Literature DB >> 30420759

Memristor crossbar arrays with 6-nm half-pitch and 2-nm critical dimension.

Shuang Pi1, Can Li1, Hao Jiang1, Weiwei Xia2, Huolin Xin2, J Joshua Yang1, Qiangfei Xia3.   

Abstract

The memristor1,2 is a promising building block for next-generation non-volatile memory3, artificial neural networks4-7 and bio-inspired computing systems8,9. Organizing small memristors into high-density crossbar arrays is critical to meet the ever-growing demands in high-capacity and low-energy consumption, but this is challenging because of difficulties in making highly ordered conductive nanoelectrodes. Carbon nanotubes, graphene nanoribbons and dopant nanowires have potential as electrodes for discrete nanodevices10-14, but unfortunately these are difficult to pack into ordered arrays. Transfer printing, on the other hand, is effective in generating dense electrode arrays15 but has yet to prove suitable for making fully random accessible crossbars. All the aforementioned electrodes have dramatically increased resistance at the nanoscale16-18, imposing a significant barrier to their adoption in operational circuits. Here we demonstrate memristor crossbar arrays with a 2-nm feature size and a single-layer density up to 4.5 terabits per square inch, comparable to the information density achieved using three-dimensional stacking in state-of-the-art 64-layer and multilevel 3D-NAND flash memory19. Memristors in the arrays switch with tens of nanoamperes electric current with nonlinear behaviour. The densely packed crossbar arrays of individually accessible, extremely small functional memristors provide a power-efficient solution for information storage and processing.

Entities:  

Year:  2018        PMID: 30420759     DOI: 10.1038/s41565-018-0302-0

Source DB:  PubMed          Journal:  Nat Nanotechnol        ISSN: 1748-3387            Impact factor:   39.213


  21 in total

1.  Hardware-Mappable Cellular Neural Networks for Distributed Wavefront Detection in Next-Generation Cardiac Implants.

Authors:  Zhuolin Yang; Lei Zhang; Kedar Aras; Igor R Efimov; Gina C Adam
Journal:  Adv Intell Syst       Date:  2022-05-12

2.  Charge Configuration Memory Devices: Energy Efficiency and Switching Speed.

Authors:  Anze Mraz; Rok Venturini; Damjan Svetin; Vitomir Sever; Ian Aleksander Mihailovic; Igor Vaskivskyi; Bojan Ambrozic; Goran Dražić; Maria D'Antuono; Daniela Stornaiuolo; Francesco Tafuri; Dimitrios Kazazis; Jan Ravnik; Yasin Ekinci; Dragan Mihailovic
Journal:  Nano Lett       Date:  2022-06-10       Impact factor: 12.262

3.  Challenges hindering memristive neuromorphic hardware from going mainstream.

Authors:  Gina C Adam; Ali Khiat; Themis Prodromakis
Journal:  Nat Commun       Date:  2018-12-10       Impact factor: 14.919

4.  Resistive Switching Memory Devices Based on Body Fluid of Bombyx mori L.

Authors:  Lu Wang; Dianzhong Wen
Journal:  Micromachines (Basel)       Date:  2019-08-16       Impact factor: 2.891

5.  Effect of Ag Concentration Dispersed in HfOx Thin Films on Threshold Switching.

Authors:  Won Hee Jeong; Jeong Hwan Han; Byung Joon Choi
Journal:  Nanoscale Res Lett       Date:  2020-01-30       Impact factor: 4.703

6.  Monitoring PSA levels as chemical state-variables in metal-oxide memristors.

Authors:  Ioulia Tzouvadaki; Spyros Stathopoulos; Tom Abbey; Loukas Michalas; Themis Prodromakis
Journal:  Sci Rep       Date:  2020-09-17       Impact factor: 4.379

7.  Understanding memristive switching via in situ characterization and device modeling.

Authors:  Wen Sun; Bin Gao; Miaofang Chi; Qiangfei Xia; J Joshua Yang; He Qian; Huaqiang Wu
Journal:  Nat Commun       Date:  2019-08-01       Impact factor: 14.919

8.  Neurohybrid Memristive CMOS-Integrated Systems for Biosensors and Neuroprosthetics.

Authors:  Alexey Mikhaylov; Alexey Pimashkin; Yana Pigareva; Svetlana Gerasimova; Evgeny Gryaznov; Sergey Shchanikov; Anton Zuev; Max Talanov; Igor Lavrov; Vyacheslav Demin; Victor Erokhin; Sergey Lobov; Irina Mukhina; Victor Kazantsev; Huaqiang Wu; Bernardo Spagnolo
Journal:  Front Neurosci       Date:  2020-04-28       Impact factor: 4.677

9.  A caloritronics-based Mott neuristor.

Authors:  Javier Del Valle; Pavel Salev; Yoav Kalcheim; Ivan K Schuller
Journal:  Sci Rep       Date:  2020-03-09       Impact factor: 4.379

10.  Effects of top electrode material in hafnium-oxide-based memristive systems on highly-doped Si.

Authors:  Sueda Saylan; Haila M Aldosari; Khaled Humood; Maguy Abi Jaoude; Florent Ravaux; Baker Mohammad
Journal:  Sci Rep       Date:  2020-11-11       Impact factor: 4.379

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