Wafer-scale solution-processed 2D material analog resistive memory array for memory-based computing

Baoshan Tang, Hasita Veluri, Yida Li, Zhi Gen Yu, Moaz Waqar, Jin Feng Leong, Maheswari Sivan, Evgeny Zamburg, Yong-Wei Zhang, John Wang and Aaron V-Y. Thean ()
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Baoshan Tang: National University of Singapore
Hasita Veluri: National University of Singapore
Yida Li: National University of Singapore
Zhi Gen Yu: Institute of High Performance Computing
Moaz Waqar: National University of Singapore
Jin Feng Leong: National University of Singapore
Maheswari Sivan: National University of Singapore
Evgeny Zamburg: National University of Singapore
Yong-Wei Zhang: Institute of High Performance Computing
John Wang: National University of Singapore
Aaron V-Y. Thean: National University of Singapore

Nature Communications, 2022, vol. 13, issue 1, 1-9

Abstract: Abstract Realization of high-density and reliable resistive random access memories based on two-dimensional semiconductors is crucial toward their development in next-generation information storage and neuromorphic computing. Here, wafer-scale integration of solution-processed two-dimensional MoS2 memristor arrays are reported. The MoS2 memristors achieve excellent endurance, long memory retention, low device variations, and high analog on/off ratio with linear conductance update characteristics. The two-dimensional nanosheets appear to enable a unique way to modulate switching characteristics through the inter-flake sulfur vacancies diffusion, which can be controlled by the flake size distribution. Furthermore, the MNIST handwritten digits recognition shows that the MoS2 memristors can operate with a high accuracy of >98.02%, which demonstrates its feasibility for future analog memory applications. Finally, a monolithic three-dimensional memory cube has been demonstrated by stacking the two-dimensional MoS2 layers, paving the way for the implementation of two memristor into high-density neuromorphic computing system.

Date: 2022
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DOI: 10.1038/s41467-022-30519-w

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