Advances in Emerging Nonvolatile Memory, 3rd Edition

A special issue of Micromachines (ISSN 2072-666X). This special issue belongs to the section "D1: Semiconductor Devices".

Deadline for manuscript submissions: 29 February 2024 | Viewed by 657

Special Issue Editor

Special Issue Information

Dear Colleagues,

As the scaling of electronic semiconductor devices displays signs of saturation, it is worth looking into emerging, beyond-CMOS technologies. Very promising emerging technologies currently in high industry demand are emerging nonvolatile memory devices, including resistive random-access memory (RRAM), phase-change memory (PCM), magneto-resistive random-access memory (MRAM), ferroelectric random-access memory (FeRAM), etc. Compared with flash memory, emerging nonvolatile memory has many merits, such as fast switching speed, low power, high endurance, and a simple device structure. Over the past decade, emerging nonvolatile memory devices have achieved great advances in physical mechanisms, modelling, materials, integration, architecture, and applications. In the context of potential applications, these include memory, neuromorphic computing, nonvolatile logic operations, and stochastic computing. At present, it is possible to buy several commercial standalone memory products based on emerging nonvolatile memory in the semiconductor market. Meanwhile, merging nonvolatile memory can store and process information using the same devices, which has made in-memory computing a hot topic recently. This Special Issue demonstrates the state of the art and exemplifies the recent advances in the field of emerging nonvolatile memory devices for storage and computing and brings together scholars from different scientific disciplines (physics, materials science, electrical engineering, computer science, etc.) representing all aspects of emerging nonvolatile memory devices, from fundamentals to applications.

We look forward to receiving your submissions.

Dr. Yao-Feng Chang
Guest Editor

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Keywords

  • emerging nonvolatile memory devices: RRAM, PCM, MRAM, FeRAM
  • physical mechanism of nonvolatile switching
  • nonvolatile switching materials
  • integration of emerging nonvolatile memory devices
  • new memory architecture for nonvolatile switching devices
  • in-memory computing based on nonvolatile memory
  • deep neural networks
  • neuromorphic computing
  • nonvolatile logic operation
  • PUF
  • stochastic computing

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Published Papers (1 paper)

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11 pages, 3661 KiB  
Article
TCAD Simulation Studies on Ultra-Low-Power Non-Volatile Memory
Micromachines 2023, 14(12), 2207; https://doi.org/10.3390/mi14122207 - 06 Dec 2023
Viewed by 513
Abstract
Ultra-Low-Power Non-Volatile Memory (UltraRAM), as a promising storage device, has attracted wide research attention from the scientific community. Non-volatile data retention in combination with switching at ≤2.6 V is achieved through the use of the extraordinary 2.1 eV conduction band offsets of InAs/AlSb [...] Read more.
Ultra-Low-Power Non-Volatile Memory (UltraRAM), as a promising storage device, has attracted wide research attention from the scientific community. Non-volatile data retention in combination with switching at ≤2.6 V is achieved through the use of the extraordinary 2.1 eV conduction band offsets of InAs/AlSb and a triple-barrier resonant tunnelling structure. Along these lines, in this work, the structure, storage mechanism, and improvement strategies of UltraRAM were systematically investigated to enhance storage window clarity and speed performance. First, the basic structure and working principle of UltraRAM were introduced, and its comparative advantages over traditional memory devices were highlighted. Furthermore, through the validation of the band structure and storage mechanism, the superior performance of UltraRAM, including its low operating voltage and excellent non-volatility, was further demonstrated. To address the issue of the small storage window, an improvement strategy was proposed by reducing the thickness of the channel layer to increase the storage window. The feasibility of this strategy was validated by performing a series of simulation-based experiments. From our analysis, a significant 80% increase in the storage window after thinning the channel layer was demonstrated, providing an important foundation for enhancing the performance of UltraRAM. Additionally, the data storage capability of this strategy was examined under the application of short pulse widths, and a data storage operation with a 10 ns pulse width was successfully achieved. In conclusion, valuable insights into the application of UltraRAM in the field of non-volatile storage were provided. Our work paves the way for further optimizing the memory performance and expanding the functionalities of UltraRAM. Full article
(This article belongs to the Special Issue Advances in Emerging Nonvolatile Memory, 3rd Edition)
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