Developing multifunctional and diversified artificial neural systems to integrate multimodal plasticity, memory, and supervised learning functions is an important task toward the emulation of neuromorphic computation. Here, we present a bioinspired mechano-photonic artificial synapse with synergistic mechanical and optical plasticity. The artificial synapse is composed of an optoelectronic transistor based on graphene/MoS₂ heterostructure and an integrated triboelectric nanogenerator. By controlling the charge transfer/exchange in the heterostructure with triboelectric potential, the optoelectronic synaptic behaviors can be readily modulated, including postsynaptic photocurrents, persistent photoconductivity, and photosensitivity. The photonic synaptic plasticity is elaborately investigated under the synergistic effect of mechanical displacement and the light pulses embodying different spatiotemporal information. Furthermore, artificial neural networks are simulated to demonstrate the improved image recognition accuracy up to 92% assisted with mechanical plasticization. The mechano-photonic artificial synapse is highly promising for implementing mixed-modal interaction, emulating complex biological nervous system, and promoting the development of interactive artificial intelligence.

In the era of 5G and the Internet of things (IoTs), various human–computer interaction systems based on the integration of triboelectric nanogenerators (TENGs) and IoTs technologies demonstrate the feasibility of sustainable and self-powered functional systems. The rapid development of intelligent applications of IoTs based on TENGs mainly relies on supplying the harvested mechanical energy from surroundings and implementing active sensing, which have greatly changed the way of human production and daily life. This review mainly introduced the TENG applications in multidiscipline scenarios of IoTs, including smart agriculture, smart industry, smart city, emergency monitoring, and machine learning-assisted artificial intelligence applications. The challenges and future research directions of TENG toward IoTs have also been proposed. The extensive developments and applications of TENG will push forward the IoTs into an energy autonomy fashion.