TY - EJOU AU - Yang, Kefan AU - Yang, Keqi AU - Zeng, Yixuan AU - Zhang, Yi AU - Zeng, Shengqing AU - Zhang, Dapeng TI - AI-Driven Optimization and Microfluidic Investigation of Triboelectric Nanogenerators for Sustainable Ocean Energy T2 - Energy Engineering PY - VL - IS - SN - 1546-0118 AB - This review systematically summarizes the progress of TENGs for marine energy, and distinguishes itself from existing TENG–ocean reviews by deeply elucidating the closed-loop synergistic mechanism of artificial intelligence and microfluidics. We quantitatively validate that AI-driven material screening increases charge density by 3–5 times, microfluidic regulation reduces biofouling-induced output attenuation to 25% of traditional structures, and the collaborative system improves energy conversion efficiency by over 23%. Unlike standalone reviews on TENGs, marine energy, AI materials, or microfluidics, this work is the first to integrate the three into a unified intelligent optimization framework, revealing bottlenecks including device power density (<1 W/m2), large-scale integration phase mismatch, and biodegradable material stability imbalance. We further propose the closed-loop intelligent control and large-scale engineering paths of AI-microfluidics-TENG. This study fills the gap in interdisciplinary collaborative optimization for ocean energy harvesting devices and provides a theoretical and technical reference for the intelligent, efficient, and sustainable utilization of marine blue energy. KW - Triboelectric nanogenerator; artificial intelligence; microfluidics; marine energy; sustainable energy; energy conversion DO - 10.32604/ee.2026.083511