Advanced Memory Technology for Emerging Storage and Computing Applications
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Microelectronics".
Deadline for manuscript submissions: 15 May 2026 | Viewed by 90
Special Issue Editors
Interests: memory; RRAM; microelectronics; neuromorphic computing; nanotechnology
Special Issue Information
Dear Colleagues,
As AI computing, edge intelligence, and data-centric architectures surge forward, memory technologies must meet unprecedented demands in performance and adaptability. The limitations of traditional von Neumann architectures—with their rigid separation of memory and processing—have become increasingly apparent. The bottleneck in data movement and energy consumption demands a paradigm shift toward low-power, high-performance memory solutions that can support real-time inference, massive parallelism, and in-memory computing. This Special Issue seeks cutting-edge contributions that address these challenges through innovations in emerging memory devices and materials. This Special Issue is aimed at addressing the challenges of speed, scalability, reliability, and integration in modern memory-enhanced computing systems.
Topics of interest include the following:
- Resistive RAM (RRAM): Material engineering, variation mitigation, power management, and 3D integration.
- Ferroelectric RAM (FeRAM): CMOS-compatible ferroelectrics, endurance, and low-power logic-in-memory.
- Magnetoresistive RAM (MRAM): Spin-transfer torque, voltage-controlled switching, and embedded applications.
- Phase-Change Memory (PCM): Thermal stability, multi-level cell design, and system-level optimization.
- Selectorless Memory and Selector Device: Self-rectifying behaviors, sneak-path current mitigation and array integration.
- Gain Cell Embedded DRAM (GC-eDRAM): Compact cell design, logic integration, and leakage reduction.
- Dynamic RAM (DRAM) and Static RAM (SRAM): Refresh strategies, scaling limits, and hybrid memory systems.
- Device and Material Renovation: Novel compounds, heterostructures, and fabrication techniques for enhanced performance.
- Reliability and Variation Solutions: Endurance modeling, fault tolerance, and adaptive error correction.
We welcome original research, comparative studies, and system-level co-design efforts that push the boundaries of memory-centric computing. Annotated timelines, historical framing, and bilingual resources are encouraged to support broader accessibility and educational impact.
Dr. Ying Chen Daphne Chen
Dr. Morteza Fayazi
Guest Editors
Manuscript Submission Information
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Keywords
- RRAM
- FeRAM
- MRAM
- PCM
- gain cell
- DRAM
- SRAM
- selector
- selectorless memory
- neuromorphic computing
- 2D materials
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