Synapses based on lead-free perovskite in artificial intelligence

Perovskites have been broadly considered as the most suitable materials for the fabrication of artificial synapses because of easily formed conductive filaments via ion migration, which are of great potential for the construction of a neuromorphic computing system with an extraordinary capacity for parallel massive information processing at an ultralow energy consumption. Based on the synaptic transmission behavior in biological system, three distinct factors are suggested for the realization of fundamental synaptic functions: the paired-pulse facilitation (PPF) index, duration of long-term plasticity (LTP), and realization of spike-timing-dependent plasticity (STDP). To enhance these parameters, we discuss the mechanisms of these factors based on the formation of vacancies, regulation of band gap, and inhibition of hole-electron recombination and suggest that element replacement and structural modification can significantly improve the parameters. Owing to the well-balanced performance and biocompatibility, the lead-free perovskite synapses are believed as a savior for the artificial intelligence techniques engaging in neuromorphic computing.