Toward Energy-Autonomous Neuromorphic Systems: Piezoelectric and Triboelectric Nanogenerators for Synaptic Plasticity Emulation

The pursuit of neuromorphic systems capable of replicating the efficiency and adaptability of the brain has driven significant advances in artificial synapse technologies. Conventional computing, constrained by the von Neumann bottleneck and high energy consumption, struggles to emulate synaptic plasticity and parallel information processing. To address these limitations, researchers have turned to bioinspired approaches that integrate emerging nanotechnologies with electronic devices. This chapter first reviews the fundamental mechanisms of biological synapses, including neurotransmission, excitatory postsynaptic currents (EPSCs), and plasticity phenomena such as paired-pulse facilitation (PPF), short-term plasticity (STP), long-term potentiation (LTP), and spike-timing-dependent plasticity (STDP). It then explores hardware strategies for emulating synaptic behavior, with a particular emphasis on piezotronic and tribotronic devices. In piezotronics, strain-induced piezopotentials at semiconductor junctions modulate charge transport, whereas tribotronics harness contact-electrification potentials from triboelectric nanogenerators (TENGs) to provide self-powered gating signals. The integration of these mechanisms with advanced transistors—such as electrolyte-gated, floating-gate, and optoelectronic architecture—has enabled the realization of artificial synapses that exhibit rich neuromorphic functionalities, including short- and long-term memory, mechanoplasticity, multimodal plasticity, and associative learning. By unifying biological principles with tribotronic and piezotronic synapses provide a promising route toward the next generation of self-powered neuromorphic computing.