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Observing strain glass transition in Ti_(33)Nb_(15)Zr_(25)Hf_(25)O_(2)high entropy alloy with Elinvar effect

Journal of Materials Science & Technology 2024年第1期168卷 16-23页

作者： Kaichao Zhang Kai Wang Bin Wang Chao Lv Jiaxing Zheng Guanqi Li Yu Fu Wenlong Xiao Qingqing Cai Xutao Nie Yingfeng Shao Huilong Hou Xinqing Zhao School of Materials Science and engineering Beihang UniversityBeijing 100191China China Aerodynamics Research and Development Center Mianyang 621000China State Key Laboratory of Nonlinear Mechanics Chinese Academy of SciencesInstitute of MechanicsBeijing 100190China Tianmushan Laboratory(Zhejiang Provincial Laboratory for Aviation) Hangzhou 310000China

Exploring the phase transition of high entropy alloys(HEAs)with multiple major elements is of great importance for understanding the underlying physical *** martensitic phase tran-sition has been frequently reported in HEAs,however,nanoscale microstructural phase evolution has not been investigated to the same ***,we have prepared the Ti_(33)Nb_(15)Zr_(25)Hf_(25)O_(2)HEA and investi-gated the strain glass transition and its associated properties using dynamic mechanical analysis and mi-crostructure *** have found that the elastic modulus in Ti_(33)Nb_(15)Zr_(25)Hf_(25)O_(2)HEA deviates from Wachtman’s equation and observed the Elinvar effect in the form of temperature-independent mod-ulus in the temperature range from 150 K to 450 K and frequency-dependence modulus around 220 *** strain glass transition has been evidenced in Ti_(33)Nb_(15)Zr_(25)Hf_(25)O_(2)HEA by the formation and growth of nano-sized domains during in-situ transmission electron microscopy(TEM)cooling,and substantiated by the broken ergodicity during zero-field-cooling/*** strain glass transition is believed to account for the Elinvar effect,where the modulus hardening of nano-sized domains compensates dynam-ically with the modulus softening of the transformable matrix.

关键词： High entropy alloys Strain glass transition Elinvar effect Microstructural evolution Nanodomains

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Inhibiting the phase transition of WO_(3)for highly stable aqueous electrochromic battery

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Journal of Energy Chemistry 2024年第8期95卷 86-95,I0003页

作者： Zhisheng Wu Zhendong Lian Ting Ding Jielei Li Jincheng Xu Jinxiao Wang Liangxing Zhang Bo Wang Shi Chen Peng Xiao Hua Xu Shuang-Peng Wang Kar Wei Ng Joint Key Laboratory of the Ministry of Education Institute of Applied Physics and Materials EngineeringUniversity of MacaoAvenida da UniversidadeMacao 999078China School of Applied Physics and Materials Wuyi UniversityJiangmen 529020GuangdongChina Guangdong-Hong Kong-Macao Joint Laboratory for Intelligent Micro-Nano Optoelectronic Technology School of Physics and Optoelectronic EngineeringFoshan UniversityFoshan 528225GuangdongChina Guangzhou New Vision Optoelectronic Technology Co. Ltd.Guangzhou 510530GuangdongChina

Aqueous electrochromic battery(ECB)has shown intense potential for achieving energy storage and saving *** tungsten oxide(WO_(3))is the most promising EC material for commercialization,the cycling stability of WO_(3)-based aqueous ECBs is currently unsatisfactory due to the repeated phase transition during the redox process and the corrosion by acidic ***,we present a titanium-tungsten oxide alloy(Ti-WO_(3))with controllable morphology and crystal phase synthesized by a facile hot injection method to overcome the *** contrast to conventional monoclinic WO_(3),the Ti-WO_(3)nanorods can stably maintain their cubic crystal phase during the redox reaction in an acidic electrolyte,thus leading to dramatically enhanced response speed and cycling stability,Specifically,when working in a well-matched hybrid Al^(3+)/Zn^(2+)aqueous electrolyte,our phasetransition-free cubic Ti-WO_(3)exhibits an ultra-high cycling stability(>20000 cycles),fast response speed(3,95 s/4,65 s for bleaching/coloring),as well as excellent discharge areal capacity of 214.5 mA h m^(-2),We further fabricate a fully complementa ry aqueous electrochromic device,for the first time,using a Ti-WO_(3)/Prussian blue device ***,the complementary ECB shows>10000 stable operation cycles,attesting to the feasibility of our Ti-WO_(3)for practical *** work validates the significance of inhibiting the phase transitions of WO_(3)during the electrochromic process for realizing highly cyclable aqueous ECB,which can possibly provide a generalized design guidance for other high-quality metallic oxides for electrochemical applications.

关键词： Aqueous electrochromic battery Ti-WO_(3) Phase transition Long-term stability

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Insights into the provenance implication of leaf wax n-alkanes along the lower Yellow River

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Science China Earth Sciences 2024年第6期67卷 2001-2018页

作者： Liang ZHANG Jinzhao LIU Chong JIANG Fei ZHANG Zhisheng AN School of Human Settlements and Civil engineering Xi’an Jiaotong UniversityXi’an 710054China State Key Laboratory of Loess and Quaternary Geology Institute of Earth EnvironmentChinese Academy of SciencesXi’an 710061China National Observation and Research Station of Earth Critical Zone on the Loess Plateau of Shaanxi Xi’an 710061China

Serving as one of the largest rivers in terms of both sediment and organic carbon transport fluxes in the world,the Yellow River plays a crucial role in regional biogeochemical process as well as in the global carbon ***,although a large number of studies have been carried out on the flux,composition,source and seasonal variation of total particulate organic carbon in the Yellow River so far,studies on molecular biomarkers at different spatial and temporal scales are still *** this study,we focus on the molecular and hydrogen isotopic properties of leaf wax n-alkanes among different types of samples which obtained from different seasons(flood ***-flood)along the lower Yellow *** molecular distribution of n-alkanes show that the riparian topsoils are subject to inputs from the overlying vegetation,while the suspended sediments from the flood season are characterized by the mixing of soil materials which originate from various stratigraphy with different ages on the Chinese Loess *** to the contrasting hydrodynamic conditions,the n-alkanes in suspended sediments also show distinct molecular composition between flood and non-flood ***,considering the effect of climatic factors,the proportion of monocots in flood-season suspended sediments is calculated from a semi-quantitative perspective using δ^(2)H_(wax).Our findings may bring to light new considerations for the interpretation of leaf wax proxies in studies of organic matter sources of Yellow River.

关键词： Molecular distribution Hydrogen isotopic composition Leaf wax n-alkanes Suspended sediments Lower Yellow River

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Deep Learning based Efficient Edge Slicing for System Cost Minimization in Wireless Networks

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Journal of communications and Information Networks 2024年第2期9卷 162-175页

作者： Wei Jiang Daquan Feng Liping Qian Yao Sun College of Information engineering Zhejiang University of TechnologyHangzhou 310023China Shenzhen Key Laboratory of Digital Creative Technology Guangdong Province Engineering Laboratory for Digital Creative TechnologyCollege of Electronics and Information EngineeringShenzhen UniversityShenzhen 518060China James Watt School of engineering University of GlasgowG128QQScotlandUK

It is widely recognized that the future wireless networks are able to efficiently slice heterogeneous resources to provide customized services for various use cases. However, it is challenging to meet the diverse requirements of ever-growing applications, especially the stringent requirements of numerous delay-sensitive and/or computation-intensive applications. To tackle this challenge, we should not only consider user admission control to cope with resource limitations, but also make resource management more intelligent and flexible to meet diverse service needs. Taking advantages of mobile edge computing(MEC)and network slicing, in this paper, we propose deep edge slicing(DES),to jointly optimize user admission control and resource scheduling with the aim of minimizing the system cost while guaranteeing multitudinous quality-of-service (QoS) requirements. Specifically, we first apply a deep reinforcement learning approach to select the optimal set of access users with different service requests for maximizing resource *** a deep learning algorithm is employed to predict traffic data for allocating the communication and computing resources to different slices in advance. Finally, we realize the dynamic scheduling of heterogeneous resources by solving the optimization problem of minimizing the system cost. Simulation results demonstrate that DES can greatly reduce the system cost compared to other benchmarks.

关键词： deep learning mobile edge computing user admission control resource scheduling

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Image Segmentation-P300 Selector: A Brain–Computer Interface System for Target Selection

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Computers, Materials & Continua 2024年第5期79卷 2505-2522页

作者： Hang Sun Changsheng Li He Zhang Mechanical engineering Nanjing University of Science and TechnologyNanjing210018China

Brain–computer interface (BCI) systems, such as the P300 speller, enable patients to express intentions withoutnecessitating extensive ***, the complexity of operational instructions and the slow pace of characterspelling pose challenges for some patients. In this paper, an image segmentation P300 selector based on YOLOv7-mask and DeepSORT is proposed. The proposed system utilizes a camera to capture real-world objects forclassification and tracking. By applying predefined stimulation rules and object-specificmasks, the proposed systemtriggers stimuli associated with the objects displayed on the screen, inducing the generation of P300 signals in thepatient’s brain. Its video processing mechanism enables the system to identify the target the patient is focusing oneven if the object is partially obscured, overlapped, moving, or changing in number. The system alters the target’scolor display, thereby conveying the patient’s intentions to caregivers. The data analysis revealed that the selfrecognitionaccuracy of the subjects using this method was between 92% and 100%, and the cross-subject P300recognition precision was 81.9%–92.1%. This means that simple instructions such as “Do not worry, just focuson what you desire” effectively discerned the patient’s intentions using the Image Segmentation-P300 selector. Thisapproach provides cost-effective support and allows patients with communication difficulties to easily express theirneeds.

关键词： Brain-computer interface deep learning electroencephalogram P300 YOLOv7-mask

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Microphysiological systems for modeling gut-organ interaction

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BIOCELL 2024年第8期48卷 1145-1153页

作者： JONG HWAN SUNG Department of Chemical engineering Hongik UniversitySeoulKorea

The gut is a digestive organ that absorbs nutrients but also plays a vital role in immune response and defense against external *** complex interaction between the gut microbiota and other organs including the immune system of the host has been known in various contexts,yielding the notion of‘axes’between the gut and other *** the presence of various gut-organ axes has been reported,the lack of adequate in vitro model systems for studying this interaction has restricted a deeper insight into these *** developed microphysiological systems(MPS),also known as organ-on-a-chip,allow researchers to study complex interactions between diverse organs,and here we provide a review of how recently developed gut-on-a-chip systems are used for building models of various diseases that were difficult to study.

关键词： Microfluidics Gut-liver axis Gut-brain axis Microphysiological systems

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Synergistic anionic/zwitterionic mixed surfactant system with high emulsification efficiency for enhanced oil recovery in low permeability reservoirs

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Petroleum Science 2024年第2期21卷 936-950页

作者： Hai-Rong Wu Rong Tan Shi-Ping Hong Qiong Zhou Bang-Yu Liu Jia-Wei Chang Tian-Fang Luan Ning Kang Ji-Rui Hou National Key Laboratory of Petroleum Resources and engineering China University of Petroleum-BeijingBeijing102249China Unconventional Petroleum Research institute China University of Petroleum-BeijingBeijing102249China Gas Production Plant 5 of PetroChina Changqing Oilfield Company PetroChinaXi'an710000ShaanxiChina College of Petroleum engineering China University of Petroleum-BeijingBeijing102249China College of Science China University of Petroleum-BeijingBeijing102249China Kazakh-British Technical University Almaty050000Kazakhstan

Emulsification is one of the important mechanisms of surfactant flooding. To improve oil recovery for low permeability reservoirs, a highly efficient emulsification oil flooding system consisting of anionic surfactant sodium alkyl glucosyl hydroxypropyl sulfonate(APGSHS) and zwitterionic surfactant octadecyl betaine(BS-18) is proposed. The performance of APGSHS/BS-18 mixed surfactant system was evaluated in terms of interfacial tension, emulsification capability, emulsion size and distribution, wettability alteration, temperature-resistance and salt-resistance. The emulsification speed was used to evaluate the emulsification ability of surfactant systems, and the results show that mixed surfactant systems can completely emulsify the crude oil into emulsions droplets even under low energy conditions. Meanwhile,the system exhibits good temperature and salt resistance. Finally, the best oil recovery of 25.45% is achieved for low permeability core by the mixed surfactant system with a total concentration of 0.3 wt%while the molar ratio of APGSHS:BS-18 is 4:6. The current study indicates that the anionic/zwitterionic mixed surfactant system can improve the oil flooding efficiency and is potential candidate for application in low permeability reservoirs.

关键词： Anionic/zwitterionic mixed surfactant system Emulsification Synergistic effect Low permeability reservoir Enhanced oil recovery

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Unlocking efficient energy storage via regulating ion and electron-active subunits:an(SbS)_(1.15)TiS_(2)superlattice for large and fast Na^(+)storage

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Science China Chemistry 2024年第1期67卷 336-342页

作者： Baixin Peng Tianxun Cai Shaoning Zhang Yuqiang Fang Zhuoran Lv Yusha Gao Fuqiang Huang State Key Laboratory of High Performance Ceramics and Superfine Microstructure Shanghai Institute of CeramicsChinese Academy of SciencesShanghai 200050China Center of Materials Science and Optoelectronics engineering University of Chinese Academy of SciencesBeijing 100049China School of Physical Science and Technology ShanghaiTech UniversityShanghai 200031China Beijing National Laboratory for Molecular Sciences State Key Laboratory of Rare Earth Materials Chemistry and ApplicationsCollege of Chemistry and Molecular EngineeringPeking UniversityBeijing 100871China

Alloying-type metal sulfides with high sodiation activity and theoretical capacity are promising anode materials for high energy density sodium ion ***,the large volume change and the migratory and aggregation behavior of metal atoms will cause severe capacity decay during the charge/discharge ***,a robust and conductive TiS_(2)framework is integrated with a high-capacity SbS layer to construct a single phase(SbS)_(1.15)TiS_(2)superlattice for both high-capacity and fast Na^(+)*** metallic TiS_(2)sublayer with high electron activity acts as a robust and conductive skeleton to buffer the volume expansion caused by conversion and alloying reaction between Na+and SbS ***,high capacity and high rate capability can be synergistically realized in a single phase(SbS)_(1.15)TiS_(2)*** novel(SbS)_(1.15)TiS_(2)anode has a high charge capacity of 618 mAh g^(-1)at 0.2 C and superior rate performance and cycling stability(205 mAh g^(-1)at 35 C after 2,000 cycles).Furthermore,in situ and ex situ characterizations are applied to get an insight into the multi-step reaction *** integrity of robust Na-Ti-S skeleton during(dis)charge process can be *** superlattice construction idea to integrate the Na^(+)-active unit and electron-active unit would provide a new avenue for exploring high-performance anode materials for advanced sodium-ion batteries.

关键词： (SbS)_(1.15)TiS_(2) sulfides sodium ion battery superlattice fast-charging

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In situ formed Mg(BH_(4))_(2) for improving hydrolysis properties of MgH_(2)

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Journal of Magnesium and Alloys 2024年第3期12卷 1204-1214页

作者： Yongyang Zhu Mili Liu liming Zeng Yin Wang Daifeng Wu Rui Li Qing Zhou Renheng Tang Fangming Xiao institute of Resources Utilization and Rare Earth Development Guangdong Provincial Key Laboratory of Rare Earth Development and ApplicationGuangdong Academy of SciencesGuangzhou 510650China School of Materials Science and engineering Guangdong Provincial Key Laboratory of Advanced Energy Storage MaterialsSouth China University of TechnologyGuangzhou 510641China

The hydrolysis of MgH_(2) delivers high hydrogen capacity(15.2 wt%),which is very attractive for real-time hydrogen ***,the formation of a surface passivation Mg(OH)_(2) layer and the large excess of H_(2)O required to ensure complete hydrolysis are two key challenges for the MgH_(2) hydrolysis ***,a low-cost method is reported to synthesize MgH_(2)@Mg(BH_(4))_(2) composite via ball-milling MgH_(2) with cheap and widely available B_(2)O_(3)(or B(OH)_(3)).By adding small amounts of B_(2)O_(3),the in-situ formed Mg(BH_(4))_(2) could significantly promote the hydrolysis of MgH_(2).In particular,the MgH_(2)–10 wt%B_(2)O_(3) composite releases 1330.7 mL·g^(−1) H_(2)(close to 80%theoretical hydrogen generation H_(2))in H_(2)O and 1520.4 mL·g^(−1) H_(2)(about 95%)in 0.5 M MgCl_(2) in 60 min at 26℃ with hydrolysis rate of 736.9 mL·g^(−1)·min^(−1) and 960.9 mL·g^(−1)·min^(−1) H_(2) during the first minute of the hydrolysis,*** addition,the MgCl_(2) solution allows repeated use by filtering and exhibits high cycle stability(20 cycles),therefore leading to much reduced capacity loss caused by the excess H_(2)*** show that by introducing B_(2)O_(3) and recycling the 0.5 M MgCl_(2) solution,the system hydrogen capacity can approach 5.9 wt%,providing a promising hydrogen generation scheme to supply hydrogen to the fuel cells.

关键词： Hydrolysis MgH_(2) Mg(BH_(4))_(2) Hydrogen generation B_(2)O_(3) MgCl_(2)

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TSC prediction and dynamic control of BOF steelmaking with state-of-the-art machine learning and deep learning methods

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Journal of Iron and Steel Research International 2024年第1期31卷 174-194页

作者： Tian-yi Xie Cai-dong Zhang Quan-lin Zhou Zhi-qiang Tian Shuai Liu Han-jie Guo Material Technology Research institute Hesteel GroupShijiazhuang050023HebeiChina Tangsteel Company Hesteel GroupTangshan063611HebeiChina School of Artificial Intelligence Beijing Technology and Business UniversityBeijing100048China School of Metallurgical and Ecological engineering University of Science and Technology BeijingBeijing100083China

Mathematical(data-driven)models based on state-of-the-art(SOTA)machine learning and deep learning models and data collected from 12,786 heats were established to predict the values of temperature,sample,and carbon(TSC)test,including temperature of molten steel(TSC-Temp),carbon content(TSC-C)and phosphorus content(TSC-P),which made prepa-ration for eliminating the TSC *** maximize the prediction accuracy of the proposed approach,various models with different inputs were implemented and compared,and the best models were applied to the production process of a Hesteel Group steelmaking plant in China in the *** number of tabular features(hot metal information,scrap,additives,blowing practices,and preset values)was expanded,and time series(off-gas profiles and blowing practice curves)that could reflect the entire steelmaking process were introduced as ***,the latest machine learning models(LightGBM,CatBoost,TabNet,and NODE)were used to make predictions with tabular features,and the best coefficient of determination R^(2)values obtained for TSC-P,TSC-C and TSC-Temp predictions were 0.435(LightGBM),0.857(Cat-Boost)and 0.678(LightGBM),respectively,which were higher than those of classic models(backpropagation and support vector machine).Then,making predictions was performed by using SOTA time series regression models(SCINet,DLinear,Informer,and MLSTM-FCN)with original time series,SOTA image regression models(NesT,CaiT,ResNeXt,and GoogLeNet)with resized time series,and the proposed Concatenate-Model and Parallel-Model with both tabular features and time *** optimization and comparisons,it was finally determined that the Concatenate-Model with MLSTM-FCN,SCINet and Informer as feature extractors performed the best,and its R^(2)values for predicting TSC-P,TSC-C and TSC-Temp reached 0.470,0.858 and 0.710,*** field test accuracies for TSC-P,TSC-C and TSC-Temp were 0.459,0.850 and 0.685,respectively.A related importance analysis was carri

关键词： BOF steelmaking In-blow prediction TSC test Machine learning Deep learning Field application

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