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The exponential growth of data in our society following the fourth industrial revolution has exposed the limitations of existing technologies. The current computing architecture struggles to process efficiently the immense volume of data generated every second. A potential breakthrough to overcome these limitations involves the adoption of neuromorphic computing to emulate the functionalities of a biological brain. In this context, a synaptic diode composed of a Pt/TiOx/Ti stack is proposed to replicate the operations of synapses and neurons. Various synapse function emulations, including potentiation, depression, and spike-rate-dependent plasticity, are examined to completely realize an artificial synapse. Additionally, precise control over pulse sequences is implemented for cost-effective and high-density reservoir computing, exploring configurations with 2, 4, and 7 bits. Thus, showcasing the synaptic diode capable of diverse functions with computing adaptability, enabling favorites in future applications of neuromorphic computing.
Ju et al. (2024) studied this question.