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In situ high-pressure nuclear magnetic resonance crystallography in one and two dimensions

Matter and Radiation at Extremes 2021年第6期6卷 94-103页

作者： Thomas Meier Alena Aslandukova Florian Trybel Dominique Laniel Takayuki Ishii Saiana Khandarkhaeva Natalia Dubrovinskaia Leonid Dubrovinsky Center for High Pressure Science and Technology Advanced Research BeijingChina Bayerisches Geoinstitut University of BayreuthBayreuthGermany Department of Physics Chemistry and Biology(IFM)Linkoping UniversitySE-58183 LinkopingSweden Material Physics and Technology at Extreme Conditions Laboratory of CrystallographyUniversity of BayreuthBayreuthGermany

Recent developments in in situ nuclear magnetic resonance(NMR)spectroscopy under extreme conditions have led to the observation of a wide variety of physical phenomena that are not accessible with standard high-pressure experimental ***,inherent di-or quadrupolar line broadening in diamond anvil cell(DAC)-based NMR experiments often limits detailed investigation of local atomic structures,especially if different phases or local environments ***,we describe our progress in the development of high-resolutionNMRexperiments in DACs using one-and two-dimensional homonuclear decoupling experiments at pressures up to the megabar *** this technique,spectral resolutions of the order of 1 ppm and below have been achieved,enabling high-pressure structural *** examples are presented that demonstrate the wide applicability of this method for extreme conditions research.

关键词： NMR extreme dimensions

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Few-layer Ti_(3)CN MXene for ultrafast photonics applications in visible band

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Journal of Materiomics 2023年第1期9卷 44-55页

作者： Zixin Yang Qi Yang Yulin Tian Xianghe Ren Chun Li Yuqian Zu Syed Zaheer Ud Din Lingfeng Gao Jian Wu Hualong Chen Han Zhang Jie Liu Jingliang He Abdullah GAl-Sehemi International School for Optoelectronic Engineering Qilu University of Technology(Shandong Academy of Sciences)Jinan250353China College of Material Chemistry and Chemical EngineeringKey Laboratory of Organosilicon Chemistry and Material TechnologyMinistry of Edu-cationHangzhou Normal UniversityHangzhou311121China College of Advanced Interdisciplinary Studies National University of Defense TechnologyChangsha410073China Institute of Microscale Optoelectronics College of Physics and Optoelectronic EngineeringShenzhen UniversityShenzhen518060China Shandong Provincial Engineering and Technical Center of Light Manipulations and Shandong Provincial Key Laboratory of Optics and Photonic Device chool of Physics and ElectronicsShandong Normal UniversityJinan250358China State Key Laboratory of Crystal Materials Shandong UniversityJinan250100China Research Center for Advanced Materials Science(RCAMS) King Khalid UniversityAbha61413Saudi Arabia Department of Chemistry College of ScienceKing Khalid UniversityAbha61413Saudi Arabia

Ti_(3)CN,as a typical hetero-MXene,has attracted tremendous attention for its unique ***,its ultrafast photonics applications are still ***,the few-layer Ti_(3)CN MXene was successfully prepared by selective etching and molecular delamination *** nonlinear optical response of few-layer Ti_(3)CN MXene at 640 nm was studied using the open-aperture Z-scan *** asprepared Ti_(3)CN MXene sample exhibited excellent nonlinear saturable absorption characteristics,resulting in the nonlinear absorption coefficient b of4.05×10^(-2)cm/GW,which was one order of magnitude larger than that of black phosphorus(BP)and molybdenum disulfide(MoS_(2)).For the optical modulation applications of few-layer Ti_(3)CN MXene,passively Q-switched(PQS)solid-state visible lasers based on Ti_(3)CN saturable absorber(SA)at 522 nm,607 nm,639 nm,and 721 nm were successfully ***,a Ti_(3)CN-based stable passively mode-locked Pr:YLF red laser was also successfully achieved with a pulse duration of 30 ps,and the corresponding repetition rate was 73.1 *** optical modulation device based on few-layer Ti_(3)CN MXene shows good *** work demonstrates that the tremendous prospects of the few-layer Ti_(3)CN MXene as a visible optical modulation device in ultrafast photonics applications.

关键词： Ti_(3)CN MXene Z-scan Saturable absorber Optical modulator Pulsed visible lasers

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An efficient and mild recycling of waste melamine formaldehyde foams by alkaline hydrolysis

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Green Energy & Environment 2024年第5期9卷 919-926页

作者： Shaodi Wu Ning Zhang Chizhou Wang Xianglin Hou Jie Zhao Shiyu Jia Jiancheng Zhao Xiaojing Cui Haibo Jin Tiansheng Deng Shanxi Engineering Research Center of Biorefinery Institute of Coal ChemistryChinese Academy of Sciences27 South Taoyuan RoadTaiyuan030001China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing100049China Department of Chemistry and Chemical Engineering Taiyuan Institute of TechnologyTaiyuanShanxi030008China Beijing Key Laboratory of Fuels Cleaning and Advanced Catalytic Emission Reduction Technology/College of New Materials and Chemical Engineering Beijing Institute of Petrochemical TechnologyBeijing102617China

Melamine formaldehyde foam(MFF)generates many poisonous chemicals through the traditional recycling methods for organic resin ***,a high MFF degradation ratio of ca.97 wt.%was achieved under the mild conditions(160℃)in a NaOH–H2O system with ammelide and ammeline as the main degradation *** alkaline solvent had an obvious corrosion effect for MFF,as indicated by scanning electron microscopy(SEM).The reaction process and products distribution were studied by Fourier-transform infrared spectroscopy(FTIR),X-ray photoelectron spectroscopy(XPS),and ^(13)C nuclear magnetic resonance(NMR).Besides,the MFF degradation products that have the similar chemical structures and bonding performances to those of melamine can be directly used as the raw material for synthesis of melamine urea-formaldehyde resins(MUFs).Moreover,the degradation system demonstrated here showed the high degradation efﬁciency after reusing for 7 *** degradation process generated few harmful pollutants and no pre-or post-treatments were required,which proves its feasibility in the safe removal or recovery of waste MFF.

关键词： Melamine formaldehyde foam Degradation Alkaline hydrolysis Recycling

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“Crossbreeding”NIR-II flavchromene for PSMA-positive prostate cancer detection and image-guided surgery

Smart Molecules

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Smart Molecules 2024年第3期2卷 102-109页

作者： Jialiang Huang Yongkang Yao Liao Zhang Chenxu Yan Zhiqian Guo State Key Laboratory of Bioreactor Engineering Key Laboratory for Advanced Materials and Joint International Research Laboratory of Precision Chemistry and Molecular EngineeringFeringa Nobel Prize Scientist Joint Research CenterInstitute of Fine ChemicalsFrontiers Science Center for Materiobiology and Dynamic ChemistrySchool of Chemistry and Molecular EngineeringEast China University of Science and TechnologyShanghaiChina

Prostate-specific membrane antigen(PSMA)is known to be overexpressed in prostate cancer(PCa).The development of precise and rapid imaging technologies to monitor PSMA is crucial for early diagnosis and *** imaging in the second near-infrared window(NIR-II)has emerged as a powerful tool for real-time tracking and in vivo visualization,offering high sensitivity and ***,there is a lack of stable,bright and easy-to-implement NIR-II fluorescent probes for PSMA ***,we presented a PSMA-targeting NIR-II fluorescent probe FC-PSMA based onπ-conjugated crossbreeding dyed strategy that affords high stability,large extinction coefficient,and good *** demonstrated,FC-PSMA displayed a high fluorescence quantum yield in fetal bovine serum(FBS).Following intravenous injection of FC-PSMA,the tumor-to-normal ratio of fluorescence intensity steadily increased over time,reaching a peak at 48 h(tumor-to-leg ratio=12.16±0.90).This advancement enables precise identification of PC through NIR-II fluorescence imaging,facili-tating high-performance guidance for prostate cancer resection surgery.

关键词： fluorescence dyes near-infrared NIR-II fluorescence imaging PSMA-targeting

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Crystal structure graph neural networks for high-performance superconducting critical temperature prediction

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science China Materials 2024年第10期67卷 3253-3261页

作者： Jingzi Zhang Chengquan Zhong Xiaoting Lu Jiakai Liu Kailong Hu Xi Lin School of Materials Science and Engineering Harbin Institute of TechnologyShenzhen 518055China Blockchain Development and Research Institute Harbin Institute of TechnologyShenzhen 518055China School of Computer Science and Technology Harbin Institute of TechnologyShenzhen 518055China State Key Laboratory of Advanced Welding and Joining Harbin Institute of TechnologyHarbin 150001China Laboratory of Environmental Sciences and Technology Xinjiang Technical Institute of Physics&ChemistryChinese Academy of SciencesUrumqi 830011China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China Sunrise(Xiamen)Photovoltaic Industry Co. Ltd.Xiamen 361006China

The utilization of machine learning methods to predict the superconducting critical temperature(T_(c))traditionally necessitates manually constructing elemental features,which challenges both the provision of meaningful chemical insights and the accuracy of *** this work,we introduced crystal structure graph neural networks to extract structure-based features for T_(c)*** results indicated that these structure-based models outperformed all previously reported models,achieving an impressive coefficient of determination(R^(2))of 0.962 and a root mean square error(RMSE)of 6.192 *** the existing Inorganic Crystal Structure Database(ICSD),our model successfully identified 76 potential high-temperature superconducting compounds with T_(c)≥77 *** these,Tl_(5)Ba_(6)Ca_(6)Cu_(9)O_(29)and TlYBa_(2)Cu_(2)O_(7)exhibit remarkably high T_(c)values of 108.4 and 101.8 K,*** work provides a perspective on the structure-property relationship for reliable T_(c)prediction.

关键词： superconductors superconducting critical temperature crystal graph network crystal structural features

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Efficient conversion of benzene and syngas to toluene and xylene over ZnO-ZrO_(2)&H-ZSM-5 bifunctional catalysts

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Chinese Journal of Chemical Engineering 2022年第5期35卷 203-210页

作者： Xiao Zhao Xuan Shi Zhongshun Chen Long Xu Chengyi Dai Yazhou Zhang Xinwen Guo Dongyuan Yang Xiaoxun Ma School of Chemical Engineering Northwest UniversityXi’an 710069China International Science&Technology Cooperation Base for Clean Utilization of Hydrocarbon Resources Chemical Engineering Research Center of the Ministry of Education for Advanced Use Technology of Shanbei EnergyCollaborative Innovation Center for Development of Energy and Chemical Industry in Northern ShaanxiNorthwest UniversityXi’an 710069China School of Chemical Engineering Dalian University of TechnologyDalian 116024China Shaanxi Key Laboratory of Energy Chemical Process Intensification School of Chemical Engineering and TechnologyXi’an Jiaotong UniversityXi’an 710049China Shanxi yanchang Petroleum(Group)Corp.LtdXi’an 710000China

A series of ZnO-ZrO_(2) solid solutions with different Zn contents were synthesized by the urea coprecipitation method,which were coupled with H-ZSM-5 zeolite to form bifunctional *** a new benzene alkylation reagent,syngas was used instead of methanol to realize the efficient conversion of syngas and benzene into toluene and xylene.A suitable ratio of ZnO-ZrO_(2) led to the significant improvement in the catalytic performance,and a suitable amount of acid helped to increase the selectivity of toluene/xylene and reduce the selectivity of the by-products ethylbenzene and C^(9+) *** highest benzene conversion of 89.2%and toluene/xylene selectivity of 88.7%were achieved over 10%ZnO-ZrO_(2)&H-ZSM-5(Si/Al=23)at a pressure of 3 MPa and a temperature of 450℃.In addition,the effect of the zeolite framework structure on product distribution was *** to the molecular dynamics of aromatic hydrocarbons,H-ZSM-5 zeolites comprise 10-membered-ring pores,which are beneficial to the activation of benzene;hence,the conversion of benzene is higher.H-ZSM-35 and HMOR zeolites exhibited small eight-membered-ring channels,which were not conducive to the passage of benzene;hence,the by-product ethylbenzene exhibits a higher *** distance between the active centers of the bifunctional catalysts was the main factor affecting the catalytic performance,and the powder mixing method was more conducive to the conversion of syngas and benzene.

关键词： ZnO-ZrO_(2) Bifunctional catalysts Aromatics Alkylation of benzene Syngas

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Open-Source Codes of Topology Optimization: A Summary for Beginners to Start Their research

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Computer Modeling in Engineering & sciences 2023年第10期137卷 1-34页

作者： Yingjun Wang Xinqing Li Kai Long Peng Wei National Engineering Research Center of Novel Equipment for Polymer Processing The Key Laboratory of Polymer Processing Engineering of the Ministry of EducationGuangdong Provincial Key Laboratory of Technique and Equipment for Macromolecular Advanced ManufacturingSouth China University of TechnologyGuangzhou510641China State Key Laboratory of Alternate Electrical Power Systemwith Renewable Energy Sources North China Electric Power UniversityBeijing102206China State Key Laboratory of Subtropical Building Science School of Civil Engineering and TransportationSouth China University of TechnologyGuangzhou510641China

Topology optimization(TO),a numerical technique to find the optimalmaterial layoutwith a given design domain,has attracted interest from researchers in the field of structural optimization in recent *** beginners,opensource codes are undoubtedly the best alternative to learning TO,which can elaborate the implementation of a method in detail and easily engage more people to employ and extend the *** this paper,we present a summary of various open-source codes and related literature on TO methods,including solid isotropic material with penalization(SIMP),evolutionary method,level set method(LSM),moving morphable components/voids(MMC/MMV)methods,multiscale topology optimization method,***,we classify the codes into five levels,fromeasy to difficult,depending on their difficulty,so that beginners can get started and understand the form of code implementation more quickly.

关键词： Topology optimization open-source code optimization methods code classification beginners

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MCAF: Multi-Headed Causal Attention Fusion Approach for Multimodal Sentiment Analysis

MCAF: Multi-Headed Causal Attention Fusion Approach for Mult...

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International Joint Conference on Neural Networks (IJCNN)

作者： Qingao Wang Xingang Wang Jinxiao Yang Yurun Bi Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Multimodal sentiment analysis(MSA) aims to synthesize multiple pieces of information, including textual, visual, and auditory information, to more accurately infer sentiment polarity. Due to the existence of complex and diverse affective causal relationships between different modalities, they interact with each other and constitute a multidimensional expression of human emotions. In the face of unbalanced data, i.e., when there are significant differences in the number of samples between different categories, the attention mechanism of the model tends to focus on spurious correlations in the training data, seriously impairing the model’s generalization ability and leading to bias, unbalanced prediction, and false correlation identification problems. To address the above problems, this study proposes a new multimodal fusion method based on the "within-sample sampling" and "cross-sample sampling" front door adjustment methods in causal inference strategies: the multi-head causal attention fusion method (MCAF). This method aims to capture potential causal relationships between different modalities through different attention heads, helping the model focus more on key causal features and avoid paying too much attention to false correlations in the training data. This helps improve the generalization performance of the model, make the decision-making process of the model more interpretable, and enhance the accuracy and robustness of the model for multimodal sentiment analysis tasks, making it more suitable for practical application scenarios.

关键词： Analytical models Sentiment analysis Visualization Correlation Neural networks Training data Predictive models

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Effect of contact forms on the wear of hard silicon surfaces by soft polymers

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Friction 2021年第5期9卷 918-928页

作者： Zhaoxiang ZHANG Xiaohong JIA Fei GUO Zhongde SHAN Yuming WANG State Key Laboratory of Tribology Tsinghua UniversityBeijing 100084China Joint Research Center for Rubber and Plastic Seals Tsinghua UniversityBeijing 100084China State Key Laboratory of Advanced Forming Technology&Equipment China Academy of Machinery Science&TechnologyBeijing 100044China

The mechanism of hard surfaces worn by soft polymers is not clearly *** this paper,a new hypothesis has been proposed,it holds that the stress acting on the hard surface under certain working conditions is the main reason for wear of the hard surface by a soft *** hypothesis was investigated by changing the contact form between *** this,friction tests between six polymer spheres and smooth,rough,and inclined monocrystalline silicon surfaces were carried *** results show that for the same tribo-pair,the silicon surface will not be worn in some contact forms,but in other contact forms it will be *** believe the wear of hard surface by a soft polymer is the result of the combined stress state action on the hard surface.

关键词： polymers silicon surface wear combined stress

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LESaET: Low-Dimensional Embedding Method for Link Prediction Combining Self-Attention and Enhanced-TuckER

LESaET: Low-Dimensional Embedding Method for Link Prediction...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Lichao Ding Jing Zhao Kai Lu Zenghao Hao Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

Knowledge graphs (KGs) provide a structured representation of the real world through entity-relation triples. However, current KGs are often incomplete, typically containing only a small fraction of all possible facts. This involves inferring missing content from existing information, a task known as link prediction. Existing methods in the field of link prediction struggle with controlling the dimensionality of embedding vectors or suffer from overly complex models. In order to tackle these challenges, we introduce a method in this paper, named Low-Dimensional Embedding Method for Link Prediction Combining Self-Attention and Enhanced-TuckER (LESaET). LESaET leverages both self-attention mechanisms and tensor factorization to learn expressive contextual-enhanced representations of KGs. Specifically, LESaET employs the multi-head self-attention mechanism of Transformer as an encoder to capture the mutual information between entities and relationships, and utilizes Enhanced-TuckER as a decoder, ultimately achieving expressive low-dimensional embeddings for link prediction tasks. LESaET demonstrates competitive performance compared to advanced methods on standard datasets.

关键词： Tensors Stacking Knowledge graphs Predictive models Transformers Vectors Decoding Standards Mutual information Periodic structures

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