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浅水湖泊溶存甲烷浓度对气温升高及季节变化响应特征

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水生态学杂志 2024年第3期45卷 1-9页

作者：马世旺袁丹妮汪洋乐静全张开瑞李思悦武汉工程大学环境生态与生物工程学院湖北武汉430205

揭示温度升高对浅水湖泊中溶存甲烷(CH_(4))浓度的影响,可为更好地应对气候变化对浅水湖泊碳排放的影响提供数据支持。采集梁子湖表层沉积物和湖水,并置于塑料水缸(沉积物厚度为10 cm,其上注入深度为1 m的湖水),设置比周围环境温度高3.... 详细信息

揭示温度升高对浅水湖泊中溶存甲烷(CH_(4))浓度的影响,可为更好地应对气候变化对浅水湖泊碳排放的影响提供数据支持。采集梁子湖表层沉积物和湖水,并置于塑料水缸(沉积物厚度为10 cm,其上注入深度为1 m的湖水),设置比周围环境温度高3.5℃的升温组(W)和不进行温度设置的控制组(C),每组6个平行,2022年1月完成系统设置后放置2个月,在春季(3、4月)和夏季(7、8月)进行样品采集并计算溶存甲烷浓度,同时测量水温(T)、pH、电导率(EC)、溶解氧(DO)、总氮(TN)、总磷(TP)、正磷(PO_(4)^(3-))、氨态氮(NH_(4)^(+))、硝态氮(NO_(3)^(-))和亚硝氮(NO_(2)^(-))、Chl-a、溶解性有机碳(DOC)等参数,并分析溶存甲烷浓度和环境因子的相关关系。结果显示,W组的甲烷浓度与C组之间差异不显著,W组的甲烷浓度总体上低于C组;夏季甲烷的浓度显著高于春季,说明温度是影响甲烷排放的重要因素;Spearman相关性分析和逐步回归分析表明溶存甲烷浓度主要与T、营养盐含量(TP、PO_(4)^(3-)、DOC)、pH、DO和EC有关,其中,季节性温度变化是影响水体溶存甲烷浓度的最主要环境因子。

关键词：溶存甲烷浓度升温季节变化浅水湖泊

Highly elastic and degradable vitrimeric elastomers using polycondensation

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Chinese Chemical Letters 2024年第3期35卷 434-438页

作者： yue liu Yongshuang Huang Chao li Guifu si Min Chen Institutes of Physical Science and Information Technology Key Laboratory of Structure and Functional Regulation of Hybrid Materials of Ministry of EducationAnhui UniversityHefei 230601China CAS Key Laboratory of Soft Matter Chemistry Department of Polymer Science and EngineeringUniversity of Science and Technology of ChinaHefei 230026China

Introducing covalently crosslinked network to polymer matrix can merge the advantages in reprocessing and durability of *** this contribution,a series of high-performance vitrimeric elastomers were achieved via *** topological structures of polymers were tuned by varying the feeding ratios of bisacetoacetate,hex–substituted bisacetoacetate,bisamine and tris(2-aminoethyl)*** these structural manipulations,the vitrimeric elastomers presented great elastic recovery properties(strain recovery value up to 80%)benefiting from the introduction of long chain ***,the elastomers exhibited excellent reprocessing property,water vapor/oxygen barrier and adhesive ***,the elastomers could be degraded into monomer under acid conditions which enabled the elastomer synthesis again in closed loop recycling *** ease of the polycondensation in this work to prepare highly elastic and recyclable vitrimeric elastomers demonstrated exciting opportunities for the synthesis of sustainable polymers.

关键词： Polycondensation Vitrimeric elastomers Highly elastic Degradable polymers

Superatom-assembled boranes,carboranes,and low-dimensional boron nanomaterials based on aromatic icosahedral B_(12)and C_(2)B_(10)

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Nano Research 2024年第7期17卷 6734-6740页

作者： Qiao-Qiao Yan Yan-Fang Wei Qiang Chen yue-Wen Mu si-Dian li Institute of Molecular Science Shanxi UniversityTaiyuan 030006China

Using the experimentally known aromatic icosahedral superatoms I_(h)B_(12)H_(12)2−and D_(5d)1,12-C_(2)B_(10)H_(12)as building blocks and based on extensive density functional theory calculations,we predict herein a series of core–shell superpolyhedral boranes and carboranes in a bottom-up approach,including the high-symmetry Th B_(12)@B_(152)H_(72)2−(2),C2h C_(2)B_(10)@B_(152)H_(72)(3),D_(3d)B_(12)@B_(144)H_(66)(4),I_(h)B_(12)@C_(24)B_(12)0H_(72)2−(6),and D_(5d)C_(2)B_(10)@C_(24)B_(12)0H_(72)(7).More interestingly,the superatom-assembled linear D2h B_(36)H_(32)^(2−)(8),close-packed planar D_(3d)B_(84)H_(60)^(2−)(10),and nearly close-packed core−shell D_(3d)B_(12)@B144H_(6)6(4)can be extended periodically to form the one-dimensional(1D)α-rhombohedral borane nanowire B_(12)H_(10)(Pmmm)(9),two-dimensional(2D)α-rhombohedral monolayer borophane B_(12)H_(6)(P m1)(11),and the experimentally known three-dimensional(3D)α-rhombohedral boron(R m)(12)which can be viewed as an assembly of the monolayer B_(12)H_(6)(11)staggered in vertical direction,setting up a bottom-up strategy to form low-dimensional boron-based nanomaterials from their borane“seeds”via partial or complete *** bonding analyses indicate that the high stability of these nanostructures originates from the spherical aromaticity of their icosahedral B_(12)or C_(2)B_(10)structural units which possess the universal skeleton electronic configuration of 1S21P61D101F8 following the Wade’s n+1 *** infrared(IR)and Raman spectra of the most-concerned neutral B_(12)@B144H_(6)6(4)and C_(2)B_(10)@C_(24)B_(12)0H_(72)(7)are computationally simulated to facilitate their experimental characterizations.

关键词： superatom-assembling bottom-up approach density functional theory superpolyhedral boranes superpolyhedral carboranes borophanes

li_(2)ZnTi_(3)O_(8)as the host–separator modifier with efficient polysulfides trapping and fast li^(+)diffusion for lithium-sulfur batteries

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Nano Research 2024年第7期17卷 6087-6094页

作者： Mao Qian Yakun Tang Lang liu yue Zhang Xiaohui li JiaJia Chen State Key Laboratory of Chemistry and Utilization of Carbon Based Energy Resources Xinjiang UniversityUrumqi 830017China State Key Laboratory of Physical Chemistry of Solid Surfaces Xiamen UniversityXiamen 361005China

The diffusion and loss of lithium polysulfides(liPSs)in lithium-sulfur batteries(LSBs)reduce the sulfur utilization rate and the catalytic conversion efficiency of sulfur species,resulting in early battery ***_(2)ZnTi_(3)O_(8)(LZTO),characterized by its stable spinel structure,exhibits high li+conductivity and holds great potential as an effective adsorbent for *** study proposes a collaborative design concept of LZTO host–separator modifier,which offers a complementary and matching approach in the cathode side,effectively addressing the challenges associated with dissolution and inadequate conversion of *** functional theory(DFT)calculation substantiates the pronounced chemical affinity of LZTO towards *** importantly,the high efficiency ion transport channels are achieved in separator coating due to the presence of the LZTO ***,the catalytic efficacy of LZTO is validated through meticulous analysis of symmetric batteries and Tafel ***,the LZTO host–separator modifier-based cell displays satisfactory rate capability(1449 and 1166 mAh·g^(−1)at 0.1 and 0.5 C)and an impressively capacity(606 mAh·g^(−1)after 500 cycles at 1 C).The coordinated strategy of host–separator modifier is supposed to have wide applications in LSBs.

关键词： li_(2)ZnTi_(3)O_(8) lithium-sulfur batteries host-separator modifier catalytic conversion diffusion and loss of liPSs

Operando measurement of lattice deformation profiles of synchrotron radiation monochromator

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Nuclear Science and Techniques 2024年第7期35卷 8-19页

作者： yue Zhang Zhong-liang li Shang-Yu si lian Xue Hong-Xin Luo Xiao-Wei Zhang Jun Hu Shanghai Synchrotron Radiation Facility Shanghai Advanced Research InstituteChinese Academy of SciencesShanghai201204China ShanghaiTech University Shanghai201210China University of the Chinese Academy of Sciences Beijing100049China Beijing Synchrotron Radiation Facility Institute of High Energy PhysicsChinese Academy of ScienceBeijing100049China

This study presents a new method for characterizing the thermal lattice deformation of a monochromator with high precision under service conditions and first reports the operando measurements of nanoscale thermal lattice deformation on a double-crystal monochromator at different incident *** nanoscale thermal lattice deformation of the monochromator first crystal was obtained by analyzing the intensity of the distorted DuMond *** diagrams of the 333 diffraction index,sensitive to lattice deformation,were obtained directly using a 2D detector and an analyzer crystal orthogonal to the *** increasing incident power and power density,the maximum height of the lattice deformation increased from 3.2 to 18.5 nm,and the deformation coefficient of the maximum height increased from 1.1 to 3.2 nm/*** maximum relative standard deviation was 4.2%,and the maximum standard deviation was 0.1 *** on the measured thermal deformations,the flux saturation phenomenon and critical point for the linear operation of the monochromator were predicted with increasing incident *** study provides a simple solution to the problem of the lower precision of synchrotron radiation monochromator characterizations compared to simulations.

关键词： Synchrotron radiation Monochromator Lattice deformation X-ray dynamic diffraction

Ultrahigh strength and uniform corrosion in Zn-li alloys through ultrahigh pressure supersaturated solid solution treatment for biodegradable orthopedic applications

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Rare Metals 2024年第10期43卷 5284-5304页

作者： Wan-Ying li Yi-Long Dai Wen-Hao Cai si-Han lin lin Guo De-Chuang Zhang Yuncang li Cuie Wen School of Materials Science and Engineering Xiangtan University Department of Prosthodontics Shanghai Ninth People′s HospitalShanghai Jiao Tong University Key Laboratory of Low Dimensional Materials&Application Technology Ministry of EducationXiangtan University School of Engineering RMIT UniversityMelbourne

Zn-li alloys are considered promising candidate materials for biodegradable orthopedic implant applications due to their high mechanical performance and good ***,the presence of a large number of second-phase particles in this class of Zn alloys can lead to severe localized degradation due to micro-galvanic corrosion,which is detrimental to the mechanical integrity of the alloys during tissue healing in the human *** this study we report ultrahigh strength,uniform corrosion,good cytocompatibility,and effective antibacterial ability in Zn-x li（x=0.3,0.5,0.7;wt%） alloys achieved through supersaturated solid solution treatment （SSST） at 375℃ under ultrahigh pressure of 3 GPa.A high concentration of β-liZn4phases coexisted with the-Zn matrix in the as-cast Zn-x li alloys,whereas almost all the li dissolved into the-Zn matrix of SSST *** yield strength was 437 MPa for SSST Zn-0.3li,592 MPa for SSST Zn-0.5 li and 686 MPa for SSST *** SSST Zn-li alloys showed uniform degradation with remarkably reduced degradation rates compared to their as-cast *** 25% concentration extracts of the Zn-x li alloys demonstrated no cytotoxicity toward MC3T3-E1 cells,and the alloys exhibited effective antibacterial ability agains methicillin-resistant staphylococcus aureus.

关键词： Corrosion behavior Mechanical property Supersaturated solid solution treatment (SSST) Ultrahigh pressure Zn-li alloy

Predicting fatigue life of automotive adhesive bonded joints:a data-driven approach using combined experimental and numerical datasets

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Advances in Manufacturing 2024年第3期12卷 522-537页

作者： Chen-Di Wei Qiu-Ren Chen Min Chen li Huang Zhong-Jie yue si-Geng li Jian Wang li Chen Chao Tong Qing liu School of Advanced Technology Xi’an Jiaotong-Liverpool UniversitySuzhou215123People’s Republic of China Key Laboratory for light-weight Materials Nanjing Tech UniversityNanjing210009People’s Republic of China Material Academy JITRISuzhou215100People’s Republic of China Nanjing University of Science and Technology Nanjing210094People’s Republic of China

The majority of vehicle structural failures originate from joint *** loading is one of the primary factors in joint failures,making the fatigue performance of joints a critical consideration in vehicle structure *** use of traditional fatigue analysis methods is constrained by the absence of adhesive life data and the wide variety of joint ***,there is a pressing need for an accurate fatigue life estimation method for the joints in the automotive *** this work,we proposed a data-driven approach embedding physical knowledge-guided parameters based on experimental data and finite element analysis(FEA)*** machine learning(ML)algorithms are adopted to investigate the fatigue life of three typical adhesive joints,namely lap shear,coach peel and KsiI *** the feature engineering and tuned process of the ML models,the preferable model using the Gaussian process regression algorithm is established,fed with eight input parameters,namely thicknesses of the substrates,line forces and bending moments of the adhesive bonded joints obtained from *** proposed method is validated with the test data set and part-level physical tests with complex loading states for an unbiased *** demonstrates that for life prediction of adhesive joints,the data-driven solutions can constitute an improvement over conventional solutions.

关键词： Fatigue life Adhesive bonded joints Finite element analysis(FEA) Machine learning(ML)

Data-driven approach to predict the fatigue properties of ferrous metal materials using the cGAN and machine-learning algorithms

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Advances in Manufacturing 2024年第3期12卷 447-464页

作者： si-Geng li Qiu-Ren Chen li Huang Min Chen Chen-Di Wei Zhong-Jie yue Ru-Xue liu Chao Tong Qing liu School of Advanced Technology Xi’an Jiaotong-Liverpool UniversitySuzhou215123JiangsuPeople’s Republic of China Key Laboratory for light-weight Materials Nanjing Tech UniversityNanjing210009People’s Republic of China Materials Bigdata and Application Division Material Academy JitriSuzhou215131JiangsuPeople’s Republic of China School of Mechanical Engineering Shanghai Jiao Tong UniversityShanghai200240People’s Republic of China

The stress-life curve(S–N)and low-cycle strain-life curve(E–N)are the two primary representations used to characterize the fatigue behavior of a *** material fatigue curves are essential for structural fatigue ***,conducting material fatigue tests is expensive and *** address the challenge of data limitations on ferrous metal materials,we propose a novel method that utilizes the Random Forest Algorithm and transfer learning to predict the S–N and E–N curves of ferrous *** addition,a data-augmentation framework is introduced using a conditional generative adversarial network(cGAN)to overcome data *** incorporating the cGAN-generated data,the accuracy(R2)of the Random Forest Algorithm-trained model is improved by 0.3–*** is proven that the cGAN can significantly enhance the prediction accuracy of the machine-learning model and balance the cost of obtaining fatigue data from the experiment.

关键词： Fatigue life curve Machine learning Transfer learning Conditional generative adversarial network(cGAN)

Predict the evolution of mechanical property of Al-li alloys in a marine environment

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Defence Technology（防务技术） 2024年第1期31卷 557-566页

作者： Wei li lin Xiang Guang Wu Hongli si Jinyan Chen Yiming Jin Yan Su Jianquan Tao Chunyang Huang State Key Laboratory of Explosion Science and Technology Beijing Institute of TechnologyBeijing100036China Chongqing Innovation Center Beijing Institute of TechnologyChongqing400044China First Research Institute of the Ministry of Public Security for PR China Beijing100036China Southwest Technology and Engineering Research Institute Chongqing400039China

The ocean is one of the essential fields of national defense in the future,and more and more attention is paid to the lightweight research of Marine equipment and *** study it is to develop a Machine learning(ML)-based prediction method to study the evolution of the mechanical properties of Al-li alloys in the marine *** obtained the mechanical properties of Al-li alloy samples under uniaxial tensile deformation at different exposure times through Marine exposure *** obtained the strain evolution by digital image correlation(DIC).The strain field images are voxelized using 2D-Convolutional Neural Networks(CNN)autoencoders as input data for Long Short-Term Memory(LSTM)neural ***,the output data of LSTM neural networks combined with corrosion features were input into the Back Propagation(BP)neural network to predict the mechanical properties of Al-li *** main conclusions are as follows:*** variation law of mechanical properties of2297-T8 in the Marine atmosphere is *** the increase in outdoor exposure test time,the tensile elastic model of 2297-T8 changes slowly,within 10%,and the tensile yield stress changes significantly,with a maximum attenuation of 23.6%.*** prediction model can predict the strain evolution and mechanical response simultaneously with an error of less than 5%.*** study shows that a CNN/LSTM system based on machine learning can be built to capture the corrosion characteristics of Marine exposure *** results show that the relationship between corrosion characteristics and mechanical response can be predicted without considering the microstructure evolution of metal materials.

关键词： Marine environment Al-li alloy Machine learning Corrosion