This thesis investigates porous silicon (pSi) as a CMOS-compatible nanoporous ion-exchange membrane for nanofluidic reverse electrodialysis (nRED), with the long-term objective of enabling miniaturized salinity-gradient energy harvesters for autonomous microsystems and low-power IoT platforms. While conventional reverse electrodialysis relies on dense polymer ion-exchange membranes optimized for large-scale stacks, nanofluidic approaches exploit surface-charge-governed ion transport in nanoscale pores and offer a possible route toward microfabricated energy conversion devices. However, despite promising results at the single-pore level, the translation of such concepts into integrable membrane technologies remains limited, and porous silicon had not previously been investigated as an active membrane material for nRED. To address this gap, the thesis combines theoretical analysis, numerical modeling, membrane fabrication, and experimental benchmarking. A physics-based model of ionic transport in charged nanopores under salinity gradients was first developed to determine how pore radius, porosity, and surface charge density affect permselectivity, ionic resistance, and output power. The simulations revealed a fundamental trade-off between selectivity and conductance and identified a fabrication window in which pores below about 20 nm are expected to be favorable at the membrane scale. Based on these insights, porous silicon membranes were fabricated and tested in a custom reverse electrodialysis platform. Two fabrication routes were explored. A self-supported approach proved unsuitable because the final DRIE step altered pore opening and induced unstable, rectifying electrical behavior. A second route based on electropolishing lift-off enabled the fabrication of free-standing membranes with preserved porous structure and stable I–V characteristics suitable for RED characterization. Their experimental response followed the qualitative trends predicted by the numerical model, confirming that ionic transport is governed by surface-charge-dominated nanofluidic effects. Most importantly, this work demonstrates for the first time that porous silicon can function as an ion-selective membrane for nanofluidic reverse electrodialysis. Under the tested conditions, the best free-standing membrane achieved a maximum power density of about 1.33 mW/m2. To further improve performance, hybrid membranes combining a thin selective active layer with a thicker support layer werefabricated, and an adaptive surface-charge regulation model was introduced to better capture the coupling between surface chemistry and ion transport. Although these developments improved physical understanding and highlighted viable optimization routes, they also showed that substantial limitations remain, especially regarding surface-charge modeling, membrane resistance, and practical upscaling. Overall, the thesis establishes porous silicon as a new platform for selective ion transport in nRED and provides the first integrated framework linking pore design, fabrication, electrochemical benchmarking, and numerical interpretation. Beyond salinity-gradient energy harvesting, the results open perspectives for porous silicon in iontronic, sensing, and lab-on-chip applications where CMOS compatibility and nanoscale control are decisive advantages.