Label-Free Field Effect Transistors (FETs) for Fabrication of Point-of-Care (POC) Biomedical Detection Probes.

Field effect transistors (FETs)-based detection probes are powerful platforms for quantification in biological media due to their sensitivity, ease of miniaturization, and ability to function in biological media. Especially, FET-based platforms have been utilized as promising probes for label-free detections with the potential for use in real-time monitoring. The integration of new materials in the FET-based probe enhances the analytical performance of the developed probes by increasing the active surface area, rejecting interfering agents, and providing the possibility for surface modification. Furthermore, the use of new materials eliminates the need for traditional labeling techniques, providing rapid and cost-effective detection of biological analytes. This review discusses the application of materials in the development of FET-based label-free systems for point-of-care (POC) analysis of different biomedical analytes from 2018 to 2024. The mechanism of action of the reported probes is discussed, as well as their pros and cons were also investigated. Also, the possible challenges and potential for the fabrication of commercial devices or methods for use in clinics were discussed.

Multiobjective optimization and performance assessment of a PEM fuel cell-based energy system for multiple products.

In this article, the optimal design of a novel multi-generation system for the production of electricity, cooling, heat and freshwater is discussed. In this system, a Proton exchange membrane fuel cell (PEM FC) is used to generate electricity, and the heat produced by it is absorbed by the Ejector Refrigeration Cycle (ERC) and used to provide cooling and heating capacity. A reverse osmosis (RO) desalination system is also used to supply freshwater. The esign variables in this research are operating temperature and pressure and current density of FC, as well as the operating pressure of the HRVG, evaporator, and condenser of the ERC system. In order to optimize the considered system, the exergy efficiency and total cost rate (TCR) of the system are considered as optimization objective functions. To this end, the genetic algorithm (GA) is used and the Pareto front is extracted. Also, three refrigerants R134a, R600 and R123 areused as ERC system refrigerant and their performance are evaluated. Finally, the optimal design point is selected. At the mentioned point, the exergy efficiency is 70.2% and the TCR of the system is 1.78 S/h.