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An efficient approach for the treatment of radioactive waste perfluoropolyether lubricants via a synergistic effect of thermal catalysis and immobilization

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Journal of Environmental Sciences 2024年第2期136卷 512-522页

作者： Xinhang Du Wenhua Tong Xinyu Zhou Jia Luo Yuqiu Liu Yabo Wang Panyu Li Yongkui Zhang department of Pharmaceutical&Biological engineering School of Chemical EngineeringSichuan UniversityChengdu 610065China

Perfluoropolyether(PFPE)lubricants are a kind of high-molecular polymer with many excellent properties.However,the use of PFPEs in the nuclear industry can lead to partial decomposition and carrying radionuclides,resulting in a large amount of radioactive waste PFPE lubricants annually.Moreover,radioactive waste PFPE lubricants are difficult to be effectively treated due to their high stability,the risk of possible leakage of radionuclides,and hypertoxic fluorine-containing by-products.In this study,without any precedent,a strategy of Mn O_(2)-catalyzed decomposition and Na_(2)CO_(3)-immobilized conversion was proposed for PFPE lubricant decomposition and fluorine immobilization simultaneously based on the Lewis acid-base and oxygen vacancies concept.A high fluorine conversion efficiency of 95.4%was achieved.Meanwhile,the mechanism of decomposition suggested that Mn O_(2)mainly provided Lewis acid sites and attacked the(basic)fluorine or oxygen atoms in PFPE molecules.The decomposition of PFPE chains was proceed down and volatile fluorine-containing gas was released by partial electron transfer,intramolecular disproportionation reaction,and unzipping fashion.Subsequently,gas by-products could be further oxidized and then immobilized into fluoride salts by carbonate solid absorbents.Overall,this study provides a simple,safe,and potentially practical strategy for the harmless conversion of refractory fluorinated organic wastes,especially perfluoropolymers.

关键词： Perfluoropolyether lubricants Catalyzed decomposition Fluorine-containing gas Immobilized conversion Fluoride

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Coupling metal-organic frameworks and wood-based carbon for water remediation

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Nano Research 2024年第6期17卷 5661-5669页

作者： Akhter Zia Manish Neupane Aidan McGlone Rui He Ruikun Xin Yifeng Liu Qiangu Yan Jinwu Wang Ling Li Zhiyong Cai Pei Dong Yingchao Yang department of Mechanical engineering University of MaineOronoME 04469USA department of Mechanical and Aerospace engineering University of MissouriColumbiaMO 65211USA department of Mechanical engineering George Mason UniversityFairfaxVA 22030USA department of Civil and Environmental engineering Rice UniversityHoustonTX 77005USA department of Materials Science and Nanoengineering Rice UniversityHoustonTX 77005USA forest Products Laboratory USDAMadisonWI 53726USA School of forestry Resources University of MaineOronoME 04469USA

Fresh and clean water is highly demanded throughout the world.To effectively address the need,nanomaterials enabled nanotechnology has been explored as a means of more efficient,reliable,and environmentally friendly approach towards water treatment practices.One concern in adopting nanomaterials is how to retrieve them from water body to avoid secondary contamination.In this work,the earth abundant and sustainable wood,e.g.,basswood,was selected and carbonized into porous carbon as host skeleton,and metal-organic frameworks(MOFs),e.g.,MOF-199 with extremely high surface area,were grown throughout all channels in the porous basswood carbon.Targeting the traditional organic pollutant,methyl orange(MO),the combination of MOFs and basswood carbon(MOFs@carbon)demonstrates a remarkable adsorption capacity,which is 243%and 454%higher than basswood carbon and MOF-199,respectively.Such an outstanding adsorption performance originates from that the positively charged carbon pulls MO molecules close to carbon surface,leading to a high MO molecule concentration,and then the concentration gradient drives the MO molecules to be stored inside MOFs,functioning like pockets.These findings highlight the potential application of coupled MOFs and biomass carbon in addressing water remediation.

关键词： metal-organic framework(MOF)-199 basswood carbon MOFs@carbon methyl orange

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Underwater inertial error rectification with limited acoustic observations

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Satellite Navigation 2024年第1期5卷 207-223页

作者： Hongqiong Tang Hongyang He Fangneng Li Jiangning Xu department of Navigation engineering Naval University of EngineeringWuhan430000China

Underwater inertial navigation is particularly difficult for the long-durance operations as many navigation systems such global satellite navigation systems are unavailable.The acoustic signal is a marvelous choice for underwater inertial error rectification due to its underwater penetration capability.However,the traditional Acoustic Positioning Systems(APS)are expensive and incapable of positioning with limited acoustic observations.Two novel underwater inertial error rectification algorithms with limited acoustic observations are proposed.The first one is the single acoustic-beacon Range-only Matching Aided Navigation(RMAN)method,which is inspired by matching navigation without reference maps and presented for the first time.The second is the improved single acoustic-beacon Virtual Long Baseline(VLBL)method,which considers the impact of indicated relative position increments on virtual beacon reconstruction.Both RMAN and improved VLBL are further developed when multi acoustic-beacons are available,named mAB-RMAN and mAB-VLBL.The comprehensive simulations and field investigations were conducted.The results demonstrated that the proposed methods achieved excellent accuracy and stability compared to the baseline,specifically,the mAB-RMAN and mAB-VLBL can reduce the inertial error by more than 90%and 98%when using single and double acoustic-beacons,respectively.These proposed techniques will provide new perspectives for underwater positioning,navigation,and timing.

关键词： Underwater PNT Range-only matching aided navigation Virtual long baseline Inertial error rectification

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ASLP-DL—A Novel Approach Employing Lightweight Deep Learning Framework for Optimizing Accident Severity Level Prediction

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Computers, Materials & Continua 2024年第2期78卷 2535-2555页

作者： Saba Awan Zahid Mehmood department of Software engineering University of Engineering and TechnologyTaxila47050Pakistan department of Computer engineering University of Engineering and TechnologyTaxila47050Pakistan

Highway safety researchers focus on crash injury severity,utilizing deep learning—specifically,deep neural networks(DNN),deep convolutional neural networks(D-CNN),and deep recurrent neural networks(D-RNN)—as the preferred method for modeling accident severity.Deep learning’s strength lies in handling intricate relation-ships within extensive datasets,making it popular for accident severity level(ASL)prediction and classification.Despite prior success,there is a need for an efficient system recognizing ASL in diverse road conditions.To address this,we present an innovative Accident Severity Level Prediction Deep Learning(ASLP-DL)framework,incorporating DNN,D-CNN,and D-RNN models fine-tuned through iterative hyperparameter selection with Stochastic Gradient Descent.The framework optimizes hidden layers and integrates data augmentation,Gaussian noise,and dropout regularization for improved generalization.Sensitivity and factor contribution analyses identify influential predictors.Evaluated on three diverse crash record databases—NCDB 2018–2019,UK 2015–2020,and US 2016–2021—the D-RNN model excels with an ACC score of 89.0281%,a Roc Area of 0.751,an F-estimate of 0.941,and a Kappa score of 0.0629 over the NCDB dataset.The proposed framework consistently outperforms traditional methods,existing machine learning,and deep learning techniques.

关键词： Injury severity prediction deep learning feature

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Formation adaptation in obstacle-cluttered environments via MPC-based trajectory planning

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Science China(Information Sciences) 2024年第7期67卷 321-323页

作者： Yuda CHEN Zhongkui LI department of Mechanics and engineering Science College of Engineering Peking University

Formation is a typical collective behavior in multiagent systems utilized in areas such as inspection, surveillance, and transportation. Commonly-used approaches to achieve formation include virtual structure [1], con...

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Statistical analysis and interpretation on lightning impulse breakdown voltages of ester liquids under varying field uniformity

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High Voltage 2024年第1期9卷 22-34页

作者： Haichuan Yu Qiang Liu Zhongdong Wang department of Electrical and Electronic engineering The University of ManchesterManchesterUK department of engineering University of ExeterExeterUK

Ester liquids(ELs),as the alternative transformer liquids to the conventional mineral oils(MOs),have been increasingly used in power transformers with high voltage ratings.Among various properties,the lightning impulse breakdown voltages(LIBDVs)have been studied elaborately in the past two decades under different electric field uniformities.The electric field uniformities do have an effect on the breakdown characteristics,for example,breakdown mechanisms,polarity effects,and differences of LIBDV between ELs and MOs,which is quantitatively investigated based on the LIBDVs collected from the literatures.The breakdown mechanism transition phenomenon between streamer initiation dominated breakdown and streamer propagation dominated breakdown has been reviewed firstly.Then,the transition field factor boundaries to observe the polarity effect on LIBDVs are taken at around 20 for ELs and 10 for MOs.Besides,the transition field factor boundaries to observe the LIBDV distinctions between ELs and MOs are about 109 and 14 under positive and negative lightning impulse,respectively.The systematic analysis and interpretation on the transition field factor boundaries among different phenomena can provide insights on insulation design of ELs filled power transformers.

关键词： field lightning breakdown

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An Electrical Impedance Imaging System Towards Edge Intelligence for Non-Destructive Testing of Concrete

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Tsinghua Science and Technology 2024年第3期29卷 883-896页

作者： Abolfazl Roshanpanah Mahdi Abbasi Hani Attar Ayman Amer Mohammad R.Khosravi Ahmed A.Solyman department of Electrical engineering Islamic Azad UniversityScience and Research BranceTehran ***Iran department of Computer engineering Bu-Ali Sina UniversityHamedan ***Iran department of Energy engineering Zarqa UniversityZarqa 13110Jordan department of Computer engineering Persian Gulf UniversityBushehr ***Iran department of Electrical and Electronics engineering Faculty of Engineering and ArchitectureNişantaşıUniversityIstanbul 34398Turkey

In the construction industry,to prevent accidents,non-destructive tests are necessary and cost-effective.Electrical impedance tomography is a new technology in non-invasive imaging in which the image of the inner part of conductive bodies is reconstructed by the arrays of external electrodes that are connected on the periphery of the object.The equipment is cheap,fast,and edge compatible.In this imaging method,the image of electrical conductivity distribution(or its opposite;electrical impedance)of the internal parts of the target object is reconstructed.The image reconstruction process is performed by injecting a precise electric current to the peripheral boundaries of the object,measuring the peripheral voltages induced from it and processing the collected data.In an electrical impedance tomography system,the voltages measured in the peripheral boundaries have a non-linear equation with the electrical conductivity distribution.This paper presents a cheap Electrical Impedance Tomography(EIT)instrument for detecting impurities in the concrete.A voltage-controlled current source,a micro-controller,a set of multiplexers,a set of electrodes,and a personal computer constitute the structure of the system.The conducted tests on concrete with impurities show that the designed EIT system can reveal impurities with a good accuracy in a reasonable time.

关键词： non-destructive testing system concrete electrical impedance tomography

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Tree species identity and interaction determine vertical forest structure in young planted forests measured by terrestrial laser scanning

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forest Ecosystems 2024年第3期11卷 266-275页

作者： Mengxi Wang Lander Baeten Frieke Van Coillie Kim Calders Kris Verheyen Quentin Ponette Haben Blondeel Bart Muys John Armston Hans Verbeeck Q-forestLab Department of EnvironmentFaculty of Bioscience EngineeringGhent UniversityBelgium forest&Nature Lab Department of EnvironmentFaculty of Bioscience EngineeringGhent UniversityBelgium Earth and Life Institute UniversitéCatholique de Louvain(UCLouvain)Louvain-la-NeuveBelgium department of Earth&Environmental Sciences KU LeuvenBelgium department of Geographical Sciences University of MarylandCollege ParkMDUSA

Vertical forest structure is closely linked to multiple ecosystem characteristics,such as biodiversity,habitat,and productivity.Mixing tree species in planted forests has the potential to create diverse vertical forest structures due to the different physiological and morphological traits of the composing tree species.However,the relative importance of species richness,species identity and species interactions for the variation in vertical forest structure remains unclear,mainly because traditional forest inventories do not observe vertical stand structure in detail.Terrestrial laser scanning(TLS),however,allows to study vertical forest structure in an unprecedented way.Therefore,we used TLS single scan data from 126 plots across three experimental planted forests of a largescale tree diversity experiment in Belgium to study the drivers of vertical forest structure.These plots were 9–11years old young pure and mixed forests,characterized by four levels of tree species richness ranging from monocultures to four-species mixtures,across twenty composition levels.We generated vertical plant profiles from the TLS data and derived six stand structural variables.Linear mixed models were used to test the effect of species richness on structural variables.Employing a hierarchical diversity interaction modelling framework,we further assessed species identity effect and various species interaction effects on the six stand structural variables.Our results showed that species richness did not significantly influence most of the stand structure variables,except for canopy height and foliage height diversity.Species identity on the other hand exhibited a significant impact on vertical forest structure across all sites.Species interaction effects were observed to be site-dependent due to varying site conditions and species pools,and rapidly growing tree species tend to dominate these interactions.Overall,our results highlighted the importance of considering both species identity and interaction effects in choosing suitable speci

关键词： TreeDivNet FORBIO Stand structural complexity Terrestrial laser scanning Vertical forest structure Tree diversity Planted forests

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An adaptive machine learning-based optimization method in the aerodynamic analysis of a finite wing under various cruise conditions

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Theoretical & Applied Mechanics Letters 2024年第1期14卷 27-34页

作者： Zilan Zhang Yu Ao Shaofan Li Grace X.Gu department of Mechanical engineering University of CaliforniaBerkeley 94720USA department of engineering Peking UniversityBeijing 100871China department of Civil and Environmental engineering University of CaliforniaBerkeley 94720USA

Conventional wing aerodynamic optimization processes can be time-consuming and imprecise due to the complexity of versatile flight missions.Plenty of existing literature has considered two-dimensional infinite airfoil optimization,while three-dimensional finite wing optimizations are subject to limited study because of high computational costs.Here we create an adaptive optimization methodology built upon digitized wing shape deformation and deep learning algorithms,which enable the rapid formulation of finite wing designs for specific aerodynamic performance demands under different cruise conditions.This methodology unfolds in three stages:radial basis function interpolated wing generation,collection of inputs from computational fluid dynamics simulations,and deep neural network that constructs the surrogate model for the optimal wing configuration.It has been demonstrated that the proposed methodology can significantly reduce the computational cost of numerical simulations.It also has the potential to optimize various aerial vehicles undergoing different mission environments,loading conditions,and safety requirements.

关键词： Aerodynamic optimization Computational fluid dynamics Radial basis function Finite wing Deep learning neural network

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Machine-learned wearable sensors for real-time hand-motion recognition: toward practical applications

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National Science Review 2024年第2期11卷 231-263页

作者： Kyung Rok Pyun Kangkyu Kwon Myung Jin Yoo Kyun Kyu Kim Dohyeon Gong Woon-Hong Yeo Seungyong Han Seung Hwan Ko department of Mechanical engineering Seoul National University IEN Center for Human-Centric Interfaces and engineering Institute for Electronics and NanotechnologyGeorgia Institute of Technology School of Electrical and Computer engineering Georgia Institute of Technology department of Chemical engineering Stanford University department of Mechanical engineering Ajou University George W.Woodruff School of Mechanical engineering Georgia Institute of Technology Institute of Advanced Machinery and Design(SNU-IAMD) Seoul National University

Soft electromechanical sensors have led to a new paradigm of electronic devices for novel motion-based wearable applications in our daily lives. However, the vast amount of random and unidentified signals generated by complex body motions has hindered the precise recognition and practical application of this technology. Recent advancements in artificial-intelligence technology have enabled significant strides in extracting features from massive and intricate data sets, thereby presenting a breakthrough in utilizing wearable sensors for practical applications. Beyond traditional machine-learning techniques for classifying simple gestures, advanced machine-learning algorithms have been developed to handle more complex and nuanced motion-based tasks with restricted training data sets. Machine-learning techniques have improved the ability to perceive, and thus machine-learned wearable soft sensors have enabled accurate and rapid human-gesture recognition, providing real-time feedback to users. This forms a crucial component of future wearable electronics, contributing to a robust human–machine interface. In this review, we provide a comprehensive summary covering materials, structures and machine-learning algorithms for hand-gesture recognition and possible practical applications through machine-learned wearable electromechanical sensors.

关键词： wearable sensor soft electronics artificial intelligence machine learning human–machine interfaces gesture recognition

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