental results. The results revealed that the essential thickness of the polymer nanocomposite to reduce the γ-ray intensity to 50% is 6.6, 8.9, and 9.8 cm for 662, 1173, and 1332 keV γ-ray energies, respectively. The physio-chemical properties of the polymer nanocomposite were evaluated using spectroscopic, microscopic, and thermal analysis tools. Additionally, the formation of spherical nanoparticles was elucidated using TEM. FTIR and leachability were used to confirm the stability, good durability, and chemical resistivity of the synthesized polymer nanocomposite. The nano-filler AgCl and SnO₂ formation mechanism was discussed in detail. Graphical abstract

Electromagnetic measurements are widely used to gain information about an object through interaction of electromagnetic fields with the physical properties of this object. The inversion problem is the process of estimating object parameters from electromagnetic records. This problem has a nonlinear nature and can be formulated as an optimization scheme. In this paper, we introduce an inversion methodology to estimate the electrical properties of a two-dimensional inhomogeneous layered scattering object. The proposed methodology deals with the inversion problem as a learning process through two multilayer perceptron artificial neural network designs. Several neural network design parameters were tuned to achieve the best inversion performance. Moreover, the proposed neural networks were tested against noise presence in terms of error criteria and proved to be effective in solving the inverse scattering problem.

Electromagnetic (EM) methods have been extensively used in geophysical investigations such as mineral and hydrocarbon exploration as well as in geological mapping and structural studies. In this paper, we developed an inversion methodology for Electromagnetic data to determine physical parameters of a set of horizontal layers. We conducted Forward model using transmission line method. In the inversion part, we solved multi parameter optimization problem where, the parameters are conductivity, dielectric constant, and permeability of each layer. The optimization problem was solved by simulated annealing approach. The inversion methodology was tested using a set of models representing common geological formations.

Inverse problems are of importance in many fields of science and engineering. Electromagnetic inversion deals with estimating information contained in electromagnetic measurements. The inversion scheme needs to be designed properly to compensate for Gibbs oscillations effects in the solution, and hence give better validation for the estimated quantities. In this paper an inversion methodology based on simulated annealing is presented that has the ability to extract information about electrical conductivity and dielectric permittivity of a vertically stratified medium using the scattered electric field. Furthermore, Gibbs phenomenon and its oscillation effect on the inversion solution have been studied, and an efficient approach has been developed to render more accurate estimations. Results of implementing the proposed approach and its resolution compared with the original methodology are presented.

The electromagnetic inverse scattering approach seeks to obtain the electric characteristics of a scatterer using information about the source and the scattered data. The inverse scattering problem usually suffers from limited knowledge about the scatterer used, which makes its solution more challenging than the forward problem. This paper presents an inversion approach to estimating the unknown electric properties of a two- and three-dimensional inhomogeneous scatterer. The presented approach considers the inverse scattering problem as a global minimization problem with a meshless forward formulation for the computation of the scattered electromagnetic field. Various simulated annealing cooling schedules are applied and assessed to solve the problem, and the results of several case studies are presented for both two- and three-dimensional electromagnetic inverse scattering problems.