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A brief review of preparation and applications of monolithic aerogels in atmospheric environmental purification

Journal of Environmental sciences 2025年第3期149卷 209-220页

作者： Linfeng Nie Shuangde Li Mengjie Cao Ning Han Yunfa Chen State Key Laboratory of Multiphase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China Key Laboratory of Science&Technology on Particle Materials Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China

Monolithic aerogels are promising candidates for use in atmospheric environmental purification due to their structural advantages,such as fine building block size together with high specific surface area,abundant pore structure,***,monolithic aerogels possess a unique monolithic macrostructure that sets them apart from aerogel powders and nanoparticles in practical environmental clean-up *** review delves into the available synthesis strategies and atmospheric environmental applications of monolithic aerogels,covering types of monolithic aerogels including SiO_(2),graphene,metal oxides and their combinations,along with their preparation *** particular,recent developments for VOC adsorption,CO_(2)capture,catalytic oxidation of VOCs and catalytic reduction of CO_(2)are ***,challenges and future opportunities for monolithic aerogels in the atmospheric environmental purification field are *** reviewprovides valuable insights for designing and utilizing monolithic aerogel-based functional materials.

关键词： Monolithic aerogel Environmental purification Catalysis Adsorption

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Developing deep learning-based large-scale organic reaction classification model via sigma-profiles

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Green Chemical engineering 2025年第2期6卷 181-192页

作者： Wenlong Wang Chenyang Xu Jian Du Lei Zhang State Key Laboratory of Fine Chemical Frontiers Science Center for Smart Materials Oriented Chemical EngineeringInstitute of Chemical Process Systems EngineeringSchool of Chemical EngineeringDalian University of TechnologyDalian116024China Department of Chemical and Biomolecular Engineering National University of SingaporeSingapore117585Singapore

Advanced technologies like deep learning have accelerated the discovery of novel chemical reactions,especially in the field of organic *** hundreds of thousands of reactions available for reference,one way to effectively leverage them is by classifying chemical reactions into different clusters based on their specific characteristics,which makes target-guided navigation in the vast chemical space *** previous attempts that apply deep learning to reaction classification tasks have made substantial progress,developing a model with good interpretability as well as high accuracy for large-scale reaction classification tasks remains an open *** this work,a deep learning-based model for a large-scale reaction classification task is first constructed by utilizing pre-trained BERT and ***,the model is trained under the open-source dataset USPTO_TPL which contains recorded reactions of up to 1000 different *** multi-classification accuracy of the model on the testing dataset is 99.382%,showing its great potential for practical ***,a reaction similarity map is presented to correlate the reactions in the USPTO_TPL dataset based on their sigmaprofile-based statistical ***,representative reactions from the testing dataset are provided to illustrate the model's effectiveness on the reaction classification task.

关键词： Reaction classification Reaction fingerprint Sigma-profiles Deep learning

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RSscore:Reaction superiority learned from reaction mapping hypergraph

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Chinese Journal of Chemical engineering 2024年第10期74卷 203-215页

作者： Chenyang Xu Lijuan Guo Kang Zhou Hai Yu Chaoliang Wei Fengqi Fan Lei Zhang State Key Laboratory of Fine Chemicals Frontiers Science Center for Smart Materials Oriented Chemical EngineeringInstitute of Chemical Process Systems EngineeringSchool of Chemical EngineeringDalian University of TechnologyDalian 116024China PetroChina Lanzhou Lubricating Oil Research&Development Institute Lanzhou 730060China

The selection of chemical reactions is directly related to the quality of synthesis pathways,so a reasonable reaction evaluation metric plays a crucial role in the design and planning of synthesis *** reaction conditions also need to be considered in synthesis pathway design,a reaction metric that combines reaction time,temperature,and yield is required for chemical reactions of different reaction *** this study,a chemical reaction graph descriptor which includes the atom-atom mapping relationship is proposed to effectively describe ***,through pre-training using graph contrastive learning and fine-tuning through supervised learning,we establish a model for generating the probability of reaction superiority(RSscore).Finally,to validate the effectiveness of the current evaluation index,RSscore is applied in two applications,namely reaction evaluation and synthesis routes analysis,which proves that the RSscore provides an important agents-considered evaluation criterion for computer-aided synthesis planning(CASP).

关键词： Computer-aided synthesis planning Neural networks Reaction evaluation indicator Reaction graph Graph contractive learning

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Superior triethylamine-sensing properties based on SnO2 hollow nanospheres synthesized via one-step process

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Progress in Natural science:Materials International 2024年第4期34卷 682-689页

作者： Mingyue Xu Shu Yan Zia Ur Rehman Jianhua Hou Liangyun Zhai Shengjie Zhu Chuanbao Cao Wanfeng Xie Junyu Zhong Jun Yang State Key Laboratory of Bio-fibers and Eco-textiles School of Electronics and Information College of Materials Science and Engineering College of Chemistry and Chemical Engineering Qingdao University College of Environmental Science and Engineering Yangzhou University State Key Laboratory of Chemical Safety SINOPEC Research Institute of Safety Engineering Co. Ltd. National Registration Center for Chemicals Ministry of Emergency Management Research Center of Materials Science Beijing Institute of Technology State Key Laboratory of Multiphase Complex Systems Institute of Process Engineering Chinese Academy of Sciences

Due to serious harm of triethylamine（TEA） to environmental safety and human health, it is significant to synthesize gas-sensitive materials with high performance for TEA detection. However, it is still a challenge to achieve high-sensitivity detection of TEA at low temperature for a sensor synthesized through an economical and efficient method. In this work, hollow-structured SnO2（HS-SnO2） nanospheres have been fabricated by a facile, low-cost hydrothermal method in one step, which exhibit superior TEA-sensing properties, including not only ultrahigh response（127.75） for 100 ppm TEA, good selectivity, but also fast response and recovery time（17/28 s）, low detection threshold（1 ppm） and robust stability at a relatively low optimum operational temperature of 225°*** excellent gas-sensitizing performances are ascribed to porous hollow structures with rich oxygen vacancies that provide abundant active sites for raising O2adsorption and reaction of TEA and oxygen species. This work offers an effective and economical strategy for fabricating high-performance TEA sensors for industrial applications.

关键词： Hollow-structured SnO2 nanospheres TEA High response Gas sensors

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Highly efficient ozone elimination by metal doped ultra-fine Cu_(2)O nanoparticles

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Journal of Environmental sciences 2023年第12期134卷 108-116页

作者： Anqi Wang Le Zhang Jian Guan Xiaoze Wang Guojun Ma Guijun Fan Hang Wang Ning Han Yunfa Chen State Key Laboratory of Multiphase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China Key Laboratory of Science&Technology on Particle Materials Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China School of Metallurgical Engineering Xi’an University of Architecture and TechnologyXi’an 710055China

Nowadays,ozone contamination becomes dominant in air and thus challenges the research and development of cost-effective *** this study,metal doped Cu_(2)O catalysts are synthesized via reduction of Cu^(2+)by ascorbic acid in base solutions containing doping metal *** results show that compared with pure Cu_(2)O,the Mg^(2+)and Fe^(2+)dopants enhance the O_(3)removal efficiency while Ni2+depresses the *** specific,Mg-Cu_(2)O shows high O3removal efficiency of 88.4%in harsh environment of 600,000 mL/(g·hr) space velocity and 1500 ppmV O_(3),which is one of the highest in the *** and electron paramagnetic spectroscopy characterization shows higher concentration of crystal defects induced by the Mg^(2+)dopants,favoring the *** in-situ diffuse reflectance Fourier transform infrared spectroscopy shows the intermediate species in the O_(3)degradation process change from O_(2)^(2-)dominant of pure Cu_(2)O to O_(2)^(-)dominant of Mg-Cu2O,which would contribute to the high *** these results show the promising prospect of the Mg-Cu_(2)O for highly efficiency O_(3)removal.

关键词： Ozone catalyst Cu_(2)O Dopant Ultra-fine nanoparticles

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Towards atom-level understanding of metal oxide catalysts for the oxygen evolution reaction with machine learning

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npj computational Materials 2024年第1期10卷 2430-2440页

作者： Jaclyn R.Lunger Jessica Karaguesian Hoje Chun Jiayu Peng Yitong Tseo Chung Hsuan Shan Byungchan Han Yang Shao-Horn Rafael Gómez-Bombarelli Department of Materials Science and Engineering Massachusetts Institute of TechnologyCambridgeMA 02139USA Center for Computational Science and Engineering Massachusetts Institute of TechnologyCambridgeMA 02139USA Department of Chemical and Biomolecular Engineering Yonsei UniversitySeoul 03722Republic of Korea Department of Computational and Systems Biology Massachusetts Institute of TechnologyCambridgeMA 02139USA Department of Materials Science and Engineering University of TorontoTorontoON M5SCanada Department of Mechanical Engineering Massachusetts Institute of TechnologyCambridgeMA 02139USA Research Laboratory of Electronics Massachusetts Institute of TechnologyCambridgeMA 02139USA

Green hydrogen production is crucial for a sustainable future,but current catalysts for the oxygen evolution reaction(OER)suffer from slow kinetics,despite many efforts to produce optimal designs,particularly through the calculation of descriptors for *** this study,we develop a dataset of density functional theory calculations of bulk and surface perovskite oxides,and adsorption energies of OER intermediates,which includes compositions up to quaternary and facets up to(555).We demonstrate that per-site properties of perovskite oxides such as Bader charge or band center can be tuned through element substitution and faceting,and develop a machine learning model that accurately predicts these properties directly from the local chemical *** leverage these per-site properties to identify promising perovskites with high theoretical OER *** identified design principles and promising materials provide a roadmap for closing the gap between current artificial catalysts and biological enzymes such as photosystem II.

关键词： perovskite oxides kinetics

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Accurately predicting hypersonic transitional flow on cone via a symmetry approach

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Chinese Journal of Aeronautics 2023年第7期36卷 337-347页

作者： Weitao BI Kexin ZHENG Zhou WEI Zhensu SHE State Key Laboratory for Turbulence and Complex Systems and Department of Mechanics and Engineering Science College of EngineeringPeking UniversityBeijing 100871China State Key Laboratory of Aerodynamics and Computational Aerodynamics Institute China Aerodynamics Research and Development CenterMianyang 621000China

A new algebraic transition model is proposed based on a Structural Ensemble Dynamics(SED)theory of wall turbulence,for accurately predicting the hypersonic flow heat transfer on *** model defines the eddy viscosity in terms of a two-dimensional multi-regime distribution of a Stress Length(SL)function,and hence is named as *** paper presents clear evidence of precise predictions of transition onset location and peak heat flux of a wide range of hypersonic Transitional Boundary Layers(TrBL)around straight cone at zero incidence,to an unprecedented accuracy as validated by over 70 measurements for varying five crucial influential factors(Mach number,temperature ratio,cone half angle,nose Reynolds number and noise level).The results demonstrate the universality of the postulated multi-regime similarity structure,in characterizing not only the spatial non-uniform distribution of the eddy viscosity in hypersonic TrBL on cone,but also the dependence of the transition onset location on the five influential *** latter yields a novel correlation formula for transition center Reynolds number which takes similar functional form as the SL function within the symmetry *** is concluded that the SED-SL model simulates TrBL around cone with uniformly high accuracy,and then points out to an optimistic alternative way to construct hypersonic transition model.

关键词： Cones Heat flux Hypersonic boundary layers Transition flow Turbulence models

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New Janus structure photocatalyst having widely tunable electronic and optical properties with strain engineering

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Journal of Materials science & Technology 2023年第24期155卷 142-147页

作者： Sri Kasi Matta Ting Liao Salvy P Russo Center for Computational Sciences University of Tsukuba Japan ARC Centre of Excellence in Exciton Science School of Science RMIT University Melbourne 3000 Australia School of Mech. Medical & Process Engineering Queensland University of Technology Gardens Point Campus Brisbane Queensland Australia

Photoelectrochemical water splitting using solar energy,generating oxygen and hydrogen is one of the clean fuel production *** by surface-dependent characteristics of Janus structures,a newly designed Janus monolayer Silicon Phosphorous Arsenide(SiPAs)was analyzed with Density Functional Theory(DFT)*** exchange-correlation functional(HSE06)combined with Wannier90-based analysis for electronic and optical properties of SiPAs reveals that it can act as a *** show an indirect bandgap of 1.88 eV,absorbing visible light range is 350 to 500 *** phonon spectrum confirms dynamic *** exciton binding energy is computed with GW/BSE *** electronic band edge positions are at-5.75 and-4.43 eV,perfectly straddling the water redox *** the strain application modifies the bandgap and also non-homogenously widens the absorption band.A novel range of photocatalyst designs with Group IV-V elements with great promise for water-splitting,photovoltaic,and narrow bandgap semiconductor(optoelectronics)applications may be feasible.

关键词： Solar water-splitting Janus structure Density functional theory Strain engineering Optical and electronic property tuning Optoelectronic

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Dynamic apertures with diffusion-regulatory functionality in soft porous crystals:A key to solving the century puzzle on isotopologues separation

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Nano Research 2023年第2期16卷 3254-3255页

作者： Yanhong Li Jianze Xiao Yangyang Guo Ning Han Fangli Yuan Yunfa Chen Ming-Shui Yao State Key Laboratory of Multi-phase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China CAS Key Laboratory of Green Process and Engineering Institute of Process EngineeringInnovation Academy for Green ManufactureChinese Academy of SciencesBeijing 100190China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesChinese Academy of SciencesBeijing 100049China Key Laboratory of Science and Technology on Particle Materials Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China

The separation of water isotopologues has been a“century-old”challenge,also known as“the Holy Grail”in separation *** water(D2O)is a stable non-radioactive water isotopologue that plays a critical role in scientific research,military,nuclear energy,and medical *** water was first reported in 1931 when *** discovered D2 and D2O,for which he was awarded the Nobel Prize in Chemistry in *** in 1933,*** et *** 0.5μL of heavy water at a concentration of around 65.7%when electrolyzing 10 liters of *** 1935,the world's first heavy water plant was built in Norway,producing 2 tons of heavy water by electrolysis,but the separation factor was merely 1.05,which was extremely *** 1943,the first heavy water plant employing the distillation method was built in the United States.

关键词： separation porous distillation

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Multi-Scale Time Series Segmentation Network Based on Eddy Current Testing for Detecting Surface Metal Defects

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IEEE/CAA Journal of Automatica Sinica 2025年第3期12卷 528-538页

作者： Xiaorui Li Xiaojuan Ban Haoran Qiao Zhaolin Yuan Hong-Ning Dai Chao Yao Yu Guo Mohammad S.Obaidat George Q.Huang the School of Intelligence Science and Technology University of Science and Technology Beijing the Beijing Advanced Innovation Center for Materials Genome Engineering the Key Laboratory of Intelligent Bionic Unmanned Systems and the Institute of Materials Intelligent Technology Liaoning Academy of Materials IEEE the Department of Computer Science Hong Kong Baptist University the School of Computer and Communication Engineering Key Laboratory of Advanced Materials and Devices for Post-Moore Chips Ministry of Education University of Science and Technology Beijing the Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology Beijing the School of Computer and Communication Engineering University of Science and Technology Beijing the King Abdullah Ⅱ School of Information Technology The University of Jordan the Department of Computational Intelligence the School of Computing SRM University the School of Engineering The Amity University The Hong Kong Polytechnic University

In high-risk industrial environments like nuclear power plants, precise defect identification and localization are essential for maintaining production stability and safety. However, the complexity of such a harsh environment leads to significant variations in the shape and size of the defects. To address this challenge, we propose the multivariate time series segmentation network(MSSN), which adopts a multiscale convolutional network with multi-stage and depth-separable convolutions for efficient feature extraction through variable-length templates. To tackle the classification difficulty caused by structural signal variance, MSSN employs logarithmic normalization to adjust instance distributions. Furthermore, it integrates classification with smoothing loss functions to accurately identify defect segments amid similar structural and defect signal subsequences. Our algorithm evaluated on both the Mackey-Glass dataset and industrial dataset achieves over 95% localization and demonstrates the capture capability on the synthetic dataset. In a nuclear plant's heat transfer tube dataset, it captures 90% of defect instances with75% middle localization F1 score.

关键词： Eddy current testing nondestructive testing semantic segmentation time series analysis

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