Silicon nitride has greatly improved the versatility of integrated photonics technologies due to its wide transparency window, compatibility with existing CMOS-foundry infrastruc ture, and its potential for extremely low propagation loss. However, its low refractive index reduces mode confinement, increasing the minimum device footprint of components such as the widely-adopted ring resonator filter, resulting in a height ened need for reduced-bending architecture to maintain high integration density.

This study investigates the current-voltage (I-V) characteristics of semiconductor nanowires (NWs) through a detailed experimental analysis and model fitting. The I-V data, collected from two different NW samples, were imported into Mathematica for curve fitting, revealing key electronic properties. The data were fitted to an exponential model, providing insights into the transport behavior of these nanostructures. The findings demonstrate the potential of semiconductor NWs for applications in electronic devices, with implications for their performance in real-world applications.

Abstract—This manuscript introduces the Chaos Fusion Mutation INFO algorithm (CFMINFO), which integrates multiple strategies and updates vector positions through three core processes. These processes incorporate Good Point Set initialization, Sine-Tent-Cosine (STC) chaotic parameterization, and Normal Cloud Mutation strategies. The algorithm is characterized by its simplicity, rapid convergence, and ability to avoid local optima. To validate its performance, CFMINFO is applied to the optimization of linear arrays.

Transformers, especially dry-type transformers, which nowadays are going to be employed instead of oil-type transformers, are one of the major equipment in the generation, transmission and distribution network of electric energy. The transformer insulation strength may reduce due to partial discharge (PD) occurrence, and this can finally result in its insulation failure.