Innovations in nanomaterial science, engineering and printing technologies have increasingly driven advances in electrochemical sensing. Screen-printed electrodes (SPEs) have become a versatile, low-cost, and scalable solution for developing portable electrochemical detection platforms. However, their analytical performance remains intrinsically limited by surface area, electron transfer efficiency, and the immobilization of biomolecules. Recent developments in nanostructured materials, ranging from two-dimensional (2D) materials such as graphene, MXenes, and transition metal dichalcogenides, to one-dimensional nanostructures and hybrid nanocomposites, have transformed the signal transduction landscape of SPE-based electrochemical sensors. Integration of nanomaterials into SPEs has successfully transformed their analytical capabilities, but the diversity of materials and modification strategies has made it difficult to consolidate current knowledge in the field. Strategies that integrate nanomaterials via ink formulation, surface modification, or in situ growth have yielded sensors with unprecedented sensitivity, reproducibility, and selectivity across various chemical and biological targets. This review offers a cross-material synthesis of how nanomaterial engineering transforms the electrochemical performance of SPEs. By integrating insights across morphology, interfacial chemistry, and device-level behavior, it establishes a unified perspective that has been missing from the current literature and clarifies the design principles driving next-generation SPE-based sensing platforms.

Innovative practices in irrigation systems can bring improvements in terms of economic efficiency and, at the same time, can reduce environmental impacts. Investment in high-tech technologies frequently involves additional costs, but an efficient water management system can increase the lifetime of the equipment. The most utilized electronic device for a smart management, used to pump units from irrigation systems, is the frequency converter. This device can regulate the speed of the motors that control the pumps according to the consumption of water, ensuring that it does not pump more water than is needed. This paper develops a new operating algorithm that ensures the operation of the pumping group at safe operating intervals and identifies the equivalent pump operating points for the entire flow range and pumping height of the pumping group in order to bring smart management to irrigation systems. The parameters monitored and collected for each vertical pump refers to the voltage, current, frequency (speeds) and flow of each hydraulic operating mode. The methodology used is based on the principle of creating an expert system to optimize energy consumption in the pumping groups. The proposed methodology was tested on an irrigation system that includes a pumping group with five pumps, showing its effectiveness in obtaining the optimal solution with a relatively low computational burden and without the violation of any system constraints under any operating conditions.

Developing bidirectional EV charging systems requires a structured engineering methodology that preserves traceability from system requirements to executable simulation models. This paper proposes a Model-Based Systems Engineering (MBSE)-oriented framework for the development and validation of grid-connected energy systems integrating vehicle-to-grid (V2G) and grid-to-vehicle (G2V) capabilities. The proposed approach is structured into a problem space and a solution space. The problem space defines system requirements and functional behavior using SysML requirement and use case diagrams developed in Eclipse Papyrus. The solution space transforms these functions into logical activity diagrams, physical architectures in MATLAB R2024b System Composer, and executable simulation models in MATLAB R2024b/Simulink. The framework is validated through a bidirectional EV charging case study connected to a low-voltage electrical grid. The simulation results confirm stable G2V and V2G operation and demonstrate the traceability between requirements, architecture, and executable simulation models. The proposed workflow supports consistency, interoperability, and early validation for EV-integrated energy systems.