Multi-spectral gate-triggered heterogeneous photonic neuro-transistors for power-efficient brain-inspired neuromorphic computing

Abstract

For the realization of low-power consumption brain-inspired neuromorphic computing devices which mimic the biological neuronal information processing methodology, the development of photonic transistors capable of synaptic behaviors and neuronal computation have attracted lots of interests. Here, metal-chalcogenide (MC)/metal-oxide (MO) heterogeneous photonic neuro-transistors capable of multi-spectrum triggered synaptic responses and corresponding neuronal computation were developed for an intelligent and energy efficient neuromorphic device. The photonic transistor architecture including a solution-processed broadband photo-active heterogeneous channel and electronic modulatory terminal enable to establish power-saved multi-level writing/reading processing. The multi-spectral gate-triggerings and their synaptic responses were emulated via the broadband absorbing MC/MO heterogeneous semiconducting structure and its defective hetero-interface, which can be fine-tuned by varying photo-spectrum of applied spikes and controlling of interfacial traps in-between, respectively. More importantly, the multi-spectrum triggered heterogeneous photonic neuro-transistors can facilitate wider dynamic and more intelligent neuronal computation such as multi-level dendritic summation and fire behaviors, logic-computation, and associated learning beyond conventional simple synaptic-level photonic devices. The results reported here argue that the multi-spectral activated heterogeneous photonic neuro-transistor outperforms current state-of-neuro-devices, provide a facile and generic route to achieve high-density and energy efficient neuromorphic system.