HfO x -Based Conductive Bridge Random Access Memory with Al2O3 Sandglass Nanostructures via Glancing Angle Deposition Technology toward Neuromorphic Applications
ACS APPLIED NANO MATERIALS(2023)
Abstract
Conductive bridge random access memory (CBRAM) is oneof the promising nonvolatile memories for next-generation technologyowing to its high density, low power consumption, and fast switchingspeed, which is also a potential candidate for implementation of neuromorphiccomputing. However, CBRAMs suffer from stochastically growing conductingfilaments in the insulator layer. Herein, we demonstrated Al2O3 sandglass nanostructures (SNGSs) embedded into HfO (x) -based CBRAMs via glancing angle depositiontechnology with the AlN thermal enhanced layer to prevent the overinjectionof cations and localize the growth of conducting filaments in theHfO (x) switching layer. With the assistanceof Al2O3 SNGSs and the AlN layer, the Cu/Al2O3 SNGSs/HfO (x) /AlN/TiNdevice exhibited a stable on/off ratio of >10 for more than 6000cycles. Furthermore, with a Te top electrode, the Te/Al2O3 SNGSs/HfO (x) /AlN/TiN deviceshows a multilevel cell characteristic by controlling compliance currents.In addition, it possesses excellent potentiation and depression nonlinearitiesof 1.28 and 0.4, respectively, which is beneficial for future applicationsin neuromorphic computing.
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Key words
conductive bridge random access memory,sandglass nanostructures,neuromorphic computing system,glancing angle deposition,synaptic plasticity,thermal enhanced layer
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