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Nanocrystal Materials for Resistive Memory and Artificial Synapses: Progress and Prospects
Yingchun Chen1, Dunkui Chen1, Chi Zhang1
1National Intellectual Property Information Service Center of HUST, Huazhong University of Science and Technology Library, Wuhan 430074, P.R. China.
Recent Patents on Nanotechnology
|April 18, 2023
Summary
Doping resistive random-access memory (RRAM) with nanocrystals (NCs) improves device performance by stabilizing switching voltages and enhancing retention. This advancement is key for next-generation memory and neuromorphic applications.
Area of Science:
- Materials Science
- Electrical Engineering
- Nanotechnology
Background:
- Resistive random-access memory (RRAM) shows promise for next-generation non-volatile memory due to its low cost and energy efficiency.
- Current RRAM technology faces challenges with random on/off switching voltages, hindering its widespread adoption.
- Nanocrystals (NCs) offer a solution, providing excellent electronic/optical properties and enabling low-cost, large-area fabrication for improved RRAM.
Purpose of the Study:
- To conduct a comprehensive survey of nanocrystal (NC) materials for enhancing resistive memory (RM) and optoelectronic synaptic devices.
- To review recent experimental advancements in NC-based neuromorphic devices, including artificial synapses and light-sensory platforms.
Main Methods:
- Collected and analyzed extensive information on NCs for RRAM and artificial synapses, including patent data.
- Focused on highlighting the unique electrical and optical characteristics of metal and semiconductor NCs.
- Reviewed experimental advances in NC-based neuromorphic devices.
Main Results:
- Doping RRAM with NCs in the functional layer improves the homogeneity of SET/RESET voltages and reduces the threshold voltage.
- NC doping enhances retention time in RRAM devices.
- NC-based RRAM demonstrates potential for mimicking biological synapse functions.
Conclusions:
- Nanocrystal doping significantly enhances the performance of resistive memory devices.
- Further research is needed to address existing challenges and fully realize the potential of NCs in RM and artificial synapses.
- NCs are highly relevant for the future development of resistive memory and neuromorphic computing platforms.

