An Effective Supramolecular Mg(II)-Metallohydrogel based Non-Volatile Memory Device with Supreme Endurance
Traditional computer systems are becoming unable to handle the needs of upcoming data-intensive applications. Resistive random access memory devices (RRAM), which offers a potential advancement in existing computing design, are preferred as promising alternatives for the application in neuromorphic computing. In this work supramolecular Mg(II)-based metallohydrogel, referred as Mg@5AP was synthesized by 5amino 1pentanol as Low Molecular Weight Gelator (LMWG) at normal temp. From scanning and transmission electron microscopy (FESEM and TEM), we observed a unique network of rectangular, pebble-like structures within Mg@5AP. From Fourier-transform infrared (FT-IR) spectroscopy, we identified organic compounds which were present in this metallohydrogel. Here, we prepared schottky diode with the configurations of metal-semiconductor-metal using Mg@5AP. To investigate its charge transportation property, we developed Mg@5AP based Resistive Random-Access Memory Device (RRAM) with lateral and vertical configurations which exhibited a bipolar resistive switching behavior. Behind this switching mechanism, formation and rapture of conduction filament between were responsible. It demonstrated impressive endurance with a high ON/OFF ratio (⁓120) upto 5000 switching cycles. Here, 2×2 crossbar array based on Mg@5AP was also prepared to demonstrate logic gate operation. In this work, it was confirmed that it worked as in-memory computing where storage and processing both were occurred simultaneously. Therefore, it provided a cost-effective and environmentally friendly alternative to conventional heavy metal-based memory systems for high-performance data storage.
Authors
- Soumya Jyoti Ray (ORCID: https://orcid.org/0000-0002-4640-708X)
- Arpita Roy
Institutions
- Indian Institute of Technology Patna (IN)
Publication Details
- Journal
- Journal of Condensed Matter
- Published
- 2025-05-04
- DOI
- https://doi.org/10.61343/jcm.v3i02.104
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00