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Molecular crowding electrolytes for stabilizing Zn metal anode in rechargeable aqueous batteries

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Chinese Chemical Letters 2024年第7期35卷 445-451页

作者： Li Lin Song-Lin tian Zhen-Yu Hu Yu Zhang Li-Min Chang Jia-jun Wang Wan-qiang Liu Qing-Shuang Wang Fang Wang School of Materials Science and Engineering Changchun University of Science and TechnologyChangchun 130022China School of Life Science and Technology Changchun University of Science and TechnologyChangchun 130022China Key Laboratory of Preparation and Applications of Environmental Friendly Materials of the Ministry of Education Jilin Normal UniversityChangchun 130103China Zhongshan Institute of Changchun University of Science and Technology Zhongshan 528437China

A solid electrolyte interphase(SEI)with a robust mechanical property and a high ionic conductivity is imperative for high-performance zinc metal ***,it is difficult to form such a SEI directly from an *** this work,a molecular crowding effect is based on the introduction of Zn(OTF)_(2)and Zn(ClO_(4))_(2)to 2 mol/L ZnSO_(4)*** and experiments indicate that the Zn(OTF)_(2)and Zn(ClO_(4))_(2)not only create a molecularly crowded electrolyte environment to promote the interaction of Zn^(2+)and OTF^(-),but also participate in the reduction to construct a robust and high ionic-conductive SEI,thus promoting metal zinc deposition to the(002)crystal *** this molecular crowding electrolyte,a high current density of 1 mA/cm^(2)can be obtained by assembling symmetric batteries with Zn as the anode for over 1000 *** in a temperature environment of-10℃,a current density of 1 mA/cm^(2)can be obtained by assembling symmetric batteries with Zn for over 200 ***//Bi_(2)S_(3)/VS4@C cells achieve a CE rate of up to 99.81%over 1000 ***,the utilization of a molecular crowding electrolyte is deemed a highly effective approach to fabricating a sophisticated SEI for a zinc anode.

关键词： Zinc ion batteries Anode Electrolyte Solid electrolyte interphase Molecular crowding effect

Arbitrarily rotating polarization direction and manipulating phases in linear and nonlinear ways using programmable metasurface

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Light(Science & Applications) 2024年第9期13卷 1789-1800页

作者： Wei Liu Si Ran Wang jun Yan Dai Lei Zhang Qiao Chen qiang Cheng Tie jun Cui State Key Laboratory of Millimeter Waves Southeast UniversityNanjing 210096China Institute of Electromagnetic Space Southeast UniversityNanjing 210096China Frontiers Science Center for Mobile Information Communication and Security Southeast UniversityNanjing 210096China Electrical Engineering Department Chalmers University of TechnologyGothenburg 41258Sweden

Independent controls of various properties of electromagnetic(EM)waves are crucially required in a wide range of *** metasurface is a promising candidate to provide an advanced platform for manipulating EM ***,we propose an approach that can arbitrarily control the polarization direction and phases of reflected waves in linear and nonlinear ways using a stacked programmable ***,we extend the space-timecoding theory to incorporate the dimension of polarization,which provides an extra degree of freedom for manipulating EM *** proof-of-principle application examples,we consider polarization rotation,phase manipulation,and beam steering at linear and nonlinear *** validation,we design,fabricate,and measure a metasurface *** experimental results show good agreement with theoretical predictions and *** proposed approach has a wide range of applications in various areas,such as imaging,data storage,and wireless communication.

关键词： surface. nonlinear rotating

Constructing oxygen deficiency-rich V_(2)O_(3)@PEDOT cathode for high-performance aqueous zinc-ion batteries

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Rare Metals 2024年第2期43卷 635-646页

作者： Dong-Fei Sun Zi-Juan Wang tian tian Xin Yu Dan-Dan Yu Xiao-Zhong Zhou Guo-Fu Ma Zi-qiang Lei Key Laboratory of Eco-functional Polymer Materials of the Ministry of Education Key Laboratory of Eco-environmental Polymer Materials of Gansu ProvinceSchool of College of Chemistry and Chemical EngineeringNorthwest Normal UniversityLanzhou730070China

Aqueous zinc-ion batteries(AZIBs)have attracted widespread attention due to the advantages of high safety and environmental *** V_(2)O_(3) is a promising cathode,the strong electrostatic interaction between Zn^(2+) and V_(2)O_(3) crystal,and the sluggish reaction kinetics still limit their application in ***,the oxygen defects rich V_(2)O_(3) with conducive poly(3,4-ethylenedioxythiophene)(PEDOT)shell(V_(2)O_(3)-Od@PEDOT)was fabricated for AZIBs by combining the sulfur-assisted thermal reduction and in-situ polymerization *** introduced oxygen vacancies of V_(2)O_(3)–Od@PEDOT weaken the electrostatic interaction between Zn^(2+) and the host material,improving the interfacial electron transport,while the PEDOT coating enhances the structural stability and conductivity of V_(2)O_(3),thus accelerating the reaction *** on the advantages,V_(2)O_(3)–Od@PEDOT electrode delivers a reversible capacity of 495 mAh·g^(−1) at 0.1 A·g^(−1),good rate capability(189 mAh·g^(−1)at 8.0 A·g^(−1)),and an impressive cycling stability with 90.1%capacity retention over 1000 cycles at 8.0 A·g^(−1).The strategy may provide a path for exploiting the other materials for high performance AZIBs.

关键词： Oxygen defects V_(2)O_(3) PEDOT Electrochemical self-optimization Aqueous zinc-ion batteries

Deep learning CNN-APSO-LSSVM hybrid fusion model for feature optimization and gas-bearing prediction

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Petroleum Science 2024年第4期21卷 2329-2344页

作者： Jiu-qiang Yang Nian-tian Lin Kai Zhang Yan Cui Chao Fu Dong Zhang College of Earth Sciences and Engineering Shandong University of Science and Technology Laboratory for Marine Mineral Resources Qingdao National Laboratory for Marine Science and Technology Transportation Institute of Inner Mongolia University Key Laboratory of Gas Hydrate Qingdao Institute of Marine Geology Ministry of Natural Resources

Conventional machine learning(CML) methods have been successfully applied for gas reservoir prediction. Their prediction accuracy largely depends on the quality of the sample data; therefore, feature optimization of the input samples is particularly important. Commonly used feature optimization methods increase the interpretability of gas reservoirs; however, their steps are cumbersome, and the selected features cannot sufficiently guide CML models to mine the intrinsic features of sample data efficiently. In contrast to CML methods, deep learning(DL) methods can directly extract the important features of targets from raw data. Therefore, this study proposes a feature optimization and gas-bearing prediction method based on a hybrid fusion model that combines a convolutional neural network(CNN)and an adaptive particle swarm optimization-least squares support vector machine(APSO-LSSVM). This model adopts an end-to-end algorithm structure to directly extract features from sensitive multicomponent seismic attributes, considerably simplifying the feature optimization. A CNN was used for feature optimization to highlight sensitive gas reservoir information. APSO-LSSVM was used to fully learn the relationship between the features extracted by the CNN to obtain the prediction results. The constructed hybrid fusion model improves gas-bearing prediction accuracy through two processes of feature optimization and intelligent prediction, giving full play to the advantages of DL and CML methods. The prediction results obtained are better than those of a single CNN model or APSO-LSSVM model. In the feature optimization process of multicomponent seismic attribute data, CNN has demonstrated better gas reservoir feature extraction capabilities than commonly used attribute optimization methods. In the prediction process, the APSO-LSSVM model can learn the gas reservoir characteristics better than the LSSVM model and has a higher prediction accuracy. The constructed CNN-APSO-LSSVM mode

关键词： Multicomponent seismic data Deep learning Adaptive particle swarm optimization Convolutional neural network Least squares support vector machine Feature optimization Gas-bearing distribution prediction

αDecay in extreme laser fields within a deformed Gamow-like model

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Nuclear Science and Techniques 2024年第2期35卷 131-144页

作者： Qiong Xiao jun-Hao Cheng Yang-Yang Xu You-tian Zou jun-Gang Deng Tong-Pu Yu Department of Physics National University of Defense TechnologyChangsha 410073China College of Science China Three Gorges UniversityYichang 443002China

In this study, the effect of extreme laser fields on the α decay process of ground-state even–even nuclei was *** the deformed Gamow-like model, we found that state-of-the-art lasers can cause a slight change in the α decay penetration probability of most nuclei. In addition, we studied the correlation between the rate of change of the α decay penetration probability and angle between the directions of the laser electric field and α particle emission for different nuclei. Based on this correlation, the average effect of extreme laser fields on the half-life of many nuclei with arbitrary α particle emission angles was calculated. The calculations show that the laser suppression and promotion effects on the α decay penetration probability of the nuclei population with completely random α particle-emission directions are not completely *** remainder led to a change in the average penetration probability of the nuclei. Furthermore, the possibility of achieving a higher average rate of change by altering the spatial shape of the laser is explored. We conclude that circularly polarized lasers may be helpful in future experiments to achieve a more significant average rate of change of the α decay half-life of the nuclei population.

关键词： αDecay Deformed Gamow-like model Half-lives Extreme laser field Penetration probability

How do the landslide and non-landslide sampling strategies impact landslide susceptibility assessment? d A catchment-scale case study from China

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第3期16卷 877-894页

作者： Zizheng Guo Bixia tian Yuhang Zhu jun He Taili Zhang School of Civil and Transportation Engineering Hebei University of TechnologyTianjin300401China Hebei Key Laboratory of Earthquake Disaster Prevention and Risk Assessment Sanhe065201China Faculty of Engineering China University of GeosciencesWuhan430074China Nanjing Center China Geological SurveyMinistry of Natural ResourcesNanjing210016China

The aim of this study is to investigate the impacts of the sampling strategy of landslide and non-landslide on the performance of landslide susceptibility assessment(LSA).The study area is the Feiyun catchment in Wenzhou City,Southeast *** types of landslides samples,combined with seven non-landslide sampling strategies,resulted in a total of 14 *** corresponding landslide susceptibility map(LSM)for each scenario was generated using the random forest *** receiver operating characteristic(ROC)curve and statistical indicators were calculated and used to assess the impact of the dataset sampling *** results showed that higher accuracies were achieved when using the landslide core as positive samples,combined with non-landslide sampling from the very low zone or buffer *** results reveal the influence of landslide and non-landslide sampling strategies on the accuracy of LSA,which provides a reference for subsequent researchers aiming to obtain a more reasonable LSM.

关键词： Landslide susceptibility Sampling strategy Machine learning Random forest China

Large reversible magnetocaloric effect in antiferromagnetic Er_(3)Si_(2)C_(2) compound

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Journal of Rare Earths 2024年第8期42卷 1555-1559,I0005页

作者： Hao Sun Lu tian Xinqiang Gao Zhaojun Mo jun Shen Baogen Shen School of Rare Earths University of Science and Technology of ChinaHefei230026China Ganjiang Innovation Academy Chinese Academy of SciencesGanzhou341000China Department of Energy and Power Engineering School of Mechanical EngineeringBeijing Institute of TechnologyBeijing100081China

The magnetic properties,magnetic phase transition and magnetocaloric effects(MCE) of Er_(3)Si_(2)C_(2) compound were investigated based on theoretical calculations and experimental *** on the first principles calculations,the antiferromagnetic(AFM) ground state type in Er_(3)Si_(2)C_(2) compound was predicted and its electronic structure was *** experimental results show that Ei_(3)Si_(2)C_(2) compound is an AFM compound with the Neel temperature(T_(N) of 7 K and undergoes a field-induced firstorder magnetic phase transition from AFM to ferromagnetic(FM) under magnetic fields exceeding 0.6 T at 2 *** magnetic transition process of Er_(3)Si_(2)C_(2) compound was investigated and *** values of the maximum magnetic entropy change(-ΔS_(M)^(max)) and the refrigeration capacity(RC) are 17 J/(kg·K)and 193 J/kg under changing magnetic fields of 0-5 T,*** a potential cryogenic magnetic refrigerant,the Er_(3)Si_(2)C_(2) compound also provides an interesting research medium to study the magnetic phase transition process.

关键词： Magnetic materials Magnetocaloric Metamagnetic transitions Magnetic phase transition Rare earths

Developing and validating a predictive model of delivering large-forgestational-age infants among women with gestational diabetes mellitus

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World Journal of Diabetes 2024年第6期15卷 1242-1253页

作者： Yi-tian Zhu Lan-Lan Xiang Ya-jun Chen tian-Ying Zhong jun-jun Wang Yu Zeng Department of Clinical Laboratory Jinling Clinical Medical College of Nanjing Medical UniversityNanjing 210002Jiangsu ProvinceChina Department of Clinical Laboratory Women’s Hospital of Nanjing Medical UniversityNanjing Women and Children’s Healthcare HospitalNanjing 210003Jiangsu ProvinceChina

BACKGROUND The birth of large-for-gestational-age(LGA)infants is associated with many shortterm adverse pregnancy *** has been observed that the proportion of LGA infants born to pregnant women with gestational diabetes mellitus(GDM)is significantly higher than that born to healthy pregnant ***,traditional methods for the diagnosis of LGA have ***,this study aims to establish a predictive model that can effectively identify women with GDM who are at risk of delivering LGA *** To develop and validate a nomogram prediction model of delivering LGA infants among pregnant women with GDM,and provide strategies for the effective prevention and timely intervention of *** The multivariable prediction model was developed by carrying out the following ***,the variables that were associated with LGA risk in pregnant women with GDM were screened by univariate analyses,for which the P value was<***,Least Absolute Shrinkage and Selection Operator regression was fit using ten cross-validations,and the optimal combination factors were se-lected by choosing lambda 1se as the *** final predictors were deter-mined by multiple backward stepwise logistic regression analysis,in which only the independent variables were associated with LGA risk,with a P value<***,a risk prediction model was established and subsequently evaluated by using area under the receiver operating characteristic curve,calibration curve and decision curve *** After using a multistep screening method,we establish a predictive *** risk factors for delivering an LGA infant were identified(P<0.01),including weight gain during pregnancy,parity,triglyceride-glucose index,free tetraiodothyronine level,abdominal circumference,alanine transaminase-aspartate aminotransferase ratio and weight at 24 gestational *** nomogram’s prediction ability was supported by the area under the curve(0.703,0.709,and 0.699 f

关键词： Large-for-gestational-age Gestational diabetes mellitus Predictive model Nomogram Triglyceride-glucose index

The Effect of Blending Ratio on the Structure and Properties of the PPR/PS In situ Fiber Reinforced System Prepared by Multi-Flow Vibration Injection Molding

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Chinese Journal of Polymer Science 2024年第6期42卷 851-863页

作者： Yan-Jiang Li Meng-Long Hu jun-Wen Zhang qiang Fu Jie Zhang College of Polymer Science and Engineering State Key Laboratory of Polymer Materials EngineeringSichuan UniversityChengdu610065China

To enhance the mechanical properties of polypropylene random copolymer(PPR),polystyrene(PS)with four different contents were added to the PPR matrix through melt ***,using the Multi-Flow Vibration Injection Molding(MFVIM)technology,PPR/PS in situ microfiber composites(MFC)with different blending ratios were *** results indicated that blending ratio had a great impact on the phase morphology and crystal structure of MFVIM samples,which was different from those of conventional injection molding(CIM)*** ultrafine fibers could be formed under the shear field and could absorb the PPR molecular chains to form hybrid shish-kebab ***,the PPR matrix could also form shish-kebab structures under the effect of strong *** the PS content reached 20%,under the combined action of PS in situ microfibers and highly oriented crystal structure,the tensile strength and Young’s modulus of the sample were obviously improved and the impact strength remained at a relatively high *** a strong and tough balanced PPR based material was *** results provide valuable insights for expanding the industrial and daily-life applications of PPR and show promising development prospects.

关键词： PPR MFVIM In situ microfibers Shearfield Hybrid shish-kebab structures