An artificial synapse based on Sr(Ti, Co)O3 films

With the explosive growth of the demand for computing power and storage on chips, researchers have proposed an artificial synapse with biological synapse-like functions to achieve low-energy, high-efficiency parallel neu-romorphic computation and perform various complex functions efficiently, in response to the shortcomings of "storage and computation separation" in traditional computing systems. In this paper, we fabricated an artificial synapse based on SrTi0.99Co0.01O3 calcium titanite. It implements a variety of important synaptic learning and memory functions, including long-term and short-term plasticity, paired-pulse depression, spike-time-dependent plasticity. It has promising applications in the construction of artificial neural networks for processing massive data. Further studies show that the resistance switching ratio of SrTi0.99Co0.01O3 is improved by an order of magnitude compared to SrTiO3, and the stability is greatly enhanced, which may be attributed to the increase in the content of oxygen vacancies in the material (from 20.3 % to 23.9 %), which is also more favorable to the synaptic performance. Therefore, Co has an important impact on the enhancement of SrTiO3 properties. This study is a good reference for future full implementation of brain-inspired computing systems.