2021
DOI: 10.1039/d1mh00315a
|View full text |Cite
|
Sign up to set email alerts
|

2D oriented covalent organic frameworks for alcohol-sensory synapses

Abstract: Resistive random access memories (RRAMs) based on electrochemical metallization mechanism (ECM) have potential applications in high-density data storage and efficient neuromorphic computing. However, the high variability of ECM device still...

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
54
0

Year Published

2021
2021
2024
2024

Publication Types

Select...
8

Relationship

1
7

Authors

Journals

citations
Cited by 37 publications
(58 citation statements)
references
References 33 publications
0
54
0
Order By: Relevance
“…From this figure, one can clearly see that the conductance distributions between the 16 states are non‐overlapping, suggesting the outstanding reliability of multi‐level performance. As one the most important deep neural networks, convolutional neural networks (CNNs) can be employed to perform such tasks as image recognition, object detection, image segmentation and others [27–31] . For this reason, we utilized the 16‐non‐overlapping states as the weight parameters that can be modulated to build a simple memristor‐based CNN for image recognition and achieved an image recognition accuracy of 80 % after 8 epochs of training.…”
Section: Figurementioning
confidence: 99%
“…From this figure, one can clearly see that the conductance distributions between the 16 states are non‐overlapping, suggesting the outstanding reliability of multi‐level performance. As one the most important deep neural networks, convolutional neural networks (CNNs) can be employed to perform such tasks as image recognition, object detection, image segmentation and others [27–31] . For this reason, we utilized the 16‐non‐overlapping states as the weight parameters that can be modulated to build a simple memristor‐based CNN for image recognition and achieved an image recognition accuracy of 80 % after 8 epochs of training.…”
Section: Figurementioning
confidence: 99%
“…Lately, Li et al 78 demonstrated in 2021 a 2D COF-based synaptic system fabricated with a sandwiched oriented 2D COF-5 between ITO and Ag electrodes (Ag/COF-5/ITO) (Figure 12a). The aligned 2D COF-5 opened its 1D porous channels out-of-plane between the two electrodes of ITO and Ag, which efficiently transferred Ag + cations and alcohol vapors rapidly.…”
Section: Reticular Materials Thin-film-based Resistive Switching Devicesmentioning
confidence: 99%
“…Thus, the research has been enthusiastically exploited to develop novel emulated human recognition systems with oxides, , phase change materials, , polymers, and perovskites from a decade ago. Recently, Li et al first reported successful mimicking the human nervous system of alcohol inhibition stimulation with 2D COFs in 2021; yet, that is only one published research article related to reticular materials-based memristors exhibiting synaptic plasticity. Thus, we will introduce the analog-type memristive system based on the reticular materials, but reticular materials-based RRAMs for high-density electrical information storage will be mostly focused on in this review.…”
Section: Basic Concepts Of Memristors and Resistive Switching Mechani...mentioning
confidence: 99%
See 1 more Smart Citation
“…This has opened new horizons for the exploration and innovation of new 2D materials. Covalent organic frameworks (COF) are novel smart materials with well-dened and adjustable porosity, 1 large surface area, intrinsic crystalline framework, high thermal stabilities, 2 conductive 3 /semiconductive properties, and ease of modifying the chemical structure, which has attracted intense attention in various applications ranging from gas adsorption/ separation, 4,5 energy storage, 6,7 advanced sensing, [8][9][10][11][12][13] semiconductive device, [14][15][16][17][18] biological applications, [19][20][21][22] photocatalysis 23,24 etc. These materials have p-electronic blocks covalently bonded and arranged in periodic planar networks stacked in layered 2 or 3-dimensional (2D or 3D) network structures with atomic precision.…”
Section: Introductionmentioning
confidence: 99%