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Carbon Nanotube Transistors
Published in Changjian Zhou, Min Zhang, Cary Y. Yang, Nanocarbon Electronics, 2020
Min Zhang, Chunhui Du, Qiuyue Huang, Zhiqiang Liao, Yanyan Deng, Weihong Huang, Xiaofang Wang
Ion gel is one of the intrinsically stretchable materials with high ionic conductivity, specific large capacitance [176, 177], which can be used as dielectric layers in stretchable electronic devices. In 2014, Xu et al. fabricated stretchable CNT TFTs by transfer and pre-strain approach using ion gel as the dielectric layer, SWCNT film as the channel, Au/Cr (25 nm/4 nm) metal films as source, drain, and side-gate electrodes, as shown in Figs. 4.17a–d [178]. The main reason to use the pre-stretching is that the electrode is made of a bulk metal film. The device could operate in a large tensile strain range from 0 to 50%. Owing to the large capacitance and stretchability of the ion gel gate dielectric, an Ion/Ioff > 104, a mobility of 10 cm2 V−1s−1, and a low operating voltage of < 2 V were achieved and maintained during repeated mechanical stretch cycle, as shown in Figs. 4.17e and f.
Properties of Electroactive Polymers
Published in Inamuddin, Mohd Imran Ahamed, Rajender Boddula, Adil A. Gobouri, Electroactive Polymeric Materials, 2022
An ion gel is a material that consists of an inorganic or polymer matrix immobilized ionic liquid (12, 13). An ion gel can be obtained by mixing or synthesizing the solid matrix and ionic liquid in situ or by using a block copolymer polymerized in solution with the ionic liquid. The aim is to create a self-assembled nanostructure in which ions can be dissolved selectively. Ion gels can be synthesized using materials such as oxides, non-copolymer polymers, or boron nitride. Ion gels can be polymeric and inorganic. The main purpose of ion gel applications is to electrically insulate the matrix components to provide ionic conductivity (14).
Ionic Liquid-Based Electrolytes
Published in Ming-Fa Lin, Wen-Dung Hsu, Jow-Lay Huang, Lithium-Ion Batteries and Solar Cells, 2021
Linh T. M. Le, Thanh D. Vo, Hoang V. Nguyen, Man V. Tran, Phung M. L. Le
ILs can be mixed with polymers [42], resulting in gels, hereafter termed “ion-gels,” which can be used as electrolytes for batteries. In ion-gels (polymer electrolyte), ILs are confined in the polymer matrix, and this is advantageous to avoid the leakage of electrolytes and resolve the safety issue of batteries. Ion-gels, however, are clearly different from conventional polymer electrolytes. In the case of Li+−-conducting conventional polymer electrolytes, Li salts are dissolved in polymers such as poly(ethylene oxide) (PEO), and the ionic conduction is coupled with the segmental motion of the polymer chains [43]. Therefore, the ionic conductivities of conventional polymer electrolytes are as low as 10−6–10−4 S cm−1 at room temperature. On the other hand, in the case of ion-gels, the liquid-state salts such as Li salt/organic ILs are mixed with polymers and the ILs behave as both charge carriers and plasticizers in the gels. By using ILs, we can prepare “polymer-in-salt” [44]-type electrolytes having relatively high ionic conductivity of ca. 10−4–10−3 S cm−1 at room temperature. Polyethylene oxide (PEO) [45], poly(methyl methacrylate) (PMMA) [46], and copolymer of poly(vinylidene fluoride–co-hexafluoropropylene) (PVDF-HFP) [47] have been reported to be compatible with ILs. It is known that the PVDF-HFP has relatively good mechanical strength due to the partially crystalline nature even if some plasticizer is included in the matrix [42]. The ionic conductivity is enhanced when increasing the content of IL in an ion-gel; however, the gel also becomes mechanically weaker. To achieve both high ionic conductivity and sufficient mechanical strength, the polymer cross-linking is effective [46].
Biological function simulation in neuromorphic devices: from synapse and neuron to behavior
Published in Science and Technology of Advanced Materials, 2023
Hui Chen, Huilin Li, Ting Ma, Shuangshuang Han, Qiuping Zhao
The photon synapses of photo-electric mixed type are based on the electrical synapses and combine with continuous illumination or light pulses to improve the synaptic plasticity. Sun et al. [67] have reported this mixed-type photon synapse, wherein graphene oxide (GO) nanosheets modified with long alkyl chains are embedded as a charge-trapping layer between the ion-gel dielectric and the indium-gallium-zinc oxide (IGZO) semiconductor (Figure 5(a)). In this device, several important forms of synaptic plasticity, including EPSC, IPSC, LTP and LTD, are successfully achieved in the pure electric mode. More importantly, when the light is introduced, these forms are improved so that the amplitude change of PSC (∆PSC) becomes much greater than the one for only electrical pulses with the same number of pulses and is in direct proportion to the light power. PSC in this mixed mode is three times larger than in the electrical mode after 200 pulses, which results in a much higher recognition rate when using these PSCs in the pattern recognition. However, in the photo-electric mixed type, light is only an auxiliary approach, and strictly speaking, this mode is not a real optical synapse. In contrast, single optical and fully optical artificial synapses display the importance of light because the light can be used to simulated these forms of synaptic plasticity.
Recent advances in neuromorphic transistors for artificial perception applications
Published in Science and Technology of Advanced Materials, 2023
Hu et al. [96] developed a novel method to synthesize hydrophilic MoS2 monolayers through covalently introducing hydroxyl groups during growth. They propose neuromorphic visual systems consisted of arrays of hydrophilic MoS2 monolayer optical memory transistors. Because of strong capability of charge trapping for hydroxyl groups, the hydrophilic MoS2 monolayers can demonstrate excellent electrical, optical, and memory properties. Figure 8(a) shows a schematic of the operational mechanism. The transistor demonstrates excellent light-dependent and time-dependent photoelectric performances. Moreover, it also demonstrates good photo-responsive memory characteristics with multibit storage. The switching ratio is above 104. It is worth noting that the neuromorphic visual system realizes high-quality image sensing and memory with high color resolution. The work provides a new concept to realize image memorization and to simplify pixel matrix preparation process, which is interesting to the development of artificial visual systems. Recently, 3D-object recognition of the stereo vision has also been successfully mimicked by constructing multiterminal neuromorphic transistors. Fan et al. [36] reported PEO and PEO:LiClO4 side-liquid-gated In2O3, pentacene thin-film transistors (TFTs) and 2D-MoS2 FETs for synaptic plasticity engineering with proton conducting mechanism and charge trapping engineering. These devices demonstrate both STP and LTP. Interestingly, a proof-of-principle artificial stereo vision system is proposed for 3D-object recognition based on In2O3/Er2O3 synaptic transistors (Figure 8(b)), which provides great potential for neuromorphic applications. The work is of interest for constructing spiking neural networks with powerful brain-inspired dynamic spatiotemporal processing. Artificial visual perception system similar to adaptive ambient brightness has also been implemented on side-gate transistors. Jin et al. [95] designed optoelectronic In2O3 transistor array with negative photoconductivity behavior using a side-gate structure. Screen-printed ion-gel acts as gate insulator. Here, an artificial visual perception system capable of self-adapting to environmental lightness is mimicked using the optoelectronic In2O3 transistor array. Under different levels of light intensity, self-adaptive behavior of light is demonstrated on the device array. Thus, visual adaption with an adjustable threshold range to the external environment is demonstrated. This work provides a new scheme to environmentally adaptive artificial visual perception system, as is meaningful for future artificial intelligence sensing and neuromorphic electronics.