Litcius/Paper detail

Tunable Synaptic Characteristics of a Ti/TiO<sub>2</sub>/Si Memory Device for Reservoir Computing

Jinwoong Yang, Hyojong Cho, Hojeong Ryu, Muhammad Ismail, Chandreswar Mahata, Sungjun Kim

2021ACS Applied Materials & Interfaces77 citationsDOI

Abstract

In this study, we fabricate and characterize a Ti/TiO2/Si device with different dopant concentrations on a silicon surface for neuromorphic systems. We verify the device stack using transmission electron microscopy (TEM). The Ti/TiO2/p++Si device exhibits interface-type bipolar resistive switching with long-term memory. The potentiation and depression by the pulses of various amplitudes are demonstrated using gradual resistive switching. Moreover, pattern-recognition accuracy (>85%) is obtained in the neuromorphic system simulation when conductance is used as the weight in the network. Next, we investigate the short-term memory characteristics of the Ti/TiO2/p+Si device. The dynamic range is well-controlled by the pulse amplitude, and the conductance decay depends on the interval between the pulses. Finally, we build a reservoir computing system using the short-term effect of the Ti/TiO2/p+Si device, in which 4 bits (16 states) are differentiated by various pulse streams through the device that can be used for pattern recognition.

Topics & Concepts

Neuromorphic engineeringMaterials scienceOptoelectronicsConductanceStack (abstract data type)AmplitudeReservoir computingSiliconMemristorNon-volatile memoryComputer scienceElectronic engineeringArtificial neural networkOpticsArtificial intelligenceRecurrent neural networkEngineeringMathematicsCombinatoricsPhysicsProgramming languageAdvanced Memory and Neural ComputingNeural Networks and Reservoir ComputingNeural dynamics and brain function
Tunable Synaptic Characteristics of a Ti/TiO<sub>2</sub>/Si Memory Device for Reservoir Computing | Litcius