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Impact of scandium and terbium on the mechanical properties,corrosion behavior,and biocompatibility of biodegradable Mg-Zn-Zr-Mn alloys

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Journal of Magnesium and Alloys 2024年第2期12卷 546-572页

作者： Khurram Munir Jixing lin xian Tong Arne Biesiekierski Yuncang li Cuie Wen School of Engineering RMIT UniversityMelbourneVictoria 3001Australia School and Hospital of Stomatology Wenzhou Medical UniversityWenzhou 325027China

Magnesium(Mg)-based bone implants degrade rapidly in the physiological environment of the human body which affects their structural integrity and biocompatibility before adequate bone *** earth elements(REEs)have demonstrated their effectiveness in tailoring the corrosion and mechanical behavior of Mg *** study methodically investigated the impacts of scandium(Sc)and terbium(Tb)in tailoring the corrosion resistance,mechanical properties,and biocompatibility of Mg–0.5Zn–0.35Zr–0.15Mn(MZZM)alloys fabricated via casting and hot *** indicate that addition of Sc and Tb improved the strength of MZZM alloys via grain size reduction and solid solution strengthening *** extruded MZZM–(1–2)Sc–(1–2)Tb(wt.%)alloys exhibit compressive strengths within the range of 336–405 MPa,surpassing the minimum required strength of 200 MPa for bone implants by a significant *** polarization tests revealed low corrosion rates of as–cast MZZM(0.25 mm/y),MZZM–2Tb(0.45 mm/y),MZZM–1Sc–1Tb(0.18 mm/y),and MZZM–1Sc–2Tb(0.64 mm/y),and extruded MZZM(0.17 mm/y),MZZM–1Sc(0.15 mm/y),MZZM-2Sc(0.45 mm/y),MZZM-1Tb(0.17 mm/y),MZZM-2Tb(0.10 mm/y),MZZM–1Sc-1Tb(0.14 mm/y),MZZM-1Sc-2Tb(0.40 mm/y),and MZZM–2Sc–2Tb(0.51 mm/y)alloys,which were found lower compared to corrosion rate of high-purity Mg(~1.0 mm/y)reported in the ***,addition of Sc,or Tb,or Sc and Tb to MZZM alloys did not adversely affect the viability of SaOS2 cells,but enhanced their initial cell attachment,proliferation,and spreading shown via polygonal shapes and *** study emphasizes the benefits of incorporating Sc and Tb elements in MZZM alloys,as they effectively enhance corrosion resistance,mechanical properties,and biocompatibility simultaneously.

关键词： Corrosion property In vitro cytotoxicity Magnesium alloys Mechanical property Rare earth elements

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Upgrading waste NOinto amino acids via electrocatalysis on Co nanoparticles encapsulated in hollow carbon nanofibers

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Science China Chemistry 2024年

作者： Jiahui xian Kaixing Cai Peisen liao Shihan wang Guangqin li IGCME Key Laboratory of Bioinorganic and Synthetic Chemistry of Ministry of Education liFM Sun Yat-Sen University School of Chemistry

Electrocatalytic conversion of waste nitrogen oxide (NOx) into value-added nitrogenous chemicals, especially amino acid, is an emerging strategy to alleviate NOxpollution. However, this process suffers from the coexistence of multiple competitive reactions leading to complex product distribution and low efficiency, and thus the rational design and modulation of efficient catalysts remains a formidable challenge. Herein, well-designed Co nanoparticles encapsulated in hollow carbon nanofiber (CoHCNF) were constructed to promote the amino acid electrosynthesis via dealing waste NOxcoupling with biomass-derived keto acids. Ascribed to the rapid reactant diffusion, electron transport and efficient contact with abundant accessible Co catalytic sites stemmed from the unique hollow nanotubular structure, Co-HCNF manifested impressive glycine synthesis performance in one-pot adopting NO as the nitrogen source with Faradaic efficiency (FE) of 41.7%and a corresponding yield rate of 222.3μmol h-1as well as 120 h robust stability. Interestingly, it also demonstrates an excellent performance with the FE of 42.8%for NO3~– solution as the nitrogen source. Specially, this strategy displays a broad universality for the synthesis of other amino acids. This work not only highlights the importance of hollow-structuring electrocatalyst towards upgrading wasted NOxspecies into amino acids, but also promotes the further development of electrosynthetic systems for high-valued N-containing organic chemicals.

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Addressing chemoresistance with a lipid gemcitabine nanotherapeutic strategy for effective treatment of pancreatic cancer

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Nano Research 2024年第9期17卷 8377-8388页

作者： Jiawei Hong Shiyun xian Shusen Zheng Hangxiang wang Donghai Jiang The First Affiliated Hospital NHC Key Laboratory of Combined Multi-Organ TransplantationCollaborative Innovation Center for Diagnosis and Treatment of Infectious DiseasesState Key Laboratory for Diagnosis and Treatment of Infectious DiseasesSchool of MedicineZhejiang UniversityHangzhou 310003China Jinan Microecological Biomedicine Shandong Laboratory Jinan 250117China

Resistance to gemcitabine in pancreatic cancer poses a significant clinical *** investigation is warranted to assess whether nano-formulation strategy can be employed to enhance the sensitivity of resistant strains to gemcitabine *** this study,using gemcitabine-resistant pancreatic cancer cell lines,we examined the therapeutic potential of a gemcitabine nanodelivery platform and assessed the ability to overcome drug resistance against resistant *** of human equilibrative nucleoside transporter 1(hENT1)led to reduced cellular uptake of gemcitabine,resulting in chemoresistance in pancreatic *** nanoparticles circumvented the entry blockade caused by hENT1 silencing through *** entry via clathrin-mediated endocytosis increased intracellular gemcitabine accumulation in gemcitabine-resistant pancreatic cancer ***,gemcitabine nanoparticles are preferential in vivo delivery to tumor tissues,likely due to the enhanced permeability and retention *** comparison to free gemcitabine,gemcitabine nanoparticles demonstrate a more pronounced cytotoxic effect on gemcitabine-resistant pancreatic cancer cells,with favorable *** study improved the efficacy of gemcitabine through nanotechnology,providing a novel strategy to address gemcitabine-resistant pancreatic cancer.

关键词： pancreatic cancer gemcitabine resistance gemcitabine nanoparticle human equilibrative nucleoside transporter 1

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Electrically tunable phase-change metasurface for dynamic infrared thermal camouflage

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Photonics Research 2024年第2期12卷 292-300页

作者： YUFENG XIONG YUNZHENG wang CHAO FENG YAOLAN TIAN liANG GAO JUN-LEI wang ZHUANG ZHUO xian ZHAO Center for Optics Research and Engineering Key Laboratory of Laser&Infrared SystemMinistry of EducationShandong UniversityQingdao 266237China School of Information Science and Engineering Shandong UniversityQingdao 266237China

Dynamic infrared thermal camouflage technology has attracted extensive attention due to its ability to thermally conceal targets in various environmental backgrounds by tuning thermal *** use of phase change materials(PCMs)offers numerous advantages,including zero static power,rapid modulation rate,and large emissivity tuning ***,existing PCM solutions still encounter several practical application challenges,such as temperature uniformity,amorphization achievement,and adaptability to different *** this paper,we present the design of an electrically controlled metal-insulator-metal thermal emitter based on a PCM metasurface,and numerically investigate its emissivity tunability,physical mechanisms,heat conduction,and thermal camouflage performance across different ***,the influence of the quench rate on amorphization was studied to provide a guidance for evaluating and optimizing device *** results reveal that the thermal emitter exhibits a wide spectral emissivity tuning range between 8 and 14μm,considerable quench rates for achieving amorphization,and the ability to provide thermal camouflage across a wide background temperature ***,it is anticipated that this contribution will promote the development of PCM-based thermal emitters for practical dynamic infrared thermal camouflage technology with broad applications in both civilian and military domains.

关键词： thermal dynamic phase

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Main controlling factor and mechanism of gas-in-place content of the Lower Cambrian shale from different sedimentary facies in the western Hubei area, South China

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Petroleum Science 2024年第3期21卷 1488-1507页

作者： Gang li xian-Ming Xiao Bo-Wei Cheng Chen-Gang Lu Yue Feng Dong-Sheng li School of Energy Resources China University of Geosciences(Beijing)Beijing100083China Frontiers Science Center for Deep-time Digital Earth China University of Geosciences(Beijing)Beijing100083 China

The Lower Cambrian shale gas in the western Hubei area,South China has a great resource prospect,but the gas-in-place(GIP)content in different sedimentary facies varies widely,and the relevant mechanism has been not well *** the present study,two sets of the Lower Cambrian shale samples from the Wells YD4 and YD5 in the western Hubei area,representing the deep-water shelf facies and shallowwater platform facies,respectively,were investigated on the differences of pore types,pore structure and methane adsorption capacity between them,and the main controlling factor and mechanism of their methane adsorption capacities and GIP contents were *** results show that the organic matter(OM)pores in the YD4 shale samples are dominant,while the inorganic mineral(IM)pores in the YD5 shale samples are primary,with underdeveloped OM *** pore specific surface area(SSA)and pore volume(PV)of the YD4 shale samples are mainly from micropores and mesopores,respectively,while those of the YD5 shale samples are mainly from micropores and macropores,*** methane adsorption capacity of the YD4 shale samples is significantly higher than that of the YD5 shale samples,with a maximum absolute adsorption capacity of 3.13 cm^(3)/g and 1.31 cm^(3)/g in average,*** with the shallow-water platform shale,the deep-water shelf shale has a higher TOC content,a better kerogen type and more developed OM pores,which is the main mechanism for its higher adsorption *** GIP content models based on two samples with a similar TOC content selected respectively from the Wells YD4 and YD5 further indicate that the GIP content of the deep-water shelf shale is mainly 34 m^(3)/t within a depth range of 1000—4000 m,with shale gas exploration and development potential,while the shallow-water platform shale has normally a GIP content oflittle shale gas *** the geological and geochemical conditions of shale gas formation a

关键词： Lower Cambrian shale Deep-water shelf facies Shallow-waterplat form facies Pore structure Methane adsorption Gas-in-place content Controlling factor

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A multi-source information fusion layer counting method for penetration fuze based on TCN-LSTM

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Defence Technology（防务技术） 2024年第3期33卷 463-474页

作者： Yili wang Changsheng li Xiaofeng wang Nanjing University of Science and Technology Nanjing 210094JiangsuChina State Key Laboratory of Explosion Science and Technology Beijing Institute of TechnologyBeijing 100081China

When employing penetration ammunition to strike multi-story buildings,the detection methods using acceleration sensors suffer from signal aliasing,while magnetic detection methods are susceptible to interference from ferromagnetic materials,thereby posing challenges in accurately determining the number of *** address this issue,this research proposes a layer counting method for penetration fuze that incorporates multi-source information fusion,utilizing both the temporal convolutional network(TCN)and the long short-term memory(LSTM)recurrent *** leveraging the strengths of these two network structures,the method extracts temporal and high-dimensional features from the multi-source physical field during the penetration process,establishing a relationship between the multi-source physical field and the distance between the fuze and the target plate.A simulation model is developed to simulate the overload and magnetic field of a projectile penetrating multiple layers of target plates,capturing the multi-source physical field signals and their patterns during the penetration *** analysis reveals that the proposed multi-source fusion layer counting method reduces errors by 60% and 50% compared to single overload layer counting and single magnetic anomaly signal layer counting,*** model's predictive performance is evaluated under various operating conditions,including different ratios of added noise to random sample positions,penetration speeds,and spacing between target *** maximum errors in fuze penetration time predicted by the three modes are 0.08 ms,0.12 ms,and 0.16 ms,respectively,confirming the robustness of the proposed ***,the model's predictions indicate that the fitting degree for large interlayer spacings is superior to that for small interlayer spacings due to the influence of stress waves.

关键词： Penetration fuze Temporal convolutional network(TCN) Long short-term memory(LSTM) Layer counting Multi-source fusion

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FlowGANAnomaly: Flow-Based Anomaly Network Intrusion Detection with Adversarial Learning

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Chinese Journal of Electronics 2024年第1期33卷 58-71页

作者： Zeyi li Pan wang Zixuan wang School of Computer Science Nanjing University of Posts and Telecommunications School of Modern Posts Nanjing University of Posts and Telecommunications School of Internet of Things Nanjing University of Posts and Telecommunications

In recent years, low recall rates and high dependencies on data labelling have become the biggest obstacle to developing deep anomaly detection(DAD) techniques. Inspired by the success of generative adversarial networks(GANs) in detecting anomalies in computer vision and imaging, we propose an anomaly detection model called Flow GANAnomaly for detecting anomalous traffic in network intrusion detection systems(NIDS). Unlike traditional GAN-based approaches, which are composed of a flow encoder, a convolutional encoder-decoder-encoder, a flow decoder and a convolutional encoder, the architecture of this model consists of a generator(G) and a discriminator(D).Flow GANAnomaly maps the different types of traffic feature data from separate datasets to a uniform feature space,thus can capture the normality of network traffic data more accurately in an adversarial manner to mitigate the problem of the high dependence on data labeling. Moreover, instead of simply detecting the anomalies by the output of D, we proposed a new anomaly scoring method that integrates the deviation between the output of two Gs’ convolutional encoders with the output of D as weighted scores to improve the low recall rate of anomaly detection. We conducted several experiments comparing existing machine learning algorithms and existing deep learning methods(Auto Encoder and VAE) on four public datasets(NSL-KDD, CIC-IDS2017, CIC-DDo S2019, and UNSW-NB15). The evaluation results show that Flow GANAnomaly can significantly improve the performance of anomaly-based NIDS.

关键词： Deep learning Machine learning algorithms Computational modeling Network intrusion detection Imaging Telecommunication traffic Generative adversarial networks

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Electrostatically connected nanoarchitected electrocatalytic films for boosted water splitting

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Nano Research 2024年第3期17卷 1114-1122页

作者： Chao-Peng wang Hao Sun Gang Bian Jia-Xi wang Xixi Pang Guoqi wang Jian Zhu xian-He Bu School of Materials Science and Engineering National Institute for Advanced MaterialsNankai UniversityTianjin 300350China Tianjin Key Laboratory of Metal and Molecule-Based Material Chemistry Nankai UniversityTianjin 300350China Tianjin Key Laboratory for Rare Earth Materials and Applications Nankai UniversityTianjin 300350China

Active sites of two-dimensional(2D)electrocatalysts are often partially blocked owing to their inevitable stacking and hydrophobic polymeric binders in macroscale electrodes,therefore impeding their applications in efficient ***,using layered double hydroxide(LDH)nanosheets as a model 2D electrocatalyst,we demonstrate that their performance toward water splitting can be boosted when they are electrostatically assembled into an organized structure pillared by hydrophilic polyelectrolytes or nanoparticles in a layer-by-layer(LbL)*** particular,their mass activity on a planar electrode can be as large as 2.267 mA·μg^(-1) toward oxygen evolution reaction(OER),when NiFe-LDH nanosheets are electrostatically connected by poly(sodium 4-styrenesulfonate)(PSS),while drop-casted NiFe-LDH nanosheets only have a mass activity of 0.116 mA·μg^(-1).In addition,these homogeneous NiFe-LDH nanofilms can be easily deposited on three-dimensional(3D)surfaces with high areas,such as carbon cloths,to serve as practical electrodes with overpotentials of 328 mV at a current density of 100 mA·cm^(-2),and stability for 40 ***,Pt nanoparticles can be LbL assembled with NiFe-LDH as bifunctional electrodes for synergistically boosted oxygen and hydrogen evolution reactions(HER),leading to successful overall water splitting powered by a 1.5 V *** study heralds the spatial control of 2D nanomaterials in nanoscale precision as an efficient strategy for the design of advanced electrocatalysts.

关键词： layer-by-layer(LbL)assembly layered double hydroxides(LDH) two-dimensional(2D)electrocatalysts oxygen evolution reaction(OER) water splitting

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Al/Hf ratio-dependent mechanisms of microstructure and mechanical property of nearly fully dense Al—Hf reactive material

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Defence Technology（防务技术） 2024年第1期31卷 230-241页

作者： Junbao li Weibing li Xiaoming wang ZNDY of Ministerial Key Laboratory Nanjing University of Science and TechnologyNanjing 210094China

This study proposed three types of Al—Hf reactive materials with particle size ratios(a),which were almost completely dense(porosity of<5.40%)owing to their preparation using hot-pressing *** characteristics and phas... 详细信息

This study proposed three types of Al—Hf reactive materials with particle size ratios(a),which were almost completely dense(porosity oflinearly with increasing strain rate.ε.It is found that the plastic deformation of the material increased with increasing strain *** a increased from 0.1 to 1,the flow stress gradually *** failure of the material was dominated by ductile fracture with a large Al phase plastic deformation band for lower a,while brittle fracture with crushed Hf particles occurred at higher ***,a constitutive model based on BP neural network was proposed to describe the stress-strain relationships of the materials,with an average relative error of 2.22%.

关键词： Reactive material Particle size Split Hopkinson pressure bar test Stressestrain relationship Impact failure BP neural network

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Enhancing Deep Learning Soil Moisture Forecasting Models by Integrating Physics-based Models

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Advances in Atmospheric Sciences 2024年第7期41卷 1326-1341页

作者： Lu li Yongjiu DAI Zhongwang WEI Wei SHANGGUAN Nan WEI Yonggen ZHANG Qingliang li xian-xiang li School of Atmospheric Sciences Sun Yat-sen UniversityGuangzhou 510275China Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) Guangzhou 510275China Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies Guangzhou 510275China Institute of Surface-Earth System Science School of Earth System ScienceTianjin UniversityTianjin 300072China College of Computer Science and Technology Changchun Normal UniversityChangchun 130123China

Accurate soil moisture(SM)prediction is critical for understanding hydrological ***-based(PB)models exhibit large uncertainties in SM predictions arising from uncertain parameterizations and insufficient representation of land-surface *** addition to PB models,deep learning(DL)models have been widely used in SM predictions ***,few pure DL models have notably high success rates due to lacking physical ***,we developed hybrid models to effectively integrate the outputs of PB models into DL models to improve SM *** this end,we first developed a hybrid model based on the attention mechanism to take advantage of PB models at each forecast time scale(attention model).We further built an ensemble model that combined the advantages of different hybrid schemes(ensemble model).We utilized SM forecasts from the Global Forecast System to enhance the convolutional long short-term memory(ConvLSTM)model for 1–16 days of SM *** performances of the proposed hybrid models were investigated and compared with two existing hybrid *** results showed that the attention model could leverage benefits of PB models and achieved the best predictability of drought events among the different hybrid ***,the ensemble model performed best among all hybrid models at all forecast time scales and different soil *** is highlighted that the ensemble model outperformed the pure DL model over 79.5%of in situ stations for 16-day *** findings suggest that our proposed hybrid models can adequately exploit the benefits of PB model outputs to aid DL models in making SM predictions.

关键词： soil moisture forecasting hybrid model deep learning ConvLSTM attention mechanism

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