Due to their biocompatibility and non-toxicity, biopolymer-based films hold significant importance in bioengineering. It is imperative to comprehend the influence of chitosan molecular weight and filler materials nature on the crystalline structure and their subsequent effect on film properties. The aim of this research was to determine how carbon nanotubes embedded within chitosan can significantly improve the performance of biopolymer-based films produced by the solvent-casting technique. Four probe measurements demonstrated that films of medium-molecular-weight chitosan/carbon nanotubes displayed an electrical conductivity value of 0.0132 S cm⁻¹, resulting in films with a low sheet resistance value of 0.0156 mΩ/Υ. Based on XRD findings, it has been demonstrated that films containing carbon nanotubes have shifted the (002) plane of chitosan towards higher angles, favoring chitosan crystal form II, which could be responsible for the enhanced mechanical performance. Structural characteristics, such as lattice strain (e), grain size (D), and dislocation density, have been calculated using the Williamson–Hall method, in which the medium-molecular-weight chitosan/CNTs film samples displayed the best crystalline quality. SEM images revealed nanotube diameters ranging in size from 140 to 300 nm, suggesting that the chitosan was effectively wrapped along carbon nanotubes. Our results indicate that developing chitosan-wrapped carbon nanotube films introduces them as potential materials for bioengineering and biomedical research.

Chitosan is a biopolymer with unique properties that have attracted considerable attention in various scientific fields in recent decades. Although chitosan is known for its poor electrical and mechanical properties, there is interest in producing chitosan-based materials reinforced with carbon-based materials to impart exceptional properties such as high electrical conductivity and high Young’s modulus. This study describes the synergistic effect of carbon-based materials, such as reduced graphene oxide and carbon nanotubes, in improving the electrical, optical, and mechanical properties of chitosan-based films. Our findings demonstrate that the incorporation of reduced graphene oxide influences the crystallinity of chitosan, which considerably impacts the mechanical properties of the films. However, the incorporation of a reduced graphene oxide–carbon nanotube complex not only significantly improves the mechanical properties but also significantly improves the optical and electrical properties, as was demonstrated from the photoluminescence studies and resistivity measurements employing the four-probe technique. This is a promising prospect for the synthesis of new materials, such as biopolymer films, with potential applications in optical, electrical, and biomedical bioengineering applications.

In the present work, a neuronal dynamic response prediction system is shown to estimate the response of multiple systems remotely without sensors. For this, a set of Neural Networks and the response to the step of a stable system is used. Six basic characteristics of the dynamic response were extracted and used to calculate a Transfer Function equivalent to the dynamic model. A database with 1,500,000 data points was created to train the network system with the basic characteristics of the dynamic response and the Transfer Function that causes it. The contribution of this work lies in the use of Neural Network systems to estimate the behavior of any stable system, which has multiple advantages compared to typical linear regression techniques since, although the training process is offline, the estimation can perform in real time. The results show an average 2% MSE error for the set of networks. In addition, the system was tested with physical systems to observe the performance with practical examples, achieving a precise estimation of the output with an error of less than 1% for simulated systems and high performance in real signals with the typical noise associated due to the acquisition system.

The rapid growth of battery energy storage systems, renewable energy integration, electric vehicles, and DC microgrids has significantly increased the demand for compact, efficient, and bidirectional isolated DC–DC converters. Conventional Dual Active Bridge (DAB) converters commonly employ high-frequency transformers to provide galvanic isolation and bidirectional power transfer. Although transformer-based DAB converters offer excellent performance, their magnetic components increase converter volume, weight, core losses, leakage inductance, manufacturing complexity, and overall cost. Consequently, recent research has explored alternative high-frequency energy transfer techniques based on capacitive coupling, aiming to reduce magnetic components while preserving efficient resonant power conversion.This paper proposes a Capacitively Coupled Dual Active Bridge (CC-DAB) converter employing high-power metallized polypropylene (MKPH) capacitors as the high-frequency energy transfer medium. The proposed converter operates at a relatively low switching frequency while investigating the safe operating conditions of the capacitive coupling network to ensure reliable and efficient power transfer. A microcontroller-based single-phase-shift (SPS) modulation strategy is implemented to generate the gate-driving signals of the full bridges, whereas the switching frequency is selected to achieve zero-voltage switching (ZVS) throughout the investigated operating range. The phase-shift angle ($\varphi$) regulates the transferred power by controlling the voltage difference between the primary and secondary bridges across the capacitive coupling network. The proposed converter is analyzed theoretically and validated through simulation and experimental testing. Experimental results demonstrate stable bidirectional power transfer, soft-switching operation, and a peak conversion efficiency of 91.3% at a relatively low switching frequency of 52 kHz. The experimental verification confirms the practical feasibility of capacitive coupling for resonant bidirectional power conversion and demonstrates its potential as an alternative architecture for low- and medium-power applications requiring compact size, high efficiency, reduced magnetic component requirements, and reversible energy transfer. Furthermore, the proposed topology contributes to the ongoing development of transformerless resonant converters by experimentally validating a high-frequency capacitive coupling network capable of supporting efficient bidirectional power flow under practical operating conditions.