Triboelectric Tactile Transducers for Neuromorphic Sensing and Synaptic Emulation: Materials, Architectures, and Interfaces

Triboelectric nanogenerators (TENGs) have a vital role in sustainable energy sources for future technologies such as wearable applications, implantable electronics, artificial intelligence (AI), machine learning (ML), medical technologies, sensors, and waste management systems. The main focus of this review article is to identify the energy output and stability of the TENG and neuromorphic devices in order to identify ongoing challenges such as power, device compatibility, scaling, and cost efficiency. The integration of TENG with ML leads to opportunities to process data for signal processing and sensor applications in order to learn complex structures in device functioning through the utilization of different databases. In addition, this review mainly summarizes the ML and TENG integration, another major research focus is on neuromorphic applications for the understanding of materials and their nature toward their application, such as memory devices, synaptical behavior artificial synaptic devices, electrolyte‐gated transistors, gated transistors, and artificial neural networks for AI and Internet of Things devices. The TENG is mainly focused on self‐powered devices with more energy output and reliability for the given application.