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Nanomaterials
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Semiconductor Nanomaterials for Memory Devices
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Special Issue "Semiconductor Nanomaterials for Memory Devices"

A special issue of Nanomaterials (ISSN 2079-4991). This special issue belongs to the section "Nanoelectronics, Nanosensors and Devices".

Deadline for manuscript submissions: 31 December 2023 | Viewed by 2251

Special Issue Editors

Prof. Dr. Xianbin Li

E-Mail Website
Guest Editor
State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, 2699 Qianjin Street, Changchun 130012, China
Interests: materials physics of phase-change memory; ultrafast optical storage; mechanism of memristor/atomristor; high-through calculation screening of memory materials; defect physics of semiconductors
Prof. Dr. Wei Zhang

E-Mail Website
Guest Editor
Center for Alloy Innovation and Design (CAID), State Key Laboratory for Mechanical Behavior of Materials, Xi'an Jiaotong University, Xi'an 710049, China
Interests: phase-change materials for memory and brain-like computing devices; TEM analysis; glass/amorphous structures; machine-learning potential simulations; optical properties of chalcogenide glass
Prof. Dr. Ming Xu

E-Mail Website
Guest Editor
1. School of Integrated Circuits, Huazhong University of Science and Technology, Wuhan 430074, China
2. Hubei Yangtze Memory Laboratories, Wuhan 430205, China
Interests: phase-change memory materials and devices; RRAM materials and devices; OTS materials and devices; machine-learning for amorphous structures; mechanisms of ionic transport; metallic glass

Special Issue Information

Dear Colleagues,

Memory Technology is a key component of the modern information society. Its value will be further enhanced in the future big-data era. As a kind of matter carrier for recording data or information, semiconductor nanomaterials increasingly play important roles in memory devices due to their potential advantage of device miniature and high-density integration. The electrical/optical/spin/magnetic/chemical/ferroelectric properties, band structure, atomic structure, defect, and various phases of semiconductor nanomaterials together decide the ways of efficient data encoding, which includes volatile and nonvolatile memories. Their microscopic working mechanism, response to external stimuli, characterization/analysis, growth, optimization/design, and device fabrication of the semiconductor nanomaterials are closely related to memory performances including data retention, power consumption, signal contrast, encoding speed, write/erase cycling and so on. Moreover, some fast-developing memory-related technologies, for example, brain-like or neuromorphic computing devices, also depend on semiconductor nanomaterials.  

Original research articles and reviews are both welcome. Research areas may include (but not limited to) the following:  

  • Nanomaterials, Devices, and Technologies for Phase-Change Memory 
  • Nanomaterials, Devices, and Technologies for Resistive Random-Access Memory 
  • Nanomaterials, Devices, and Technologies for Magnetic/Spin Memory 
  • Nanomaterials, Devices, and Technologies for Ferroelectric Memory 
  • Nanomaterials, Devices, and Technologies for Flash Memory 
  • Nanomaterials, Devices, and Technologies for DRAM/SRAM  
  • Nanomaterials for Neuromorphic Computing/In-Memory Computing Devices 
  • Nanomaterials for Optical Storage/Optical Computation 
  • Nanomaterials for Selector Devices 
  • Two-Dimensional Materials for Memory Devices 
  • Nanotube Materials for Memory Devices 
  • Other Semiconductor Nanomaterials for Memory and Related Devices 
  • Simulation and Theoretical Analysis

The Special Issue “Semiconductor Nanomaterials for Memory Devices” aims at providing an overview of the most recent progress and new developments in the design and utilization of semiconductor nanomaterials for advanced memory devices as well as their related technologies. Here, we are pleased to invite you to contribute works related to this Special Issue. Thank You. 

Prof. Dr. Xianbin Li
Prof. Dr. Wei Zhang
Prof. Dr. Ming Xu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Nanomaterials is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • memory
  • data storage
  • volatile/nonvolatile
  • 2D materials
  • nanomaterials
  • semiconductor
  • PCM
  • RRAM
  • FeRAM
  • MRAM
  • DRAM
  • SRAM
  • flash memory
  • neuromorphic computing
  • selector

Published Papers (2 papers)

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Research

15 pages, 2256 KiB  
Article
Semiempirical Two-Dimensional Model of the Bipolar Resistive Switching Process in Si-NCs/SiO2 Multilayers
by
Juan Ramirez-Rios
,
Karla Esther González-Flores
,
José Juan Avilés-Bravo
,
Sergio Alfonso Pérez-García
,
Javier Flores-Méndez
,
Mario Moreno-Moreno
and
Alfredo Morales-Sánchez
Nanomaterials 2023, 13(14), 2124; https://doi.org/10.3390/nano13142124 - 21 Jul 2023
Viewed by 438
Abstract
In this work, the SET and RESET processes of bipolar resistive switching memories with silicon nanocrystals (Si-NCs) embedded in an oxide matrix is simulated by a stochastic model. This model is based on the estimation of two-dimensional oxygen vacancy configurations and their relationship [...] Read more.
In this work, the SET and RESET processes of bipolar resistive switching memories with silicon nanocrystals (Si-NCs) embedded in an oxide matrix is simulated by a stochastic model. This model is based on the estimation of two-dimensional oxygen vacancy configurations and their relationship with the resistive state. The simulation data are compared with the experimental current-voltage data of Si-NCs/SiO2 multilayer-based memristor devices. Devices with 1 and 3 Si-NCs/SiO2 bilayers were analyzed. The Si-NCs are assumed as agglomerates of fixed oxygen vacancies, which promote the formation of conductive filaments (CFs) through the multilayer according to the simulations. In fact, an intermediate resistive state was observed in the forming process (experimental and simulated) of the 3-BL device, which is explained by the preferential generation of oxygen vacancies in the sites that form the complete CFs, through Si-NCs. Full article
(This article belongs to the Special Issue Semiconductor Nanomaterials for Memory Devices)
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13 pages, 20953 KiB  
Article
Investigation of Program Efficiency Overshoot in 3D Vertical Channel NAND Flash with Randomly Distributed Traps
by
Chanyang Park
,
Jun-Sik Yoon
,
Kihoon Nam
,
Hyundong Jang
,
Minsang Park
and
Rock-Hyun Baek
Nanomaterials 2023, 13(9), 1451; https://doi.org/10.3390/nano13091451 - 24 Apr 2023
Viewed by 1252
Abstract
The incremental step pulse programming slope (ISPP) with random variation was investigated by measuring numerous three−dimensional (3D) NAND flash memory cells with a vertical nanowire channel. We stored multiple bits in a cell with the ISPP scheme and read each cell pulse by [...] Read more.
The incremental step pulse programming slope (ISPP) with random variation was investigated by measuring numerous three−dimensional (3D) NAND flash memory cells with a vertical nanowire channel. We stored multiple bits in a cell with the ISPP scheme and read each cell pulse by pulse. The excessive tunneling from the channel to the storage layer determines the program efficiency overshoot. Then, a broadening of the threshold voltage distribution was observed due to the abnormal program cells. To analyze the randomly varying abnormal program behavior itself, we distinguished between the read variation and over−programming in measurements. Using a 3D Monte−Carlo simulation, which is a probabilistic approach to solve randomness, we clarified the physical origins of over−programming that strongly influence the abnormal program cells in program step voltage, and randomly distributed the trap site in the nitride of a nanoscale 3D NAND string. These causes have concurrent effects, but we divided and analyzed them quantitatively. Our results reveal the origins of the variation and the overshoot in the ISPP, widening the threshold voltage distribution with traps randomly located at the nanoscale. The findings can enhance understanding of random over−programming and help mitigate the most problematic programming obstacles for multiple−bit techniques. Full article
(This article belongs to the Special Issue Semiconductor Nanomaterials for Memory Devices)
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