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Short-Term Memory Dynamics of TiN/Ti/TiO2/SiO/Si Resistive Random Access Memory
1Division of Electronics and Electrical Engineering, Dongguk University, Seoul 04620, Korea.
Nanomaterials (Basel, Switzerland)
|September 16, 2020
Summary
This study demonstrates a novel synaptic device mimicking biological neurons for neuromorphic computing. The complementary metal-oxide-semiconductor (CMOS)-compatible resistive random access memory shows potential for efficient, brain-inspired data processing.
Area of Science:
- Materials Science
- Neuroscience
- Computer Engineering
Background:
- Neuromorphic computing offers an alternative to von Neumann architecture for efficient data processing.
- Short-term memory is crucial in neural networks for information filtering and temporary spike retention.
- Biological synapses exhibit plasticity, a key feature for learning and memory.
Purpose of the Study:
- To investigate the synaptic functions of TiN/Ti/TiO2/SiO/Si resistive random access memory (RRAM).
- To develop a complementary metal-oxide-semiconductor (CMOS)-compatible synaptic device for neuromorphic computing.
- To demonstrate short-term memory dynamics and spike-timing-dependent plasticity (STDP) in the RRAM device.
Main Methods:
- Fabrication of a TiN/Ti/TiO2/SiO/Si RRAM device.
- Characterization of synaptic potentiation and depression using varying pulse conditions.
- Demonstration of short-term memory through pulse modulation and paired-pulse facilitation.
- Investigation of STDP by analyzing synaptic weight changes based on pre- and postsynaptic timing.
Main Results:
- The RRAM device successfully mimicked synaptic potentiation and depression.
- Short-term memory dynamics were observed with specific pulse voltages (-3.5 V) and widths (10 ms).
- The SiO layer provided nonlinear current-voltage characteristics, enabling high-density synapse arrays.
- STDP was successfully implemented, showing synaptic weight modulation based on neural timing.
Conclusions:
- The developed CMOS-compatible synaptic device shows promise for neuromorphic computing applications.
- The RRAM device effectively emulates biological synaptic functions, including short-term memory and plasticity.
- The findings confirm the viability of implementing this RRAM technology in future neuromorphic chips.
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