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Design and fabrication of lightweight AlCrFeNiTi_(x) compositionally complex alloys with exceptional specific strength

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Rare Metals 2024年第7期43卷 3314-3328页

作者： Jun-Zhi Li Wei-Zong Bao Jie Chen Bo-Hua Yu Kun zuo Tian Gao Ze-Yun Cai Guo-Qiang Xie School of Materials Science and Engineering Harbin Institute of Technology(Shenzhen)Shenzhen 518055China State Key Laboratory of Advanced Welding and Joining Harbin Institute of TechnologyHarbin 150001China

This study focuses on compositionally complex alloys(CCAs),aiming to achieve a balance between high strength and low density for new energy and aerospace *** composition of AlCrFeNiTi_(x) CCAs is strategically guided by employing density functional theory and the theoretical design of thermodynamic *** CCAs,particularly AlCrFeNiTi_(0.25) alloy,demonstrate remarkable specific yield strength(1640.8 MPa) and 22.7% maximum *** incorporation of Ti facilitates the formation of lightweight and high-strength L2_(1)phase,contributing to the overall high specific *** effects of grain boundary strengthening,solid solution strengthening,Orowan strengthening and Peierls flow stress further enhance *** exploration of micros tructural changes during fracture reveals the role of ordered phases in suppressing crack propagation and absorbing energy within disordered phases,thereby improving the toughness and fracture resistance of *** methods and discoveries establish a robust foundation for advancing the development of novel lightweight CCAs.

关键词： Lightweight Compositionally complex alloys Specific yield strength

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Physics-informed deep learning for fringe pattern analysis

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Opto-Electronic Advances 2024年第1期7卷 4-15页

作者： Wei Yin Yuxuan Che Xinsheng Li Mingyu Li Yan Hu Shijie Feng Edmund Y.Lam Qian Chen Chao zuo Smart Computational Imaging Laboratory(SCILab) School of Electronic and Optical EngineeringNanjing University of Science and TechnologyNanjing 210094China Smart Computational Imaging Research Institute(SCIRI)of Nanjing University of Science and Technology Nanjing 210019China Jiangsu Key Laboratory of Spectral Imaging&Intelligent Sense Nanjing 210094China Department of Electrical and Electronic Engineering The University of Hong KongPokfulamHong Kong SAR 999077China

Recently,deep learning has yielded transformative success across optics and photonics,especially in optical *** neural networks (DNNs) with a fully convolutional architecture (e.g.,U-Net and its derivatives) have been widely implemented in an end-to-end manner to accomplish various optical metrology tasks,such as fringe denoising,phase unwrapping,and fringe ***,the task of training a DNN to accurately identify an image-to-image transform from massive input and output data pairs seems at best naive,as the physical laws governing the image formation or other domain expertise pertaining to the measurement have not yet been fully exploited in current deep learning *** this end,we introduce a physics-informed deep learning method for fringe pattern analysis (PI-FPA) to overcome this limit by integrating a lightweight DNN with a learning-enhanced Fourier transform profilometry (Le FTP) *** parameterizing conventional phase retrieval methods,the Le FTP module embeds the prior knowledge in the network structure and the loss function to directly provide reliable phase results for new types of samples,while circumventing the requirement of collecting a large amount of high-quality data in supervised learning *** by the initial phase from Le FTP,the phase recovery ability of the lightweight DNN is enhanced to further improve the phase accuracy at a low computational cost compared with existing end-to-end *** results demonstrate that PI-FPA enables more accurate and computationally efficient single-shot phase retrieval,exhibiting its excellent generalization to various unseen objects during *** proposed PI-FPA presents that challenging issues in optical metrology can be potentially overcome through the synergy of physics-priors-based traditional tools and data-driven learning approaches,opening new avenues to achieve fast and accurate single-shot 3D imaging.

关键词： optical metrology deep learning physics-informed neural networks fringe analysis phase retrieval

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A review on ultra-small undoped MoS_(2) as advanced catalysts for renewable fuel production

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Carbon Energy 2024年第2期6卷 92-112页

作者： Guoping Liu Lingling Ding Yuxuan Meng Ahmad Ali Guifu zuo Xianguang Meng Kun Chang Oi Lun Li Jinhua Ye Hebei Provincial Laboratory of Inorganic Nonmetallic Materials College of Materials Science and EngineeringNorth China University of Science and TechnologyTangshanChina College of Materials Science and Technology Nanjing University of Aeronautics and AstronauticsNanjingChina School of Materials Science and Engineering Pusan National UniversityBusanKorea International Center for Materials Nanoarchitectonics(WPIMANA) National Institute for Materials Science(NIMS)1-1 NamikiTsukubaIbarakiJapan

Molybdenum disulfide(MoS_(2))has garnered significant attention in the field of catalysis due to the high density of active sites in its unique two-dimensional(2D)structure,which could be developed into numerous high-performance *** synthesis of ultra-small MoS2 particles(<10 nm)is highly desired in various experimental *** ultra-small structure could often lead to a distinct S-Mo coordination state and nonstoichiometric composition in MoSx,minimizing in-plane active sites of the 2D structure and making it probable to regulate the atomic and electronic structure of its intrinsic active sites on a large extent,especially in MoSx *** article summarizes the recent progress of catalysis over ultra-small undoped MoS_(2) particles for renewable fuel *** a systematic review of their synthesis,structural,and spectral characteristics,as well as the relationship between their catalytic performance and inherent defects,we aim to provide insights into catalysis over this matrix that may potentially enable advancement in the development of high-performance MoS_(2)-based catalysts for sustainable energy generation in the future.

关键词： applications catalytic MoS_(2) structure synthesis

Effect of low-degree astigmatism on the objective visual quality

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International Journal of Ophthalmology(English edition) 2024年第6期17卷 1086-1093页

作者： Ling-Ying Ye Shu-Feng Li Jing-Jing zuo Jin Li Hui-Xiang Ma National Clinical Research Center for Ocular Diseases Eye HospitalWenzhou Medical UniversityWenzhou 325027Zhejiang ProvinceChina

AIM:To evaluate the effect of low-degree astigmatism on objective visual quality through the Optical Quality Analysis System(OQAS).METHODS:This study enrolled 46 participants(aged 23 to 30y,90 eyes)with normal or corrected-to-normal *** cylindrical lenses(0,0.5,0.75,1.0,and 1.25 D)were placed at the axial direction(180°,45°,90°,and 135°)in front of the eyes with the best correction to form 16 types of regular low-degree *** was used to detect the objective visual quality,recorded as the objective scattering index(OSI),OQAS values at contrasts of 100%,20%,and 9%predictive visual acuity(OV100%,OV20%,and OV9%),modulation transfer function cut-off(MTFcut-off)and Strehl ratio(SR).The mixed effect linear model was used to compare objective visual quality differences between groups and examine associations between astigmatic magnitude and objective visual quality ***:Apparent negative relationships between the magnitude of low astigmatism and objective visual quality were *** increase of OSI per degree of astigmatism at 180°,45°,90°,and 135°axis were 0.38(95%CI:0.35,0.42),0.50(95%CI:0.46,0.53),0.49(95%CI:0.45,0.54)and 0.37(95%CI:0.34,0.41),*** decrease of MTFcut-off per degree of astigmatism at 180°,45°,90°,and 135°axis were-10.30(95%CI:-11.43,-9.16),-12.73(95%CI:-13.62,-11.86),-12.75(95%CI:-13.79,-11.70),and-9.97(95%CI:-10.92,-9.03),*** the same astigmatism degree,OSI at 45°and 90°axis were higher than that at 0°and 135°axis,while MTFcut-off were ***:Low astigmatism of only 0.50 D can significantly reduce the objective visual quality.

关键词： low-degree astigmatism objective visual quality Optical Quality Analysis System

Surface-targeted functionalization of nickel-rich cathodes through synergistic slurry additive approach with multi-level impact using minimal quantity

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Nano Research 2024年第1期17卷 333-343页

作者： Jing Zhang Jiapei Li Longhao Cao Wenhua Cheng Ziyin Guo Xiuxia zuo Chao Wang Ya-Jun Cheng Yonggao Xia Yudai Huang State Key Laboratory of Chemistry and Utilization of Carbon Based Energy Resources College of ChemistryXinjiang UniversityUrumqi 830017China Ningbo Institute of Materials Technology&Engineering Chinese Academy of SciencesNingbo 315201China School of Materials Science and Engineering Tongji UniversityShanghai 200240China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China

LiNi0.8Co0.1Mn0.1O_(2)(NCM811),a Ni-rich layered oxide,is a promising cathode material for high-energy density lithium-ion batteries(LIBs).However,its structural instability,caused by adverse phase transitions and continuous oxygen release,as well as deteriorated interfacial stability due to excessive electrolyte oxidative decomposition,limits its widespread *** address these issues,a new concept is proposed that surface targeted precise functionalization(STPF)of the NCM811 cathode using a synergistic slurry additive(SSA)*** approach involves coating the NCM811 particle surface with 3-aminopropyl dimethoxy methyl silane(3-ADMS),followed by the precise deposition of ascorbic acid via an acid-base *** slurry additives induce the formation of an ultra-thin spinel surface layer and a stable cathode–electrolyte interface(CEI),which enhances the electrochemical kinetics and inhibits crack *** STPF strategy implemented by the SSA approach significantly improves the cyclic stability and rate performance of the NCM811 cathode in both half-cell and full-cell *** work establishes a promising strategy to enhance the structural stability and electrochemical performance of nickel-rich cathodes and provides a feasible route to promote practical applications of high-energy density lithium-ion battery technology.

关键词： nickel-rich cathode slurry additive lithium-ion battery cathode–electrolyte interface ascorbic acid phase transition

Deep Learning in Predicting Preterm Birth:A Comparative Study of Machine Learning Algorithms

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Maternal-Fetal Medicine 2024年第3期6卷 141-146页

作者： Fangchao Zhang Lingling Tong Chen Shi Rui zuo Liwei Wang Yan Wang Department of Gynecology and Obstetrics Peking University Third HospitalBeijing 100191China Department of Gynecology and Obstetrics The Fourth Hospital of ShijiazhuangShijiazhuang 050010China School of Intelligence Science and Technology Peking UniversityBeijing 100871China Information Management and Big Data Center Peking University Third HospitalBeijing 100191China National Center for Healthcare Quality Management in Obstetrics Peking University Third HospitalBeijing 100191China National Clinical Research Center for Obstetrics and Gynecology Peking University Third HospitalBeijing 100191China

Objective:To determine whether deep learning algorithms are suitable for predicting preterm ***:A retrospective study was conducted at Peking University Third Hospital from January 2018 to June *** data were divided into two parts based on the date of delivery:the first part was used for model training and validation,while real world viability was evaluated using the second *** machine learning algorithms(logistic regression,random forest,support vector machine,and transformer)were employed to predict preterm *** operating characteristic curves were plotted,and the area under the curve(AUC),sensitivity,specificity,positive predictive value(PPV),negative predictive value(NPV),and accuracy were ***:This research included data on 30,965 births,where 24,770 comprised the first part,and included 3164(12.77%)in the preterm birth group,with 6195 in the second part,including 795(12.83%)in the preterm birth *** differences in various factors were observed between the preterm and full-term birth *** transformer model(AUC=79.20%,sensitivity=73.67%,specificity=72.48%,PPV=28.21%,NPV=94.95%,and accuracy=72.61%in the test dataset)demonstrated superior performance relative to logistic regression(AUC=77.96%in the test dataset),support vectormachine(AUC=71.70%in the test dataset),and random forest(AUC=75.09%in the test dataset)***:This study highlights the promise of deep learning algorithms,specifically the transformer algorithm,for predicting pretermbirth.

关键词： Artificial intelligence Machine learning Preterm birth Transformer

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Facile synthesis of W-Mo bimetallic oxides with high adsorption properties from secondary resources

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Tungsten 2024年第4期6卷 806-820页

作者： Jia-Li Cheng Yang-Si Liu Xiao-Li Xi zuo-Ren Nie Collaborative Innovation Center of Capital Resource-Recycling Material Technology College of Materials Science and Engineering Beijing University of Technology National Engineering Laboratory for Industrial Big-Data Application Technology Beijing University of Technology Key Laboratory of Advanced Functional Materials Ministry of Education Beijing University of Technology

A simple solvothermal method was used to obtain W-Mo bimetallic oxides from W-Mo alloy scrap,and pure metal powders were also used as the raw materials to simulate *** products had a sea urchin-like structure with abundant oxygen vacancies and the products prepared at low temperatures forms a sosoloid resembling orthorhombic *** WMo bimetallic oxide prepared at the reaction temperature of 120 ℃ exhibited excellent selective adsorption performance for methylene blue（MB）,which the adsorption rate of MB reached 99% in 12 min and the adsorption rate reached 90% after6 adsorption *** the W-Mo molar ratio is 1:3,the maximum adsorption capacity of sample for MB can reach1148 mg·*** adsorption process followed the Langmuir and pseudo-second-order models,which is surface-controlled monolayer *** experimental results show the feasibility of preparing W-Mo bimetal oxide products from pure materials and *** process is simple and effective,which offered a potential approach for secondary resource recycling and reusing.

关键词： Oxygen vacancy Selective adsorption Solvothermal W–Mo alloy scrap W–Mo bimetallic oxide

An increment of diversity method for cell state trajectory inference of time-series scRNA-seq data

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Fundamental Research 2024年第4期4卷 770-776页

作者： Yan Hong Hanshuang Li Chunshen Long Pengfei Liang Jian Zhou Yongchun zuo State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock Institutes of Biomedical SciencesCollege of Life SciencesInner Mongolia UniversityHohhot010020China

The increasing emergence of the time-series single-cell RNA sequencing(scRNA-seq)data,inferring developmental trajectory by connecting transcriptome similar cell states(i.e.,cell types or clusters)has become a major *** existing computational methods are designed for individual cells and do not take into account the available time series *** present IDTI based on the Increment of Diversity for Trajectory Inference,which combines time series information and the minimum increment of diversity method to infer cell state trajectory of time-series scRNA-seq *** apply IDTI to simulated and three real diverse tissue development datasets,and compare it with six other commonly used trajectory inference methods in terms of topology similarity and branching *** results have shown that the IDTI method accurately constructs the cell state trajectory without the requirement of starting *** the performance test,we further demonstrate that IDTI has the advantages of high accuracy and strong robustness.

关键词： Increment of diversity Time-series scRNA-seq data Cell state trajectory inference Topology similarity Branching accuracy

My Hometown-Longwan Ancient Architecture Protection Documentary

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China Book International 2024年第3期 24-29页

作者： Chen zuo the Chinese Calligraphy Association the Chinese Couplet Society Luo Feng Art Association

This book records the architectural features of Longwan folk houses in the middle and late Qing *** also tells the story of the reconstruction of the village in the city of Longwan in the new *** District activates cultural heritage and excavates cultural deposits through the"Longwan mode"of"onsite protection,migration protection,and disassembly component protection"to archive the ancient buildings in Longwan and retain the"nostalgia"for the city,practicing the essence of President Xi Jinping's speech of"Enjoying the view of mountains and waters and remembering one's roots!"

关键词： mountains architectural remember