Engineering Ferroelectric‐/Ion‐Modulated Conductance in 2D vdW CuInP 2 S 6 for Non‐Volatile Digital Memory and Artificial Synapse

Two‐dimensional (2D) ferroionics is appealing in performing complex artificial intelligence tasks due to the interesting property of coexistence of ferroelectricity and ionic activities. CuInP 2 S 6 (CIPS), as a typical 2D ferroionic material, is highly conducive to rich functions of information dev...

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Bibliographic Details
Published inAdvanced functional materials Vol. 34; no. 25
Main Authors Ci, Wenjuan, Wang, Peng, Xue, Wuhong, Yuan, Hongtao, Xu, Xiaohong
Format Journal Article
LanguageEnglish
Published 01.06.2024
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Summary:Two‐dimensional (2D) ferroionics is appealing in performing complex artificial intelligence tasks due to the interesting property of coexistence of ferroelectricity and ionic activities. CuInP 2 S 6 (CIPS), as a typical 2D ferroionic material, is highly conducive to rich functions of information devices due to the displacement of Cu + inducing both ferroelectricity and ionic conductivity. However, the coupling and modulation of polarization and ion migration in CIPS for multifunctional information devices has not been fully explored. Here, this study demonstrates that digital memory and synaptic simulations are realized in Au/CIPS/Au device via engineering ferroelectric polarization reversal and the long‐distance migration of the Cu + to change conductive modes. Steep resistive switching behavior based on ion‐migration is observed with a high on/off ratio of over 10 8 , long retention time (>2 × 10 4  s), and current compliance engineered multilevel resistance states, demonstrating reliable nonvolatile high‐density memory characteristics. Based on the continuous modulation of polar order, the key synaptic behaviors are successfully simulated. Moreover, by the co‐modulation of polarization state and ions migration, the paired‐pulse facilitation, paired‐pulse depression, and potentiation following depression are achieved. These results suggest that CIPS is a promising candidate for constructing high‐performance, function‐enriched devices for data storage, information processing, and neuromorphic computing.
ISSN:1616-301X
1616-3028
DOI:10.1002/adfm.202316360