Ionic conductive hydrogel electrolyte is considered to be an ideal electrolyte candidate for flexible supercapacitor due to its flexibility and high conductivity. However, due to the lack of ...effective recycling methods, a large number of ineffective flexible hydrogel supercapacitors caused by some irreversible damages and dryness of hydrogel electrolyte are abandoned, which would induce heavy economic and environmental protection problems. Herein,a smart ionic conductive hydrogel (SPMA‐Zn: ZnSO4/sodium alginate/polymethylacrylic acid) is developed for flexible hybrid supercapacitor (SPMA‐ZHS). The SPMA‐Zn exhibits an excellent self‐healing ability and can recover its electrochemical performance after multiple mechanical damages. More importantly, it possesses an outstanding powder self‐healable property, which could easily regenerate the hydrogel electrolyte after powdering, and maintain stable electrochemical performance of SPMA‐ZHS. Besides, the SPMA‐ZHS displays excellent electrochemical performance with a wide and stable working voltage range of 0–2.2 V, high energy density of 164.13 Wh kg−1 at the power density of 1283.44 Wh kg−1 and good stability with a capacity retention of 95.3% after 5000 charge/discharge cycles at 10 A g−1. The strategy in this work would provide a new insight in exploring flexible hydrogel electrolyte‐based supercapacitor with good sustainability and high energy density for flexible wearable electronic devices.
A recyclable hydrogel electrolyte with excellent conductivity and self‐healing ability is designed for flexible supercapacitors. Compared with existing flexible supercapacitor, the sodium alginate polymethylacrylic acid hydrogels based zinc hybrid supercapacitor not only exhibits high energy density and excellent self‐healing ability, but also possesses good powder self‐healable ability to guarantee the hydrogel electrolyte‐based supercapacitor with excellent recyclability, exhibiting great potential for sustainable flexible energy storage devices.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
As an important part of artificial intelligence, electronic skin has received more and more attention recently. However, two serious issues, slow self-healing and lack of direction recognition, have ...limited the burgeoning of electronic skin largely. Herein, for the first time we report a dual network flexible hydrogel, which was synthesized
via
cross-linking polyvinyl alcohol (PVA) and polyethylenimine (PEI) with 4-formylbenzoboric acid (Bn) to form a polymer network and then incorporating MXene into the polymer network. Due to the synergy of multiple reversible dynamic covalent bonds and supramolecular interactions, the PVA/Bn/PEI/MXene (PBPM) hydrogel exhibits direction-aware and ultrafast self-healing abilities (self-healing time ∼0.06 s) as well as rapid response performance (signal response time ∼0.12 s). Furthermore, an electronic skin strain sensor assembled by using the PBPM hydrogel can not only efficiently detect the movements in different parts of the prosthetic person body but also specifically identify the directions of the movements including head-down/up and wrist-down/up. The flexible PBPM hydrogel in this work has shown great potential in the applications of artificial skin, soft robots, health monitoring and human-machine exchange interfaces.
A dual network flexible electronic skin hydrogel with direction-recognition and ultrafast self-healing ability was prepared and applied for strain sensors.
With the rapid development of economy, computer software technology has been used in various fields, different design software has different design functions and software characteristics, graphic ...design has begun to use a variety of computer image processing software for processing. The combination of computer graphic design and related design software can optimize the effect of graphic design. Taking graphic design as an example, this paper briefly analyzes some applications of computer software technology in graphic design.
Despite the wide applications of functional magnetic resonance imaging (fMRI) to mapping brain activation and connectivity in cortical gray matter, it has rarely been utilized to study white-matter ...functions. In this study, we investigated the spatiotemporal characteristics of fMRI data within the white matter acquired from humans both in the resting state and while watching a naturalistic movie. By using independent component analysis and hierarchical clustering, resting-state fMRI data in the white matter were de-noised and decomposed into spatially independent components, which were further assembled into hierarchically organized axonal fiber bundles. Interestingly, such components were partly reorganized during natural vision. Relative to resting state, the visual task specifically induced a stronger degree of temporal coherence within the optic radiations, as well as significant correlations between the optic radiations and multiple cortical visual networks. Therefore, fMRI contains rich functional information about the activity and connectivity within white matter at rest and during tasks, challenging the conventional practice of taking white-matter signals as noise or artifacts.
•ICA applied to white-matter fMRI signals reveals reproducible and hierarchical patterns.•White-matter ICA components are mostly preserved, but are in part distinct between the resting state and the task state.•The distinction is specific to the axonal fibers involved in the task execution.•White-matter fMRI data are not noise or artifacts, but instead are signals of likely neuronal origin.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Biostable electronic materials that can maintain their super mechanical and conductive properties, even when exposed to biofluids, are the fundamental basis for designing reliable bioelectronic ...devices. Herein, cellulose‐derived conductive 2D bio‐nanosheets as electronic base materials are developed and assembled into a conductive hydrogel with ultra‐high biostability, capable of surviving in harsh physiological environments. The bio‐nanosheets are synthesized by guiding the in situ regeneration of cellulose crystal into a 2D planar structure using the polydopamine‐reduced‐graphene oxide as supporting templates. The nanosheet‐assembled hydrogel exhibits stable electrical and mechanical performances after undergoing aqueous immersion and in vivo implantation. Thus, the hydrogel‐based bioelectronic devices are able to conformally integrate with the human body and stably record electrophysiological signals. Owing to its tissue affinity, the hydrogel further serves as an “E‐skin,” which employs electrotherapy to aid in the faster healing of chronic wounds in diabetic mice through transcutaneous electrical stimulation. The nanosheet‐assembled biostable, conductive, flexible, and cell/tissue affinitive hydrogel lays a foundation for designing electronically and mechanically reliable bioelectronic devices.
2D conductive cellulose nanosheets are developed using polydopamine‐reduced graphene oxide‐templated in situ regeneration of nanostructured cellulose. The resulting nanosheets are then assembled into a biostable conductive hydrogel that withstands harsh physiological environments. The hydrogel is highly suitable for reliable bioelectronic applications to record electrophysiological signals stably and can serve as an “E‐skin” for electrotherapy to promote chronic diabetic wound healing.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
This paper proposes a new method of mixed gas identification based on a convolutional neural network for time series classification. In view of the superiority of convolutional neural networks in the ...field of computer vision, we applied the concept to the classification of five mixed gas time series data collected by an array of eight MOX gas sensors. Existing convolutional neural networks are mostly used for processing visual data, and are rarely used in gas data classification and have great limitations. Therefore, the idea of mapping time series data into an analogous-image matrix data is proposed. Then, five kinds of convolutional neural networks-VGG-16, VGG-19, ResNet18, ResNet34 and ResNet50-were used to classify and compare five kinds of mixed gases. By adjusting the parameters of the convolutional neural networks, the final gas recognition rate is 96.67%. The experimental results show that the method can classify the gas data quickly and effectively, and effectively combine the gas time series data with classical convolutional neural networks, which provides a new idea for the identification of mixed gases.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Due to their outstanding flexibility and high sensitivity, stretchable ionic conductive hydrogel-based sensors are considered one of the best candidates for the real-time monitoring of human body ...motion as a wearable health-care detection electronic device. In the detection of body motion, the ionic conductive hydrogel is sensitive to its deformation. However, the current reported hydrogels struggle to recover their initial shape after numerous repeated stretching cycles owing to fatigue, leading to their response insensitivity and service life degradation. In this work, a super-stretchable and recoverable ionic conductive hydrogel (double network polymer hydrogel (SA-Zn): ZnSO
4
/sodium alginate/poly acrylic-acrylamide) was designed as a stretchable sensor for human body motion detection. The SA-Zn hydrogel exhibited outstanding stretchability (up to 4000% tensile strain) and excellent shape self-recovery ability (20 min recovery time). After self-recovery for 50 cycles, the hydrogel still retained good flexibility, stable self-recovery ability and high conductivity. More importantly, the assembled wireless wearable stretchable sensor (SA-Zn-W) could transform human body motion into a visual electrical signal when combined with a Wi-Fi transmitter, revealing its excellent sensitivity, fast response, effective identification and stable electromechanical repeatability. The superior performance of the SA-Zn-W offers a promising solution for effectively and remotely detecting human body motion.
A super-stretchable and self-recoverable ionic conductive hydrogel was designed and used as a wearable stretchable sensor to monitor human body motions.
A hybrid electric vehicle (HEV) is a product that can greatly alleviate problems related to the energy crisis and environmental pollution. However, replacing such a battery will increase the cost of ...usage before the end of the life of a HEV. Thus, research on the multi-objective energy management control problem, which aims to not only minimize the gasoline consumption and consumed electricity but also prolong battery life, is necessary and challenging for HEV. This paper presents an adaptive equivalent consumption minimization strategy based on a recurrent neural network (RNN-A-ECMS) to solve the multi-objective optimal control problem for a plug-in HEV (PHEV). The two objectives of energy consumption and battery loss are balanced in the cost function by a weighting factor that changes in real time with the operating mode and current state of the vehicle. The near-global optimality of the energy management control is guaranteed by the equivalent factor (EF) in the designed A-ECMS. As the determined EF is dependent on the optimal co-state of the Pontryagin’s minimum principle (PMP), which results in the online ECMS being regarded as a realization of PMP-based global optimization during the whole driving cycle. The time-varying weight factor and the co-state of the PMP are map tables on the state of charge (SOC) of the battery and power demand, which are established offline by the particle swarm optimization (PSO) algorithm and real historical traffic data. In addition to the mappings of the weight factor and the major component of the EF linked to the optimal co-state of the PMP, the real-time performance of the energy management control is also guaranteed by the tuning component of the EF of A-ECMS resulting from the Proportional plus Integral (PI) control on the deviation between the battery SOC and the optimal trajectory of the SOC obtained by the Recurrent Neural Network (RNN). The RNN is trained offline by the SOC trajectory optimized by dynamic programming (DP) utilizing the historical traffic data. Finally, the effectiveness and the adaptability of the proposed RNN-A-ECMS are demonstrated on the test platform of plug-in hybrid electric vehicles based on GT-SUITE (a professional integrated simulation platform for engine/vehicle systems developed by Gamma Technologies of US company) compared with the existing strategy.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
With the rapid development of flexible wearable electronic devices and the growing energy demands of modern society, flexible energy storage equipment is attracting increasing attention. Recently, ...flexible Zn-ion hybrid supercapacitors (ZHSs), as a new type of flexible energy storage device, have been reported. However, the limited energy density of the currently reported flexible ZHSs should be further improved to realize their large-scale applications. Herein, we designed a novel redox bromide-ion additive hydrogel electrolyte (SA-Zn-Br) for flexible Zn-ion hybrid supercapacitors (BH-ZHSs)
via
the introduction of extra faradaic contributions (3Br
−
/Br
3
−
) into the hydrogel electrolyte to improve their energy density. Additionally, the assembled flexible BH-ZHS displays a maximum energy density of 605 W h kg
−1
at a power density of 1848 W kg
−1
at an amazing voltage of 2.6 V, which is better than that of most reported flexible ZHSs. After a 5000 cycle charge/discharge cycling test, capacity retention of 87.7% is retained. Interestingly, the strong interactions between the charged groups and Zn
2+
ion in the SA-Zn-Br hydrogel electrolyte can harmonize Zn
2+
migration with uniform nucleation on a Zn foil surface, leading to layered zinc deposition. Additionally, the SA-Zn-Br hydrogel electrolyte can also serve as an inhibitor of water/oxygen, resulting in the mitigation of corrosion and highly reversible zinc stripping/depositing. The strategy described in this study should provide a new insight for exploring flexible ZHSs with boosted energy density and controllable zinc deposition.
A novel redox bromide-ion additive hydrogel electrolyte was designed for flexible Zn-ion hybrid supercapacitors to improve their energy density.
Platinum (Pt) is the most effective bench‐marked catalyst for producing renewable and clean hydrogen energy by electrochemical water splitting. There is demand for high HER catalytic activity to ...achieve efficient utilization and minimize the loading of Pt in catalysts. In this work, we significantly boost the HER mass activity of Pt nanoparticles in Ptx/Co to 8.3 times higher than that of commercial Pt/C by using Co/NC heterojunctions as a heterogeneous version of electron donors. The highly coupled interfaces between Co/NC and Pt metal enrich the electron density of Pt nanoparticles to facilitate the adsorption of H+, the dissociation of Pt−H bonds and H2 release, giving the lowest HER overpotential of 6.9 mV vs. RHE at 10 mA cm−2 in acid among reported HER electrocatalysts. Given the easy scale‐up synthesis due to the stabilization of ultrafine Pt nanoparticles by Co/NC solid ligands, Ptx/Co can even be a promising substitute for commercial Pt/C for practical applications.
Co/NC heterojunctions are used as “solid ligands” to control the growth of as‐supported ultrafine Pt nanoparticles via donating electrons. Ultrafine Pt nanoparticles with enhanced electron density promote the proton capture from electrolyte to catalyst surface, the dissociation of Pt−H bonds and successive release of H2 molecules from the Pt surface.
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