A study on the high power microwave effects of PIN diode limiter based on deep learning algorithm.

PIN diodes, due to their simple structure and variable resistance characteristics under high-frequency high-power excitation, are often used in radar front-end as limiters to filter high power microwaves (HPM) to prevent its power from entering the internal circuit and causing damage. This paper carries out theoretical derivation and research on the HPM effects of PIN diodes, and then uses an optimized neural network algorithm to replace traditional physical modeling to calculate and predict two types of HPM limiting indicators of PIN diode limiters. We proposes a neural network model for each of the following two prediction scenarios: in the scenario of time-junction temperature curves under different HPM irradiation, the weighted mean squared error (MSE) between the predicted values from the test dataset and the simulated values is below 0.

Anti-Corrosion Mechanism of Parsley Extract and Synergistic Iodide as Novel Corrosion Inhibitors for Carbon Steel-Q235 in Acidic Medium by Electrochemical, XPS and DFT Methods.

The parsley extract (PLE) was prepared using absolute ethyl alcohol. The PLE and synergistic iodide were firstly utilized as efficacious corrosion inhibitors to slow down the corrosion rate of carbon steel-Q235 in 0.5 mol/L HSO solution.