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Multi-attribute wearable pressure sensor based on multilayered modulation with high constant sensitivity over a wide range

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Nano Research 2023年第5期16卷 7583-7592页

作者： Ning Li Song Gao Yang Li Jianwen Liu Wenhao Song Guozhen Shen School of Information Science and Engineering University of JinanJinan 250022China Shandong Provincial Key Laboratory of Network Based Intelligent Computing University of JinanJinan 250022China School of Integrated Circuits and Electronics Beijing Institute of TechnologyBeijing 100081China School of Aeronautical and Astronautical Engineering Purdue University West LafayetteIN 47907USA

Flexible pressure sensors capable of monitoring diverse physiological signals and body movements have garnered tremendous attention in wearable electronic devices.Thereinto,high constant sensitivity over a wide pressure range combined with breathability,biocompatibility,biodegradability is pivotal for manufacturing of reliable pressure sensors in practical sensing applications.In this work,inspired by the multilayered structure of skin epidermis,we propose and demonstrate a multi-attribute wearable piezoresistive pressure sensor consisting of multilayered gradient conductive poly(ε-caprolactone)nanofiber membranes composites.In response to externally applied pressure,a layer-by-layer current path is activated inside the multilayered membranes composites,leading to the most salient sensing performance of high constant sensitivity of 33.955 kPa^(−1) within the pressure range of 0–80 kPa.The proposed pressure sensor also exhibits a fast response–relaxation time,a low detection limit,excellent stability,which can be successfully used to measure human physiological signals.Lastly,an integrated sensor array system that can locate objects’positions is constructed and applied to simulate sitting posture monitoring.These results indicate that the proposed pressure sensor holds great potential in health monitoring and wearable electronic devices.

关键词： wearable pressure sensors multilayer structure high constant sensitivity multi-attribute physiological signals monitoring

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Strengthening absorption ability of Co-N-C as efficient bifunctional oxygen catalyst by modulating the d band center using MoC

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Green Energy & Environment 2023年第2期8卷 459-469页

作者： Jianwen Liu Ying Guo Xian-Zhu Fu Jing-Li Luo Chunyi Zhi Shenzhen Key Laboratory of Polymer Science and Technology Guangdong Research Center for Interfacial Engineering of Functional MaterialsCollege of Materials Science and EngineeringShenzhen University518060China Department of Materials Science and Engineering City University of Hong Kong83 Tat Chee AvenueKowloon TongHong KongChina Department of Chemical and Materials Engineering University of AlbertaEdmontonAlbertaT6G 1H9Canada

Co-N-C is a promising oxygen electrochemical catalyst due to its high stability and good durability.However,due to the limited adsorption ability improvement for oxygen-containing intermediates,it usually exhibits inadequate catalytic activity with 2-electron pathway and high selectivity of hydrogen peroxide.Herein,the adsorption of Co-N-C to these intermediates is modulated by constructing heterostructures using transition metals and their derivatives based on d-band theory.The heterostructured nanobelts with MoC core and pomegranate-like carbon shell consisting of Co nanoparticles and N dopant(MoC/Co-N-C)are engineered to successfully modulate the d band center of active Co-N-C sites,resulting in a remarkably enhanced electrocatalysis performance.The optimally performing MoC/Co-N-C exhibits outstanding bi-catalytic activity and stability for the oxygen electrochemistry,featuring a high wave-half potential of 0.865 V for the oxygen reduction reaction(ORR)and low overpotential of 370 mV for the oxygen evolution reaction(OER)at 10 mA cm^(-2).The zinc air batteries with the MoC/Co-N-C catalyst demonstrate a large power density of 180 mW cm^(-2)and a long cycling lifespan(2000 cycles).The density functional theory calculations with Hubbard correction(DFT+U)reveal the electron transferring from Co to Mo atoms that effectively modulate the d band center of the active Co sites and achieve optimum adsorption ability with"single site double adsorption"mode.

关键词： Bifunctional oxygen catalysts Pomegranate-like shell D band theory Enhanced synergistic effect Rechargeable zinc air battery

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Synergistic effect of lithiophilic Zn nanoparticles and N-doping for stable Li metal anodes

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Journal of Energy Chemistry 2022年第2期31卷 439-447页

作者： Lei You Shunlong Ju Jianwen Liu Guanglin Xia Zaiping Guo Xuebin Yu Department of Materials Science Fudan UniversityShanghai 200433China Hubei Collaborative Innovation Center for Advanced Organic Chemical Materials Ministry-of-Education Key Laboratory for Synthesis and Applications of Organic Functional MoleculesCollege of Chemistry and Chemical EngineeringHubei UniversityWuhan 430062HubeiChina School of Chemical Engineering&Advanced Materials The University of AdelaideAdelaideSA 5005Australia

Li metal is the most ideal anode material for next-generation high energy lithium-ion batteries.The uncontrollable growth of Li dendrites,however,hinders its practical application.Herein,we propose the adoption of Zn nanoparticles uniformly embedded in N-doped carbon polyhedra homogeneously built on carbon cloth(Zn@NC@CC)to prevent the formation of Li dendrites.Based on theoretical calculation and experimental observation,lithiophilic Zn nanoparticles and N-doping inside of the assynthesized Zn@NC play a synergistic role in enhancing the adsorption capacity with Li,thus resulting in uniform Li deposition and complete suppression of Li dendrites.Moreover,the porous N-doped carbon polyhedras uniformly distributed on carbon cloth effectively relieves the volume change of Li upon repeated Li stripping/plating process,which contributes to preserving the structural integrity of the whole electrode and hence enhancing its long-term cycling stability.Benefiting from these synergistic effects,the Li-Zn@NC@CC electrode delivers a prolonged lifespan of over 1200 h at 1 mA cm^(-2) with an areal capacity of 1 mA h cm^(-2) in symmetric cells and high Coulombic efficiencies of 95.4%under an ultrahigh capacity of 12 mA h cm^(-2).Remarkably,Li-Zn@NC@CC//LiFePO_(4) full cells deliver a high reversible capacity of 110.2 mA h g^(-1) at 1 C over 200 cycles.

关键词： Li metal anodes Zn nanoparticles N-doping Synergistic effect

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Boosting practical high voltage lithium metal batteries by butyronitrile in ether electrolytes via coordination, hydrolysis of C≡N and relatively mild concentration strategy

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Journal of Energy Chemistry 2022年第4期31卷 290-299页

作者： Jingrong Ning Kaijia Duan Kai Wang Jianwen Liu Shiquan Wang Jiujun Zhang College of Chemistry and Chemical Engineering&Collaborative Innovation Center for Advanced Organic Chemical Materials Co-constructed by the Province and Ministry&Ministry of Educational Key Laboratory for the Synthesis and Application of Organic Functional Molecules Hubei UniversityWuhanHubei 430062China Institute for Sustainable Energy/College of Science Shanghai UniversityShanghai 200444China

Currently ether solvents have been regarded as the most compatible organic solvents with lithium metal in electrolytes of lithium batteries.However,ether solvents are unstable under high voltage (>4.0 V),and prone to side reactions with nickel-rich high-voltage cathode materials.In this work,a novel dual-solvent electrolyte in ethylene glycol dimethyl ether (DME) and butyronitrile (BN) mixed solvent was designed and fabricated for Li/Li Ni_(0.5)Mn_(0.3)Co_(0.2)O_(2)-based lithium metal batteries.When charged to high voltage4.3 V,the battery cycled in this optimal electrolyte can maintain the capacity at 133.7 m Ah g^(-1) with a retention of 88.84%after 150 cycles at 0.2 C and-10℃.During long-term cycling,the battery also exhibits excellent cycling performance with capacity maintained at about 112.0 m Ah g^(-1) after 500 cycles at 1C and-10℃.BN has strong oxidation resistance and high conductivity,which can inhibit the decomposition of ether solvents under high voltage and improve the low temperature performance of battery effectively.Additionally,the cyano (–C≡N) group in BN molecular has a strong coordination ability with the high-valent metal ions and can mask the active ions on the cathode,correspondingly reducing the corrosion of cathode material by the electrolyte.Moreover,cyano group can participate in the hydrolysis to remove trace amounts of water and acidic by-products such as HF in the electrolyte.Therefore,the boosting effect of butyronitrile for ether solvents can provide a promising strategy for enhancing the performance of high voltage lithium metal batteries for practical industrialization.

关键词： Electrolytes Lithium metal batteries Ether solvents Butyronitrile High voltage

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Dual-metal zeolite imidazolate framework for efficient lithium storage boosted by synergistic effects and self-assembly 2D nanosheets

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Chinese Chemical Letters 2022年第6期33卷 3291-3295页

作者： Ming Yue Yajing Fu Canping Zhang Junxiao Fu Shiquan Wang Jianwen Liu College of Chemistry and Chemical Engineering&Collaborative Innovation Center for Advanced Organic Chemical Materials Co-constructed by the Province and Ministry&Ministry of Educational Key Laboratory for the Synthesis and Application of Organic Functional Molecules Hubei UniversityWuhan 430062China Jiangsu Pylon Battery Co. Ltd.Yangzhou 211400China

Metal-organic framework materials(MOFs),such as zeolitic imidazolate framework(ZIF),have been widely used in energy storage due to their advantages such as high structural stability,large specific surface,more active sites and skeleton structures.Herein,a novel two-dimensional(2D)Co Cu-ZIF was synthesized by a facile solvothermal method.The as-prepared Co Cu-ZIF nanosheets exhibit an ultrahigh reversible capacity of 2287.4 m Ah/g and remains at 1172.1 m Ah/g after 300 cycles at a current density of 100 m A/g,far better than that of the single Co-ZIF and Cu-ZIF.Additionally,the specific discharge capacity of Co Cu-ZIF nanosheets can maintain at about 590 m Ah/g after 1000 cycles at the current density of 2 A/g.Owing to the synergistic effect of two metals,function of nitrogen in the molecular and selfassembly 2D nanosheets,our research can provide strong support for the practical application of Co Cu-ZIF materials in lithium ion batteries.

关键词： Lithium ion batteries Metal-organic frameworks Co Cu-ZIF nanosheets Synergistic effect Self-assembly

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Highly elastic cobweb-like SiO/CNF composites with reconstructed heterostructure for high-efficient lithium storage

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Chinese Chemical Letters 2021年第9期32卷 2914-2918页

作者： Jie liu Miao Ben Andeng liu Jianwen Liu Shiquan Wang Jiujun Zhang Hubei Collaborative Innovation Center for Advanced Organic Chemical Materials&Ministry of Educational Key Laboratory for the Synthesis and Application of Organic Functional Molecules&College of Chemistry and Chemical Engineering Hubei UniversityWuhan 430062China Institute for Sustainable Energy College of ScienceShanghai UniversityShanghai 200444China

The silicon-based materials are promising candidates for lithium-ion batteries owing to their high energy density.However,achieving long lifespan under realistic conditions remains a challenge because of the volume expansion and low conductivity.In this work,the highly elastic cobweb-like composite materials consisted by SiO and nanofibers are designed and fabricated for high-efficient lithium storage by ballmilling&electrostatic spinning method.The reconstructed heterostructure and highly elastic nanofibers can simultaneously increase the conductivity and inhibit the"expansion effect"of silicon-based materials.The constructed electrode of n-SiO/CNF delivers an initial capacity of 1700 m Ah/g,and maintains the capacities over 1000 m Ah/g after 100 cycles at the current density of 500 m A/g.Meanwhile,this electrode can give an initial coulombic efficiency over 85%and maintains at 98%in the following charge/discharge processes.Furthermore,it exhibits efficient long-term electrochemical performance,maintaining the capacity at about 1000 m Ah/g at a high current density of 1000 m A/g after 1000 cycles.This work could provide a promising strategy for enhancing the performance of siliconbased composite materials for practical application in lithium-ion batteries.

关键词： Lithium ion batteries Silicon-based materials SiO/CNF composites Highly elastic composites Reconstructed heterostructure

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Simulation of FY-2D infrared brightness temperature and sensitivity analysis to the errors of WRF simulated cloud variables

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Science China Earth Sciences 2018年第7期61卷 957-972页

作者： Xiaokang SHI Yaodong LI Jianwen Liu Xizi XIANG Le liu Beijing Aviation Meteorological Institute Beijing 100085China Guizhou Sub-bureau of Southwest Air Traffic Management Bureau of Civil Aviation of China Guiyang 550002China Guangxi Meteorological Observatory Nanning 530022China

This study simulated FY-2 D satellite infrared brightness images based on the WRF and RTTOV models. The effects of prediction errors in WRF micro-and macroscale cloud variables on FY-2 D infrared brightness temperature accuracy were analyzed. The principle findings were as follows. In the T+0–48 h simulation time, the root mean square errors of the simulated brightness temperatures were within the range 10–27 K, i.e., better than the range of 20–40 K achieved previously. In the T+0–24 h simulation time, the correlation coefficients between the simulated and measured brightness temperatures for all four channels were >0.5. The simulation performance of water channel IR3 was stable and the best. The four types of cloud microphysical scheme considered all showed that the simulated values of brightness temperature in clouds were too high and that the distributions of cloud systems were incomplete, especially in typhoon areas. The performance of the THOM scheme was considered best, followed in descending order by the WSM6, WDM6, and LIN schemes. Compared with observed values, the maximum deviation appeared in the range 253–273 K for all schemes. On the microscale, the snow water mixing ratio of the THOM scheme was much bigger than that of the other schemes. Improving the production efficiency or increasing the availability of solid water in the cloud microphysical scheme would provide slight benefit for brightness temperature simulations. On the macroscale, the cloud amount obtained by the scheme used in this study was small. Improving the diagnostic scheme for cloud amount, especially high-level cloud, could improve the accuracy of brightness temperature simulations. These results could provide an intuitive reference for forecasters and constitute technical support for the creation of simulated brightness temperature images for the FY-4 satellite.

关键词：亮度温度温度模拟 WRF 红外线模仿敏感分析调查结果关联系数

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Metagenomic next-generation sequencing for pneumocystis jirovecii pneumonia in patients with connective tissue disease

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Rheumatology & Autoimmunity 2023年第2期3卷 100-107页

作者： Jianwen Liu Chenmin Wu Juanjuan He Yanfang Wu Fei Gao Zhihan Chen Department of Rheumatology and Immunology Fujian Provincial HospitalShengli Clinical Medical College of Fujian Medical UniversityFuzhouFujianChina

Background:Accurate diagnosis of Pneumocystis jirovecii pneumonia(PJP)is challenging,and the delayed diagnosis of PJP is associated with high mortality in patients with connective tissue disease(CTD).Metagenomic next-generation sequencing(mNGS)technology facilitates etiological diagnosis of various infectious diseases,with promising application in diagnosing PJP.This study aimed to investigate the value of mNGS using bronchoalveolar lavage fluid(BALF)for diagnosing PJP infection.Methods:Data from 55 patients with CTD and suspected pulmonary infection was retrospectively collected and analysed.A PJP group and non-PJP group were formed.The clinical manifestations,laboratory test results,treatment methods,and outcomes were summarized.BALF mNGS results were compared with traditional pathogen tests(TPT)and serum 1,3-beta-D-glucan(BDG)testing.Results:The mean age of PJP patients was 54 years,and 59%(10/17)of the patients were female.A significant difference was found between the average daily dose of prednisone administered to the PJP group and non-PJP group(25 mg vs.16 mg,P<0.001).The PJP group had a significantly higher incidence of dyspnoea(88%[15/17]vs.16%[6/38],P<0.001)and elevated serum BDG level(167.73 vs.30.67 pg/mL,P<0.001).BALF mNGS was more sensitive than both TPT(100%[95%confidence interval{CI}:77.1%-100%]vs.11.8%[95%CI:2.1%-37.7%],P<0.001)and serum BDG(100%[95%CI:77.1%-100%]vs.85.7%[95%CI:42%-99.2%],P<0.001).BALF mNGS was more specific than serum BDG(89.5%[95%CI:74.3%-96.6%]vs.46.7%[95%CI:22.3%-72.6%],P=0.493).Co-infection with cytomegalovirus(CMV)was more common in the PJP patients than in the non-PJP patients(59%[10/17]vs.11%[4/38],respectively,P<0.001).Conclusion:BALF mNGS technology is highly effective for diagnosing PJP in patients with CTD and identifying co-infections.

关键词： Connective tissue disease(CTD) Metagenomics next-generation sequencing(mNGS) Pneumocystis jirovecii pneumonia(PJP)

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ISAR autofocus imaging algorithm for maneuvering targets based on deep learning and keystone transform

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Journal of Systems Engineering and Electronics 2020年第6期31卷 1178-1185页

作者： SHI Hongyin liu Yue GUO jianwen liu Mingxin School of Information Science and Engineering Yanshan UniversityQinhuangdao 066004China

The issue of small-angle maneuvering targets inverse synthetic aperture radar(ISAR)imaging has been successfully addressed by popular motion compensation algorithms.However,when the target’s rotational velocity is sufficiently high during the dwell time of the radar,such compensation algorithms cannot obtain a high quality image.This paper proposes an ISAR imaging algorithm based on keystone transform and deep learning algorithm.The keystone transform is used to coarsely compensate for the target’s rotational motion and translational motion,and the deep learning algorithm is used to achieve a super-resolution image.The uniformly distributed point target data are used as the data set of the training u-net network.In addition,this method does not require estimating the motion parameters of the target,which simplifies the algorithm steps.Finally,several experiments are performed to demonstrate the effectiveness of the proposed algorithm.

关键词： inverse synthetic aperture radar(ISAR) maneuvering target keystone transform deep learning u-net network

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Highly-efficient quantitative fluorescence resonance energy transfer measurements based on deep learning

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Journal of Innovative Optical Health Sciences 2020年第6期3卷 23-35页

作者： Lin Ge Fei liu jianwen Luo Department of Biomedical Engineering School of Medicine Tsinghua UniversityBeijing100084China Beijing Advanced Information&Industrial Technology Research Institute Beijing Information Science&Technology University Beijing 100192China

Intensity-based quantitative fluorescence resonance energy transfer(FRET)is a technique to measure the distance of molecules in scale of a few nanometers which is far beyond optical diffraction limit.This widely used technique needs complicated experimental process and manual image analyses to obtain precise results,which take a long time and restrict the application of quantitative FRET especially in living cells.In this paper,a simplified and automatic quanti-tative FRET(saqFRET)method with high efficiency is presented.In saqFRET,photo-activatable acceptor PA-mCherry and optimized excitation wavelength of donor enhanced green fluorescent protein(EGFP)are used to simplify FRET crosstalk elimination.Traditional manual image analyses are time consuming when the dataset is large.The proposed automatic image analyses based on deep learning can analyze 100 samples within 30 s and demonstrate the same precision as manual image analyses.

关键词： Resonance energy transfer fluorescence living cells photoactivatable deep network

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