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In this work, computationally efficient design optimization of frequency selective surface (FSS)-loaded ultra-wideband Vivaldi antenna via the use of data-driven surrogate model is studied. The proposed design methodology consists of a multi-layer FSS structure aimed for performance improvement of the Vivaldi design, which makes the design a multi-objective multi-dimensional optimization problem. For having a fast and accurate optimization process, a data-driven surrogate model alongside the metaheuristic optimizer honeybee mating optimization (HBMO) had been used. The optimally designed antenna had been prototyped and its performance characteristics had been measured. The obtained experimental results are compared with the simulated results of the proposed method. Results show that the obtained FSS-loaded structure has enhanced directivity compared with the design without FSS structure, without any performance losses in the return loss characteristics. The FSS-loaded Vivaldi antenna operates at 2–12 GHz band with a maximum gain of 10 dBi at 10 GHz which makes the design a good solution for RADAR applications.

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The Pippard relations (CP vs. P and P vs. T) are examined at various temperatures up to 1200 K at zero pressure (P = 0) for the cubic gauche nitrogen. The specific heat (CP) is related to the thermal expansion (P) and the P is also related to the isothermal compressibility (T) as the Pippard relations for this solid structure. For those relations, experimental data are used from the literature. It is found that the variation of the CP with the P and P with the T is linear. Using the linear relations dP/dT is predicted, which can be compared with the experimental measurements in the P-T phase diagram of cubic gauche nitrogen.

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A steady-state fluorescence technique was employed to study the swelling of j-carrageenan gels at various temperatures. Pyranine was used as a fluorescence probe. The fluorescence intensity of pyranine was measured during the in situ swelling process of j-carrageenan gels. The fluorescence intensity increased exponentially as the swelling time increased. The increase in the fluorescence intensity was modeled with the Li-Tanaka equation, from which the swelling time constants and cooperative diffusion coefficients were determined. The swelling time constants decreased and the cooperative diffusion coefficients increased as the swelling temperature was increased. The swelling activation energies were measured to be 47.05 kJ/mol.

In this work, design optimization process of a multi-band antenna via the use of artificial neural network (ANN) based surrogate model and meta-heuristic optimizers are studied. For this mean, first, by using Latin-Hyper cube sampling method, a data set based on 3D full wave electromagnetic (EM) simulator is generated to train an ANN-based model. By using the ANN-based surrogate model and a meta-heuristic optimizer invasive weed optimization (IWO), design optimization of a multi-band antenna for (1) 2.4–3.6 GHz for ISM, LTE, and 5G sub-frequencies, and (2) 9–10 GHz for X-band applications is aimed. The obtained results are compared with the measured and simulated results of 3D EM simulation tool. Results show that the proposed methodology provides a computationally efficient design optimization process for design optimization of multi-band antennas.