Changing the memory behaviors from volatile to nonvolatile via end-capping of hyperbranched polyimides with polycyclic arenes

Song, Ying; Yao, Hongyan; Tan, Haiwei; Zhu, Shiyang; Dong, Bo; Guan, Shaokang

doi:10.1016/j.dyepig.2017.01.008

Cited by 19 publications

(8 citation statements)

References 41 publications

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“…There are also many other reports in the literature, documenting the polyimides based volatile and nonvolatile memory behaviors. [179][180][181][182][183][184] Reproduced with permission. [169] Copyright 2014, Royal Society of Chemistry.…”

Section: Nonconjugated Resistive Switching Polymersmentioning

confidence: 99%

Organic Memory and Memristors: From Mechanisms, Materials to Devices

Yuan

Liu

Chen

et al. 2021

Adv Elect Materials

116

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silicon-based semiconductor devices are encountering constraints of downscaling with significant data fidelity issues and unaffordable manufacturing cost at the impending 2-3 nm nodes, hindering their direct application for both flexible and very (ultra) large-scale integration (VLSI). [4] One way to solve this problem is by developing in-memory computing technologies. By using new materials and different mechanisms to design and implement memory cells, the "von Neumann bottleneck" can be solved, and the semiconductor industry can maintain an exciting development trend.When dealing with 21st-century applications such as real-time voice recognition, image processing, and big-data analysis, as the huge amount of involved information is usually accessed unpredictably, it may take many processor cycles to fetch the target data from the memory hierarchy and the computer may stall due to the unavailability of the data, resulting in loss of computation performance and power efficiency. Compared with the human brain, modern supercomputers have faster operation speed but much lower efficiency. The human brain transmits signals with neurons. The neural network consists of 10 11 neurons and is connected with 10 15 synapses. The synapse is the nanogap between neurons, which permits electrical or chemical signal transmission. [5,6] Benefited from the neural network structure, the human brain can deal with recognition tasks effectively. When processing massively parallel information, each synapse event consumes about 1-100 fJ. [7] The human brain has strong stability because the neural network does not collapse with the death of nerve cells. Moreover, when humans interact with new things, the neural network will automatically learn and update without the need for human readjustment. [8] In order to execute artificial intelligence algorithms with energy efficiency performance and performance comparable to that of the brain, it is hoped to simulate the function of neural networks (for example, the interconnection of biological synapses and neurons) through the inherent combination of information storage and processing on the device scale. [9] Fortunately, memristor, another resistive switching device beyond the bistable memories, may be important in computer systems before the von Neumann architecture.Memristor was conceived by Chua based on the theory of the symmetry arguments in 1971 and experimentally demonstrated by Strukov et al. [10,11] Memsietor can be defined as a two-terminal device with nonvolatile resistance which can be modulated by light, electricity, heat, and so on. [12] Unlike devices that display a Facing the exponential growth of data digital communications and the advent of artificial intelligence, there is an urgent need for information technologies with huge storage capacity and efficient computing processing. However, the traditional von Neumann architecture and silicon-based storage and computing technology will reach their limits and cannot meet the storage requirements of ultrasmall size, ultrahigh densi...

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Section: Nonconjugated Resistive Switching Polymersmentioning

confidence: 99%

Organic Memory and Memristors: From Mechanisms, Materials to Devices

Yuan

Liu

Chen

et al. 2021

Adv Elect Materials

116

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“…9). The HOMO and LUMO energy levels of the HL ligand and the Cu(II) complex can be estimated from the onset oxidation potential (E onset ) and E ferrocene as follows: [38][39][40] HOMO The results are listed in Table 2. The HOMO and LUMO energy levels and the energy gap of the Cu(II) complex are lower than those of the HL ligand, and this indicates that the corresponding electron transition from HOMO to LUMO for the Cu(II) complex is easier than that for the HL ligand.…”

Section: Electrochemical Characteristicsmentioning

confidence: 99%

The synthesis of a Cu(ii) Schiff base complex using a bidentate N₂O₂ donor ligand: crystal structure, photophysical properties, and antibacterial activities

Guo

Zhang

et al. 2019

RSC Adv.

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“…Our group has carried out some work focusing on hyperbranched polyimides (HBPIs) memory materials [19–24] . HBPIs usually exhibit good solubility, processability and rich structural flexibility on account of their three‐dimensional dendritic structure [25–27] .…”

Section: Introductionmentioning

confidence: 99%

Novel Hyperbranched Polyimides Bearing Bis(trifluoromethyl)‐triphenylamine Moiety: Preparation and Rewritable Nonvolatile Memory Behaviours

et al. 2021

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Two novel hyperbranched polyimides (HBPIs) bearing bis(trifluoromethyl)‐triphenylamine moiety were prepared by condensation polymerization of a triamine monomer, N,N‐bis[4‐amino‐2‐(trifluoromethyl)phenyl]‐1,4‐benzenediamine (ATPB), with oxydiphthalic dianhydride (ODPA) and hexafluoroisopropyl phthalic anhydride (6FDA). The trifluoromethyl group was introduced into HBPIs to improve the property of the memory device. The resulting hyperbranched polyimides exhibited high molecular weights (weight‐average molecular weights large to 7.51×104 with a polydispersity of 1.63), outstanding organic‐solubility and excellent thermal stability (5 % thermal weight‐loss temperature up to 518 °C). Memory devices based on these hyperbranched polyimides showed similar rewritable nonvolatile memory characteristics but with different threshold voltages. The switching voltage was found to have a dependence on the energy barrier between polymer active layer and electrodes. These devices displayed favorable stability in both OFF and ON states with retention time long to 104 s and ON/OFF current ratio as high as 106. The space charge‐limited conduction model and local filaments formation were responsible for the switching behaviors of these memory devices. The results indicate that these hyperbranched polyimides are promising candidates for polymer memory application.

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Changing the memory behaviors from volatile to nonvolatile via end-capping of hyperbranched polyimides with polycyclic arenes

Cited by 19 publications

References 41 publications

Organic Memory and Memristors: From Mechanisms, Materials to Devices

Organic Memory and Memristors: From Mechanisms, Materials to Devices

The synthesis of a Cu(ii) Schiff base complex using a bidentate N₂O₂ donor ligand: crystal structure, photophysical properties, and antibacterial activities

Novel Hyperbranched Polyimides Bearing Bis(trifluoromethyl)‐triphenylamine Moiety: Preparation and Rewritable Nonvolatile Memory Behaviours

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Changing the memory behaviors from volatile to nonvolatile via end-capping of hyperbranched polyimides with polycyclic arenes

Cited by 19 publications

References 41 publications

Organic Memory and Memristors: From Mechanisms, Materials to Devices

Organic Memory and Memristors: From Mechanisms, Materials to Devices

The synthesis of a Cu(ii) Schiff base complex using a bidentate N2O2 donor ligand: crystal structure, photophysical properties, and antibacterial activities

Novel Hyperbranched Polyimides Bearing Bis(trifluoromethyl)‐triphenylamine Moiety: Preparation and Rewritable Nonvolatile Memory Behaviours

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The synthesis of a Cu(ii) Schiff base complex using a bidentate N₂O₂ donor ligand: crystal structure, photophysical properties, and antibacterial activities