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| 1 | Defect-engineered Mn_(3)O_(4)/CNTs composites enhancing reaction kinetics for zinc-ions storage performance显示文摘The designing of reasonable nanocomposite materials and proper introduction of defect engineering are of great significance for the improvement of the poor electronic conductivity and slow reaction kinetics of manganese-based compounds. Herein, we report manganese-deficient Mn_(3)O_(4) nanoparticles which grow in-situ on highly conductive carbon nanotubes(CNTs)(denoted as DMOC) as an advanced cathode material for aqueous rechargeable zinc-ion batteries(RAZIBs). According to experimental and calculation results, the DMOC cathode integrates the advantages of enriched Mn defects and small particle size. These features not only enhance electronic conductivity but also create more active site and contribute to fast reaction kinetics. Moreover, the structure of DMOC is maintained during the charging and discharging process, thus benefiting for excellent cycle stability. As a result, the DMOC electrode delivers a high specific capacity of 420.6 m A h g^(-1) at 0.1 A g^(-1) and an excellent cycle life of 2800 cycles at 2.0 A g^(-1) with a high-capacity retention of 84.1%. In addition, the soft-packaged battery assembled with DMOC cathode exhibits long cycle life and high energy density of 146.3 Wh kg^(-1) at 1.0 A g^(-1) . The results are beneficial for the development of Zn/Mn_(3)O_(4) battery for practical energy storage. | Xiuli Guo Hao Sun Chunguang Li Siqi Zhang Zhenhua Li Xiangyan Hou Xiaobo Chen Jingyao Liu Zhan Shi Shouhua Feng | 2022 | Journal of Energy Chemistry2022，31，5： | 1 |
| 2 | Production of sorption functional media (SFM) from clinoptilolite tailings and its performance investigation in a biological aerated filter (BAF) reactor显示文摘 | Yan Feng Jingyao Qi Liying Chi Dong Wang Zhaoyang Wang Ke Li Xin Li | 2013 | Journal of Hazardous Materials2013，，： | 1 |
| 3 | Robust Reconstruetion of Block Sparse Signals from Adaptively One-Bit Measurements显示文摘Though various theoretical results and algorithms have been proposed in one-bit Compressed sensing(l・bit CS),t here are few stu dies on more structured signals,such as block sparse signals.We address the problem of recovering block sparse signals from one-bit measurements.We first propose two recovery schemes,one based on second-order cone programming and the other based on hard thresholding,for common non-adaptively thresholded one-bit measurements.Note that the worst・case error in recovering sparse signals from non・adaptively thresholded one-bit measurements is bounded below by a polynomial of oversampling factor.To break the limit,we introduce a recursive strategy that allows the thresholds in quantization to be adaptive to previous measurements at each it eration.Using the scheme,we propose two iterative algorithms and show that corresponding recovery errors are both exponential functions of the oversampling factor.Several simulations are conducted to reveal the superiority of our methods to existing approaches. | HOU Jingyao WANG Jianjun ZHANG Feng HUANG Jianwen | 2020 | Chinese Journal of Electronics2020，29，5： | 1 |
| 4 | Tensor restricted isometry property analysis for a large class of random measurement ensembles显示文摘Dear editor,Low-rank tensor recovery(LRTR)[1]is a natural higherorder generalization of the compressed sensing(CS)[2]and the low-rank matrix recovery(LRMR)[3,4].It has been applied extensively in various fields of artificial intelligence,including computer vision,image processing and machine learning. | Feng ZHANG Wendong WANG Jingyao HOU Jianjun WANG Jianwen HUANG | 2021 | Science China(Information Sciences)2021，64，1： | 1 |
| 5 | An intermediate poly-dopamine layer for alginate coating on high-purity magnesium to achieve corrosion mitigation显示文摘Although magnesium(Mg)and its alloys are proposed as the next generation orthopedics transplanted materials,their clinical applications are limited by the fast degradation.To reduce the degradation rate,a strong adhesion poly-dopamine(PDA)layer was introduced as an intermediate layer for the subsequent alginate(ALG)spin-coating on high-purity Mg.The surface morphology and chemical composition were detected by scanning electron microscope,energy disperse spectroscopy,and Fourier transform infrared spectroscopy.The corrosion resistances of all samples were evaluated by electrochemical and 10-day immersion tests in Hanks’balanced salt solution.Our results suggest that the thickness of the fabricated PDA/ALG composite coating is 8.58±0.65μm,and the intermediate PDA layer evidently enhances the adhesion between the substrate and ALG coating.The corrosion current density of Mg coated with the PDA/ALG composite coating decreases more than 10 times compared to that of the Mg substrate,and the charge transfer resistance is 12 times bigger than that of the bare Mg,which indicates the improved corrosion resistance.Moreover,the mechanism of corrosion protection of the composite coating is also discussed. | Qingyun Fu Weihong Jin Mingcheng Feng Jingyao Li Jian Li Wei Li Zhentao Yu | 2023 | Journal of Magnesium and Alloys2023，11，6： | 0 |
| 6 | Deep Learning Models Based on Weakly Supervised Learning and Clustering Visualization for Disease Diagnosis显示文摘The coronavirus disease 2019(COVID-19)has severely disrupted both human life and the health care system.Timely diagnosis and treatment have become increasingly important;however,the distribution and size of lesions vary widely among individuals,making it challenging to accurately diagnose the disease.This study proposed a deep-learning disease diagnosismodel based onweakly supervised learning and clustering visualization(W_CVNet)that fused classification with segmentation.First,the data were preprocessed.An optimizable weakly supervised segmentation preprocessing method(O-WSSPM)was used to remove redundant data and solve the category imbalance problem.Second,a deep-learning fusion method was used for feature extraction and classification recognition.A dual asymmetric complementary bilinear feature extraction method(D-CBM)was used to fully extract complementary features,which solved the problem of insufficient feature extraction by a single deep learning network.Third,an unsupervised learning method based on Fuzzy C-Means(FCM)clustering was used to segment and visualize COVID-19 lesions enabling physicians to accurately assess lesion distribution and disease severity.In this study,5-fold cross-validation methods were used,and the results showed that the network had an average classification accuracy of 85.8%,outperforming six recent advanced classification models.W_CVNet can effectively help physicians with automated aid in diagnosis to determine if the disease is present and,in the case of COVID-19 patients,to further predict the area of the lesion. | Jingyao Liu Qinghe Feng Jiashi Zhao Yu Miao Wei He Weili Shi Zhengang Jiang | 2023 | Computers, Materials & Continua2023，76，9： | 0 |
| 7 | Optimizing the electronic spin state and delocalized electron of NiCo_(2)(OH)_(x)/MXene composite by interface engineering and plasma boosting oxygen evolution reaction显示文摘The electrocatalytic activity of transition-metal-based compounds is closely related to the electronic configuration.However,optimizing the surface electron spin state of catalysts remains a challenge.Here,we developed a spin-state and delocalized electron regulation method to optimize oxygen evolution reaction(OER)performance by in-situ growth of NiCo_(2)(OH)_(x) using Oswald ripening and coordinating etching process on MXene and plasma treatment.X-ray absorption spectroscopy,magnetic tests and electron paramagnetic resonance reveal that the coupling of NiCo_(2)(OH)_(x) and MXene can induce remarkable spin-state transition of Co^(3+)and transition metal ions electron delocalization,plasma treatment further optimizes the 3 d orbital structure and delocalized electron density.The unique Jahn-Teller phenomenon can be brought by the intermediate spin state(t2 _(g)^(5) e_(g)^(1))of Co^(3+),which benefits from the partial electron occupied egorbitals.This distinct electron configuration(t2_(g)^(5) e_(g)^(1))with unpaired electrons leads to orbital degeneracy,that the adsorption free energy of intermediate species and conductivity were further optimized.The optimized electrocatalyst exhibits excellent OER activity with an overpotential of 268 m V at 10 m A cm^(-2).DFT calculations show that plasma treatment can effectively regulate the d-band center of TMs to optimize the adsorption and improve the OER activity.This approach could guide the rational design and discovery of electrocatalysts with ideal electron configurations in the future. | Jingyao Xu Xia Zhong Xiaofeng Wu Ying Wang Shouhua Feng | 2022 | Journal of Energy Chemistry2022，31，8： | 0 |
| 8 | In situ mechanical characterization of silver nanowire/graphene hybrids films for flexible electronics显示文摘Flexible transparent conductive films are indispensable for nowadays wearable electronic devices with various applications.However,existing solutions such as ITO and metal mesh were limited by their poor intrinsic stretching ability.In this work,we designed and fabricated silver nanowires(AgNWs)on graphene hybrid films for enhanced mechanical and electrical performance.In situ TEM characterizations show that,beside conductive paths,silver nanowire network,can also contribute to the toughening mechanisms of the hybrid films.Furthermore,bending and electrical tests were applied to examine the corresponding flexible electronics’perfor-mance.Finally,we showed that the fabrication of our AgNW/graphene hybrid films could be scaled up for large film applications and extended to other 1D/2D hybrid systems. | Ke Cao Haokun Yang Libo Gao Ying Han Jingyao Feng Hongwei Yang Haiyan Zhang Weidong Wang Yang Lu | 2020 | International Journal of Smart and Nano Materials2020，11，3： | 0 |
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