Trends in hydrogen-, lithium- and oxygen-based electrochemical RAM: materials, mechanisms, and applications
ECRAM devices, including Li-, H-, and O-based types, enable low-power, analog memory for neuromorphic computing. This work reviews materials, architectures, performance, and challenges, guiding future development for scalable, reliable AI hardware.
Authors
- Maria Mukhtar (ORCID: https://orcid.org/0009-0002-5607-5629)
- Usman Ali (ORCID: https://orcid.org/0000-0002-2039-1630)
- Sang Yeol Lee (ORCID: https://orcid.org/0000-0002-4405-9042)
- Muhammad Junaid Sultan
Institutions
- University of Rome Tor Vergata (IT)
- Gachon University (KR)
Publication Details
- Journal
- Journal of Materials Chemistry C
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d5tc02043c
- Citations
- 2
- Primary Topic
- Fuel Cells and Related Materials
- Type
- article
- Field-Weighted Citation Impact
- 1.46