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In order to satisfy the machining requirements of aero-engine casing in modern aviation industry, this paper investigates three main issues during the design and development process of a five-axis machine tool with high accuracy, stiffness and efficiency, including whole structure design, key components design, and supporting stiffness design. First, an appropriate structure of five-axis machine tool is determined considering the processing characteristics of aero-engine casing. Then, a dual drive swing head and a compact motorized spindle are designed with enough drive capability and stiffness, and related structure, assembly method, cooling technology, and performance simulation are given in detail. Next, a design method of supporting stiffness of guide is proposed through the deformation prediction of the spindle end. Based on above work, a prototype of machine tool is developed, and some experiments are carried out, including performance tests of swing head and motorized spindle, and machining of a simulated workpiece of aero-engine casing. All experimental results show that the machine tool has satisfactory accuracy, stiffness and efficiency, which meets the machining requirements of aero-engine casing. The main work can be used as references for engineers and technicians, which are meaningful in practice.

Judiciously engineering the electrocatalysts is attractive and challenging to exploit materials with high electrocatalytic performance for hydrogen evolution reaction. Herein, we successfully perform the interface engineering by alternately depositing Co-P and Ni-Fe-P films on nickel foam, via facile electroless plating and de-alloying process. This work shows that there is a significant effect of de-alloying process on alloy growth. The electronic structure of layered alloys is improved by interface engineering. The multilayer strategy significantly promotes the charge transfer. Importantly, the Co-P/Ni-Fe-P/NF electrode fabricated by interface engineering exhibits excellent electrocatalytic hydrogen evolution activity with an overpotential of 43.4 mV at 10 mA cm-2 and long-term durability for 72 h in alkaline medium (1 M KOH). The innovative strategy of this work may aid further development of commercial electrocatalysts.

Industrial assets exposed to random environment often exhibit complex deterioration mechanisms with health status variations. In actual field operation, hidden defect signals are usually crucial indicators of upcoming malfunctions and also reminders of proactive maintenance executions. Despite the extensive applications of defect-centered maintenance, in the literature, little attempt has: a) captured the impact of random environments on health variation and restoration, and b) explored the differentiated functions of maintenance windows in separate states. This article addresses these challenges by introducing a state-based maintenance policy with multifunctional maintenance windows. The impact of environmental disturbance on both defect initialization and propagation is characterized by random increment of the state transition rate as well as probabilistic malfunction risk. Three types of maintenance windows (regular, opportunistic, and postponed) are scheduled to ensure a flexible scheduling of inspection and spare part resources. Importantly, the function of opportunistic window is state-based, defect identification when normal and removal when defective. The objective is to minimize the cost rate via the joint optimization of inspection interval, postponed interval, and opportunistic threshold. Experimental studies demonstrate the superior performance of this policy over some conventional policies.

Based on the precise logical analysis method, the paper constructs a comprehensive evaluation model of transportation superiority in terms of transportation network density, the influence of transportation arteries, and regional location-specific advantages, then select Southwest China as a case to evaluate the transportation superiority and analyze the correlations of transportation with regional economic development and population distribution. The results show that there is a positive correlation between regional transportation superiority and regional population density as well as GDP per capita in the spatial distribution. Finally, by using the fuzzy logic analysis method, we propose countermeasures and suggestions for the impact of transportation integration on regional economic development and population distribution.

Excellent catalysts with low-temperature activity and relatively wide temperature window for selective catalytic reduction of NO with ammonia (NH3-SCR) are highly demanded in view of the practical treatment of NO. Herein, we have designed a highly active VOx-MnOx/CeO2 material based on the intrinsic requirement of SCR reaction for catalyst, namely redox sites and surface acid sites. The vanadium oxide and manganese oxide are highly dispersed over the ceria mesosphere via simple incipient wetness impregnation. The loading of manganese could introduce acid sites and enhance the redox property remarkably, while the loading of vanadium increases acid sites and weakens redox property. Through tentatively controlling the appropriate loading ratio of the two components, the optimal catalyst achieves a balance between redox property and surface acidity. The work shed light on the development of new SCR catalyst with superior low temperature activity, wide work temperature window and good hydrothermal stability.

Small molecule(SM) drugs can affect the expression of miRNAs, which plays crucial roles in many important biological processes. The chemical structure and clinical information of small molecule can simultaneously incorporate information such as anatomical distribution, therapeutic effects and structural characteristics. It is necessary to develop a novel model that incorporates small molecule chemical structure and clinical information to reveal the unknown small molecule-miRNA associations. In this study, we developed a new framework based on non-negative matrix factorization, called SMANMF, to discover the potential small molecules-miRNAs associations. First, the functional similarity of two miRNAs can be obtained by computing the overlap of the target gene sets in which the miRNAs interact together, and we integrated two types of small molecule similarities, including chemical similarity and clinical similarity. Then, we utilized a non-negative matrix factorization model to discover the unknown relationship between small molecules and miRNAs. The evaluation results indicate that our model can achieve superior prediction performance compared with previous approaches in 5-fold cross-validation. At the same time, the results of case studies also reveal that the SMANMF model has good predictive performance for predicting the potential association between small molecules and miRNAs.

We study thetruthful facility assignmentproblem, where a set of agents with private most-preferred points on a metric space have to be assigned to facilities that lie on the metric space, under capacity constraints on the facilities. The goal is to produce such an assignment that minimizes the social cost, i.e., the total distance between the most-preferred points of the agents and their corresponding facilities in the assignment, under the constraint of truthfulness, which ensures that agents do not misreport their most-preferred points. We propose aresource augmentation framework, where a truthful mechanism is evaluated by its worst-case performance on an instance with enhanced facility capacities against the optimal mechanism on the same instance with the original capacities. We study a well-known mechanism, Serial Dictatorship, and provide an exact analysis of its performance. Among other results, we prove that Serial Dictatorship has approximation ratio$$g/(g-2)$$g/(g-2)when the capacities are multiplied by any integer$$g \ge 3$$g≥3. Our results suggest that with a limited augmentation of the resources we can achieve exponential improvements on the performance of the mechanism and in particular, the approximation ratio goes to 1 as the augmentation factor becomes large. We complement our results with bounds on the approximation ratio of Random Serial Dictatorship, the randomized version of Serial Dictatorship, when there is no resource augmentation.

Conversion and alloy-type anode materials suffer from large volume expansion during lithiation process, which causes the destruction of intact electrode structure and loss of efficient electrical contact between current collector and particles of anode material, resulting in fast capacity decay and poor cycling stability. Herein, a combined slurry-casting and heat-treatment approach has been adopted to prepare highly stable integrated anode composed of anode materials particles and all-carbon binder consisting of commercial carbon nanotubes (CNTs) and polyvinylidene fluoride (PVDF) derived carbon. This all-carbon binder shows a strong cohesive ability to copper current collector compared with traditional PVDF binder, and could effectively bind anode material particles and current collector. Moreover, CNTs reinforced all-carbon binder provides a robust mechanical and high conductive network to ensure structural stability of integrated anode, in which volume expansion of anode materials could be effectively suppressed during lithiation process. The integrated electrode with tin dioxide and silicon as active materials exhibits remarkable long-term cycling stability, maintaining 861.4 mA h g−1 after 500 cycles and 902.4 mA h g−1 after 300 cycles at 0.5C, respectively. This simple yet effective strategy is compatible with the traditional anode manufacture process, demonstrating its great potential in the practical use.

Discrete element method (DEM) is an effective approach to investigate non-spherical granular systems that are widely encountered in nature, industry, and our daily life. To describe the complex shapes of non-spherical particles, different particle shape representation approaches have been developed. In this paper, comparative study of modeling tablets using multi-sphere approach, multi-super-ellipsoid approach, and polyhedron approach is done to investigate the effect of different approaches. The accuracy of these approaches is testified by experiments and corresponding simulations of the packing, heap forming, and the flow in a rotating drum with two kinds of biconvex tablets firstly. Then the simulations of the flow of two kinds of biconvex tablets in a horizontal rotating drum are carried out by DEM. The simulation results are compared to discuss the effect of different approaches, which include the repose angle, the tablet orientation, the axial movement and mixing, the contact number, the percentage of the tablets reaching the free surface of the granular bed, and the computational efficiency. The results show that the simulations using multi-super-ellipsoid approach and polyhedron approach have some differences with those using multi-sphere approach.

The TiO2-Ag hybrid nanofluids were prepared by diluting high-concentration nanofluids and adding Span80 as surfactants. The stability of nanofluids was studied by taking photos of the nanofluids with storage time of 0–30 days. The thermal conductivity and dynamic viscosity were measured at different volume fraction, temperature and ultrasonication time. The results showed that compared with the base fluid, the maximum enhancement of thermal conductivity was 9.98%, and the maximum dynamic viscosity ratio was 2.78. And ultrasonication treatment is recommended to alleviate the sedimentation of nanofluids. Then, two artificial neural networks (ANNs) were established and the size of the networks was optimized according to the relative error to improve the ability to predict the thermal properties of nanofluids. The results show that the maximum relative error of the prediction of thermal conductivity and dynamic viscosity is 1.44% and 3.54%, respectively, which is beneficial to saving experiment time and cost.

Layered Ni-rich LiNixMnyCo1-x-yO2 (NMC) materials are the most promising cathode materials for Li-ion batteries due to their favorable energy densities. However, the low thermal stability typically caused by detrimental oxygen release leads to significant safety concerns. Determining the pathways of oxygen evolution reaction is essential, as the ideal safety countermeasure is to break the reaction chain of thermal runaway. In this study, we demonstrate that two endogenous pathways of oxygen involved in strong exothermic reactions lead the NMC811|graphite pouch cell to an uncontrollable state, and we quantify the individual contribution of the pathways to thermal runaway. Approximately 41% of thermal-induced oxygen reacts aggressively with ethylene carbonate (EC) at the cathode/electrolyte interface with 16% heat generation, accelerating the self-heating rate and thereby further triggering thermal runaway. The residual oxygen that survives the reaction with carbonate spreads to the lithiated anode with major heat generation (65%), bringing the battery to the maximum destructive temperature during thermal runaway. By confirming the significant roles of EC and anode, a deeper understanding on battery fire was achieved. The revealed mechanism can help guide studies on stopping the two reaction pathways, allowing for the safer use of high-energy lithium-ion batteries in the future.

Purpose The purpose of this paper is to determine the corrosion fatigue behavior and mechanism of 6005A aluminum alloy and welded joint. Design/methodology/approach Electron back-scattered diffraction (EBSD) were adopted to characterize the microstructure of 6005A aluminum alloy and welded joint. Through potentiodynamic polarization, electrochemical impedance spectroscopy (EIS) and corrosion fatigue experiments, the corrosion fatigue behavior and mechanism of 6005A aluminum alloy base metal and welded joint were studied. Findings The results show that the corrosion fatigue crack initiation of 6005A aluminum alloy base metal and welded joint is mainly caused by the preferential anodic dissolution and hydrogen concentration in the areas with inclusions and welding defects. Originality/value The research is an originality study on the corrosion fatigue behavior and mechanism of 6005A aluminum alloy and welded joint.

Air traffic administration requires evidence when promoting new technology or a new concept of operation. Therefore, when decision support tools are applied, it is necessary to analyze the costs and benefits quantitatively. This paper focuses on the evaluation of Key Performance Indicators (KPIs) correlated with the improvement of arrival operations after the implementation of the Arrival Management (AMAN) system and Wake Turbulence Re-categorization in China (RECAT-CN). Firstly, we give an overview of the implementation of the AMAN system and RECAT in China. Secondly, the KPIs related to the arrival operation are established according to the characteristics of AMAN and RECAT-CN, based on the existing KPI systems in the field of Air Traffic Management (ATM). The proposed KPIs are: airport acceptance rate; final approach interval; flight time within the terminal area (TMA); and taxi-in time. Thirdly, arrival operation within the TMA around Guangzhou International Airport is used as an example to carry out the quantitative analysis. The region and time range were defined for the performance comparison, and external factors were also examined. Finally, using descriptive and inferential statistics, the proposed KPIs’ comparison results are presented and visualized. Such results indicate a significant improvement in arrival operation with the AMAN system and RECAT-CN at Guangzhou International Airport.

In this study, the continuum-discontinuum element method (CDEM) was used to investigate the tensile fracture mechanism of rock materials. An isotropic rock disk model and models considering different foliation inclinations were established, and three schemes were used to simulate the rock fracturing in Brazilian test. Then, the influences of the rock matrix and foliation strengths on anisotropy rock fracturing were investigated. Furtherly, simulation results were verified, and the rock fracture mechanisms were discussed. The results show that the rock fracturing in Brazilian test can be accurately simulated by CDEM, which is in accordance with the experimental results. For isotropic and horizontal foliation rock, the stress concentration in loading positions causes a local fracture of rock sample, and application of a local strengthening scheme can simulate the integral tension fracture of sample middle. As the foliation angle varies from 15° to 45°, the rock fracturing is affected by the stress concentration and foliation distribution. In splitting simulation, a strengthening scheme should be adopted to overcome this influence. As a result, the rock sample generates the sliding and compression-shear fracture. As the foliation angle changes from 45° to 75°, the foliation, rather than the matrix, dominates the fracture behavior of rock sample. For vertical foliations’ rock, as the middle foliation thickness is appropriately broadened, the simulation results are reasonable. In general, the tensile strength of anisotropic rock entirely decreases with an increase of foliation angle, and the effect of foliation strength on the tensile strength rock sample is larger than that of the rock matrix.

Self-assembly of colloidal nanoparticles (NPs) into well-defined superstructures has been recognized as one of the most promising ways to fabricate rationally-designed functional materials for a variety of applications. Introducing hierarchical mesoporosity into NP superstructures will facilitate mass transport while simultaneously enhancing the accessibility of constituent NPs, which is of critical importance for widening their applications in catalysis and energy-related fields. Herein, we develop a colloidal co-assembly strategy to construct mesostructured, carbon-coated Co0.5Fe2.5O4 NP superstructures (M-C@CFOSs), which show great promise as highly efficient electrocatalysts for the oxygen evolution reaction (OER). Specifically, organically-stabilized SiO2 NPs are employed as both building blocks and sacrificial template, which co-assemble with Co0.5Fe2.5O4 NPs to afford binary NP superstructures through a solvent drying process. M-C@CFOSs are obtainable after in situ ligand carbonization followed by the selective removal of SiO2 NPs. The hierarchical mesoporous structure of M-C@CFOSs, combined with the conformal graphitic carbon coating derived from the native organic ligands, significantly improves their electrocatalytic performance as OER electrocatalysts when compared with nonporous Co0.5Fe2.5O4 NP superstructures. This work establishes a new and facile approach for designing NP superstructures with hierarchical mesoporosity, which may find wide applications in energy storage and conversion.

Despite being difficult to identify, extremely dilute oxygen vacancies have been widely reported to play an important role in enhancing magnetism in ZnFe2O4. The mechanisms underlying this enhanced magnetism have not been well understood for a long time and remain controversial because the formation of oxygen vacancy-rich ZnFe2O4 can be accompanied by changes in the chemical/physical characteristics, especially the composition, particle size, surface morphology and cation distribution, which can significantly affect the magnetization. An open and important question is whether and to what extent the enhanced magnetization can be attributed only to oxygen vacancies. In this study, the relationship between the magnetization and oxygen vacancies in ZnFe2O4 was definitively determined by using a carefully designed “shake-and-heat” treatment to prepare vacancy-rich samples while keeping the other crystal/surface parameters constant. Compared to the nearly vacancy-free paramagnetism samples, the vacancy-rich samples exhibited a higher magnetization of approximately 5 emu/g at both 300 K and 2 K. The Fe3+-O2--Fe3+ superexchange paths broken by oxygen vacancies then resulting in the Fe3+-Fe3+ ferromagnetism configuration. Meanwhile, the oxygen vacancy is highly diluted then the ferromagnetism configuration is confined in a single super-cell, favoring a short-range magnetic ordering at room temperature. The concentration of oxygen vacancies was calculated to be 0.68% by magnetization measurement. Our results may shed a light on how oxygen vacancies affect magnetism.

In the present work, oil-in-water (O/W) emulsion systems were prepared by using the PEG-7 lauric acid glycerides as the emulsifiers and the liquid paraffin as the oil phase. The influence of processing parameters such as emulsification temperature, stirring speed, emulsifier concentration, oil-water volume ratio and polymer addition on the stability of the emulsion systems was investigated. In order to determine the optimal conditions for the preparation of the emulsion systems based on PEG-7 lauric acid glycerides, a laser drop size analyser and a rotational rheometer were used. As the stability of the O/W emulsion systems increased, the average droplet size of the O/W emulsions measured by the laser droplet size analyser became smaller and the viscosity, storage modulus and loss modulus of the O/W emulsions measured by the rotational rheometer became larger. The following optimal conditions were determined in this study: emulsification temperature 80°C, stirring speed 500 r/min, emulsifier concentration 5 wt%, oil-water volume ratio 1:1 and added amount of xanthan gum 0.2 wt%. The droplet morphology of the O/W emulsion prepared under the optimal conditions, which was characterised by a super high magnification microscope, is small. Furthermore, the long-term stability of the emulsion system prepared under the optimal conditions was investigated over a period of time (4 weeks). The O/W emulsion proves to be well stable even after 4 weeks, with a water separation rate of 0%.

Near-field communication (NFC) is a set of communication protocols that enable two electronic devices. Its security and reliability are welcomed by mobile terminal manufactures, banks, telecom operators, and third-party payment platforms. Simultaneously, it has also drawn more and more attention from hackers and attackers, and NFC-enabled devices are facing increasing threats. To improve the security of the NFC technology, the paper studied the technology of discovering security vulnerabilities of NFC Data Exchange Format (NDEF), the most important data transmission protocol. In the paper, we proposed an algorithm, GTCT (General Test Case Construction and Test), based on fuzzing to construct test cases and test the NDEF protocol. GTCT adopts four strategies to construct test cases, manual, generation, mutation, and “reverse analysis,” which can detect logic vulnerabilities that fuzzing cannot find and improve the detection rate. Based on GTCT, we designed an NDEF vulnerability discovering framework and developed a tool named “GNFCVulFinder” (General NFC Vulnerability Finder). By testing 33 NFC system services and applications on Android and Windows Phones, we found eight vulnerabilities, including DoS vulnerabilities of NFC service, logic vulnerabilities about opening Bluetooth/Wi-Fi/torch, design flaws about the black screen, and DoS of NFC applications. Finally, we give some security suggestions for the developer to enhance the security of NFC.

Metal-organic frameworks (MOFs) have been proposed as emerging fillers for composite polymer electrolytes (CPEs). However, MOF particles are usually served as passive fillers that yield limited ionic conductivity improvement. Building continuous MOF reinforcements and exploiting their active roles remain challenging. Here we demonstrate the feasibility of engineering fast Li+ conduction within MOF on molecule conception. Two-dimensional Cu(BDC) MOF is selected as an active filler due to its sufficient accessible open metal sites for perchlorate anion anchoring to release free Li+, verified by theoretical calculations and measurements. A novel Cu(BDC)-scaffold-reinforced CPE is developed via in situ growth of MOF, which provides fast Li+ channels inside MOF and continuous Li+ paths along the MOF/polymer interface for high Li+ conductivity (ambient 0.24 mS cm-1) and enables high mechanical strength. Stable cycling is achieved in solid-state Li-NCM811 full cell using the MOF-reinforced CPE. This molecule-basis Li+ conduction strategy brings new ideas for designing advanced CPEs.

Flow distortions from upstream combustors generate various and significant changes to the patterns of endwall heat transfer for an aircraft engine. In this study, to model engine-representative onc...

Quantum dots (QDs) have a wide range of applications in the field of optoelectronics. They have been playing multiple roles within the configuration of a device, by serving as the building blocks for both the active layer and the carrier transport layer. While the performance of various optoelectronic devices has been steadily improving via developments in passivating the QD active layer, the possible improvement via passivation of the QD-based carrier transport layer has been largely overlooked. Here, with lead sulfide QD photovoltaics as the platform of study, we demonstrate that the device performance can be significantly improved by passivating the QD hole transport layer (HTL) with zinc salt post-treatments. The power conversion efficiency is improved from 8.7% of the reference device to 10.2% and 9.5% for devices with zinc acetate (ZnAc)- and zinc iodide (ZnI2)-treated HTLs, respectively. Transient absorption spectroscopy confirms that both treatments effectively reduce band-tail states and increase carrier lifetime of the HTLs. Further elemental analysis shows that ZnAc provides a higher amount of Zn2+ for passivation while maintaining the function of HTL by allowing essential p-doping oxidation. In contrast, the additional I- passivation from ZnI2 inhibits p-doping oxidation and limits the function of HTL. This work demonstrates the potential of improving device performance by passivating the QD-based HTLs, and the method developed is likely applicable to other optoelectronic devices.

In this study, near-neutrally stratified planetary boundary layer (PBL) flows over complex terrain are numerically investigated via a one-way coupling of mesoscale numerical weather prediction (NWP) with unsteady computational fluid dynamics (CFD) codes. First, empirical turbulence model constants are modified to accomplish consistent turbulent viscosities between PBL schemes of mesoscale NWP and the $$k - \omega$$ turbulence closure of microscale CFD. Next, to reconstruct turbulent inflows calculated from coarse NWP analysis, inverse distance weighted (IDW) interpolation is optimized and adopted around the coupling interfaces. This method has been shown to decrease prediction uncertainty, as high-aspect-ratio NWP grids are used. Compared with time-series measurements, the proposed approach presents wind velocities in agreement around both upstream and separated regions in the Askervein Hill case, although the turbulent kinetic energy on the leeward side is still underestimated. Another moderately complex terrain with an enlarged domain around Feng Men Hill also exhibits improved numerical results. Moreover, the unsteady simulations reveal that both wind speed-up and wake are highly correlated with inflow characteristics. The successful integration of the nesting simulation with a general CFD code demonstrates the flexibility and efficiency of this procedure in modeling high-resolution unsteady flows over complex terrain.

Estimating future temporal patterns of Surface Urban Heat Islands (SUHIs) on multiple time scales is an ongoing research endeavor. Among these time scales, estimation of next-day SUHIs is of special significance to urban residents, yet we currently lack a simple but efficient approach for making such estimations. In the present study, we propose a statistical strategy for estimating next-day nighttime SUHIs, based on incorporating various SUHI controls into a support vector machine regression (SVR) model. The majority of both the surface controls (including factors related to land cover and solar radiation) and meteorological controls (including temperature fluctuations, relative humidity, accumulated precipitation, wind speed, aerosol optical depth, and soil moisture) that have previously been found to account for daily SUHI variations were used as estimators, and we provide estimations for both the overall SUHI intensity (SUHII) and pixel-by-pixel Gaussian-based LSTs over 59 Chinese megacities. For the overall SUHII, the mean absolute error (MAE) is 0.67 K on average, and the mean absolute percentage error (MAPE) is no more than 25% for more than 90% of the cities. For the pixel-by-pixel LSTs, the associated MAE is less than 2.0 K in most scenarios. In addition, the contribution from each selected estimator to SUHII estimation is assessed comprehensively. Among all the estimators, the contribution from relative humidity is the greatest, followed by rural surface temperature and surface air temperature. Moreover, for nearly 78% of the cities, the estimators related to day-to-day SUHI variations make a larger contribution than those related to intra-annual SUHI variations. We conclude that our simple yet effective statistical approach for estimating next-day SUHIs can potentially help urban residents to better adapt to urban heat stress.

With the in-depth application of new technologies such as big data in education fields, the storage and sharing model of student education records data still faces many challenges in terms of privacy protection and efficient transmission. In this paper, we propose a data security storage and sharing scheme based on consortium blockchain, which is a credible search scheme without verification. In our scheme, the implementation of data security storage is using the blockchain and storage server together. In detail, the smart contract provides protection for data keywords, the storage server stores data after data masking, and the blockchain ensures the traceability of query transactions. The need for precise privacy data is achieved by constructing a dictionary. Cryptographic techniques such as AES and RSA are used for encrypted storage of data, keywords, and digital signatures. Security analysis and performance evaluation shows that the availability, high efficiency, and privacy-preserving can be achieved. Meanwhile, this scheme has better robustness compared to other educational records data sharing models.

In urban Vehicular Ad hoc Networks (VANETs), high mobility of vehicular environment and frequently changed network topology call for a low delay end-to-end routing algorithm. In this paper, we propose a Multi-Agent Reinforcement Learning (MARL) based decentralized routing scheme, where the inherent similarity between the routing problem in VANET and the MARL problem is exploited. The proposed routing scheme models the interaction between vehicles and the environment as a multi-agent problem in which each vehicle autonomously establishes the communication channel with a neighbor device regardless of the global information. Simulation performed in the 3GPP Manhattan mobility model demonstrates that our proposed decentralized routing algorithm achieves less than 45.8 ms average latency and high stability of 0.05 % averaging failure rate with varying vehicle capacities.

A microcrystalline cellulose-based temperature sensitivity paclitaxel molecular imprinted hydrogel (MCC-TSMIHs-PTX) was successfully prepared by temperature-sensitive monomer N-isopropylacrylamide, functional monomer 4-vinylpyridine, cross-linking agent N, N'-methylenebisacrylamide and microcrystalline cellulose. They showed imprinting effective responses to the temperature changes. The results of adsorption kinetics, adsorption equilibrium, thermodynamics, selectivity and reusability showed the successful formation of a grafting thermosensitivity hydrogel with higher adsorption capacity and specific recognition. When the temperature reached 308 K, imprinting effect of hydrogel cavities would be most effective and conducive to capture template molecules. When the temperature reached 288 K, the lowest imprinting effect would facilitate the desorption of PTX. Finally, the MCC-TSMIHs-PTX was applied to enrich the paclitaxel in Taxus × media extracts samples, the relative contents of PTX in the samples were increased greatly from 7.23% to 78.32%, indicating the MCC-TSMIHs-PTX was a stable adsorption capacity for efficient separation and enrichment of PTX in Taxus × media extracts.

Hualei Song,1,* Yuntao Zhang,2,* Zihan Zhang,2,* Shijiang Xiong,3 Xiangrui Ma,2 Yourui Li2 1Department of Laboratory, Binzhou Medical University Hospital, Binzhou, 256603, People’s Republic of China; 2Department of Stomatology, Binzhou Medical University Hospital, Binzhou, 256603, People’s Republic of China; 3Shandong Provincial Key Laboratory of Oral Tissue Regeneration, School of Stomatology, Shandong University, Jinan, 250012, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yourui LiDepartment of Stomatology, Binzhou Medical University Hospital, 661#, 2nd Huanghe Road, Binzhou, 256603, Shangdong Province, People’s Republic of ChinaTel +86 543 3256715Email carylee37@qq.comBackground: As commonly bone defect is a disease of jaw that can seriously affect implant restoration, the bioactive scaffold can be used as potential systems to provide effective repair for bone defect.Purpose: A osteoinductive bone tissue engineering scaffold has been prepared in order to explore the effect of bioactive materials on bone tissue engineering.Methods: In this study, NELL-1 nanoparticles (Chi/NNP) and nano hydroxyapatite were incorporated in composite scaffolds by electrospinning and characterized using TEM, SEM, contact angle, tensile tests and in vitro drug release. In vitro biological activities such as MC3T3-E1 cell attachment, proliferation and osteogenic activity were studied.Results: With the addition of nHA and nanoparticles, the fiber diameter of PCL/BNPs group, PCL/NNPs group and PCL/nHA/NNPs group was significantly increased. Moreover, the hydrophilic hydroxyl group and amino group presented in nHA and nanoparticles had improved the hydrophilicity of the composite fibers. The composite electrospun containing Chi/NNPs can form a double protective barrier which can effectively prolong the release time of NELL-1 growth factor. In addition, the hydroxyapatite/NELL-1 nanoparticles electrospun fibers can promote attachment, proliferation, differentiation of MC3T3-E1 cells and good cytocompatibility, indicating better ability of inducing osteogenic differentiation.Conclusion: A multi-functional PCL/nHA/NNPs composite fiber with long-term bioactivity and osteoinductivity was successfully prepared by electrospinning. This potential composite could be used as scaffolds in bone tissue engineering application after in vivo studies.Keywords: polycaprolactone, nanoscaffold, MC3T3-E1 cells, osteogenic activity

Hyperspectral remote sensing is an important earth observation method with wide application. But the low spatial resolution of hyperspectral images makes it difficult to distinguish the ground objects. The hyperspectral image unmixing is a task to estimate the spectral signatures and corresponding fractional abundances. However, the unmixing speed and efficiency are still limited by traditional structures. In this paper, a novel multilayer nonnegative matrix factorization framework is proposed with Hoyer’s projector, called HP-MLNMF. The well-known framework, multilayer nonnegative factorization (MLNMF), is completely restructured and enhanced by introducing the Hoyer’s projector to provide the iteration directivity of the structure in the unmixing process. Besides, a novel sparse constraint to spectral signatures suitable for this structure is found as l 1 / 4 -norm based on some experimental discussions. Moreover, the l p -norm is utilized to find the possible sparest solution for abundance terms. Finally, HP-MLNMF is compared with some representative and state-of-art methods on synthetic and real-world hyperspectral image datasets. Experiments indicate that our method performances well in most cases.

The prediction of the remaining useful life (RUL) of rolling bearings is an important means to ensure the rotating machinery's safe operation. At present, most of the proposed methods use direct prediction based on bearing vibration signals, which not only have low prediction accuracy but also time-consuming. This paper proposes a staged prediction method, and the regularized learning machine (RELM) based on the proposed sensitive degradation feature is applied to predict RUL of the bearing with high accuracy and speed. Firstly, the relative root mean square value (RRMS) is used to divide the degradation stages of rolling bearings. Secondly, the RRMS indicator is used for multi-step time series prediction in the normal phase of the bearing. Thirdly, in the bearing's degradation stage, the Pearson Correlation Coefficient (PCC) Combined Entropy Weight Method (EWM) feature selection criterion is proposed to predict the RUL of the rolling bearing. Finally, the sensitive degradation feature of the bearing vibration signals is input into RELM to predict the RUL. The bearing data sets of PHM Challenging 2012 are used to verify the effectiveness of the proposed method. Three comparative experiments have been verified to prove the accuracy and rapidity of the proposed method in time series forecasting.

This study examines the job-access inequity between the richest 10% and poorest 40% transit-based workers across space (i.e. central city, the inner-ring/outer-ring suburb) and race (i.e. white, bl...

Strong-coupling effects alter the polaritonic states of metal–dielectric nanostructures and, therefore, can be used to tailor the response of infrared (IR) photonic elements. We report on the devel...

Bifurcated granular flow in a 2D channel with two lateral exits is numerically investigated by the discrete element method. Under the fixed inflow rate condition, the outflow rate is equal to the inflow rate in the dilute flow state and rapidly declines when dilute-to-dense flow transition (DDFT) occurs. The flow rate and the transition can be controlled by adjusting the sizes of the two exits. These observations can be explained by the relationship between the flow rate and the packing density in the bottleneck region under the fixed grain condition. Beverloo's formula is valid to describe the dependence of the dense flow rate on the exit size for bifurcated and non-bifurcated granular flows. The packing density in the bottleneck region plays a crucial role on the flow state. In specific, DDFT occurs at 0.6, and the dense flow terminates at 0.79.

Binarized convolutional neural network (BCNN) is a promising and efficient technique toward the landscape of Artificial Intelligence of Things (AIoT) applications. In-Memory Computing (IMC) has widely been studied to accelerate the inference task of BCNN to maximize both throughput and energy efficiency. However, existing IMC circuits and architectures are only optimized for a fixed kernel size and nominal voltage operation, which poses practical limitations on optimal network architecture exploration and additional energy efficiency benefits. In this brief, we present a reconfigurable, near-threshold IMC-based BCNN accelerator design. The IMC-based accelerator architecture is scalable for different kernels sizes ( $3 \times 3 \times d$ and $5 \times 5 \times d$ ) and achieves high resource utilization for both cases. Moreover, the IMC bitcell is optimized for reliable near-threshold operation. Implemented in a 55-nm CMOS process, our proposed reconfigurable IMC-based BCNN accelerator achieves 5526 TOPS/W energy efficiency at 0.4V, which is $6.38\times $ higher compared to the state-of-the-art designs. The inference accuracies of our proposed design are 97.73%, 82.56%, and 92.61% across three datasets (MNIST, CIFAR-10, and SVHN), respectively.

Spontaneously blinking probe, which switches between dark and bright state without UV or external additives, is extremely attractive in super resolution imaging of live cells. Herein, a clickable rhodamine spirolactam probe, Atto565-Tet, is rationally constructed for spontaneously blinking after biorthogonal labelling and successfully applied to super resolution imaging of mitochondria and lysosomes

Heterostructures composed of two-dimensional (2D) nanosheets and zero-dimensional (0D) nanoparticles (NPs) have attracted increasing attention because of the synergy arising from the coupling interactions between the two mixed-dimensional components. Despite recent advances, it remains a challenge to fabricate 2D/0D heterostructures with clean and accessible surfaces, which is highly desirable for the diversity of catalytic, sensing, and energy storage applications. Herein, we report a generalized methodology that enables the facile assembly of sandwich-like 0D/2D/0D heterostructures with facilitated mass-transport channels and exposed surface active sites. A ligand-exchange strategy with HBF4 is employed to strip off the surface-coating ligands of colloidal NPs, rendering them positively charged and dispersible in polar solvents. This allows subsequent electrostatic assembly of NPs with oppositely charged 2D nanosheets to afford sandwich-like 0D/2D/0D heterostructures. The barely covered surfaces and the advantageous architectures of such sandwich-like 0D/2D/0D heterostructures induce the desired synergistic effect, making them particularly suitable for electrochemical energy storage and conversion. We demonstrate this by employing MXene/NiFe2O4 and MXene/Fe3O4 heterostructures for high-performance electrocatalytic oxygen evolution and supercapacitors, respectively.

In this paper, to demonstrate the deposition effects on cooling performance, the changing patterns of film cooling due to particle deposition are numerically investigated on a turbine vane that is cooled by an array of film-holes. The uniqueness of this work is addressing the cooling performance at an early deposition stage, in which deposits are relatively slight. The build-ups of the deposits are simulated by moving grid nodes on the wall boundaries. Results show that in addition to particle velocity, the blowing conditions and wall temperatures are two important factors to determine the deposition patterns. Increasing coolant-to-mainstream mass flow ratios and lowering wall temperatures can help inhibit the growth of deposits. In addition, the modifications of the vane profile due to incipient deposition are completely different from those with excessive deposition. Although flow fields are less sensitive to the early-stage deposits in the subsonic vane passage, cooling effectiveness is significantly changed and the changes are linked to the mass flow ratios. Compared to the cooling performance from a non-deposition case, reduced cooling performance due to incipient deposition is found at a low mass flow ratio of 1.09%, while cooling performance is improved at moderate and high mass flow ratios of 1.64% and 2.06%.

Quantum dots (QDs) light-emitting diodes (QLEDs) are considered the most promising candidate for application in displays. While the efficiency of QLEDs has been greatly developed in recent years and is comparable to that of organic light-emitting diodes (OLEDs), it still remains challenging to realize both high efficiency and long lifetimes. In this work, we report efficient and stable red QLEDs with the maximum current efficiency of 13.48 cd A-1, external quantum efficiency of 18.65%, and low efficiency roll-off at high luminance with a long lifetime exceeding ∼2.9 × 105 h, representing a 3-fold increase in stability. Tailoring the composition of QDs suppresses nonradiative Forster resonant energy transfer and Auger recombination and provides favorable valence band alignment to boost the hole injection. Our work suggests that tailoring the nanostructures of QDs offers an effective means to simultaneously achieve high efficiency and high stability, accelerating QLED technology for practical applications in displays and lighting.

Hand sorting for different types of waste textiles is time-consuming, laborious and inaccurate. The non-destructive and efficient identification of fibers in waste fabrics is of great significance to the reuse of textile materials. In this paper, 593 samples were selected as the research objects, including polyester, cotton, wool, viscose, nylon, silk, acrylic, polyester/nylon, polyester/cotton, polyester/wool and silk/cotton waste textiles. The near-infrared spectrum of each sample was obtained by a portable near-infrared spectrometer, and the influence of environmental humidity and fabric thickness on the near-infrared spectrum of the sample was discussed to obtain the best test conditions. On this basis, the back propagation artificial neural network (BP-ANN) was applied to the qualitative classification of waste textiles to complete the automatic identification of fabric components in the sorting process. Firstly, a standard sample set was established by waveform clipping and normalization, and a BP-ANN deep web suitable for near-infrared spectroscopy was established. Then the BP network was trained according to the input near-infrared spectrum data of known sample categories and the classification results of the preset 11 types of labels, and the weights and thresholds of each layer were adjusted in the repeated training process. Finally, a 1500 × 100 × 11 network structure was established when the network error was the smallest, and the number of corresponding hidden layer nodes was 100. When the number of training steps was 500, the sum of squared errors reached 0.001, and the model recognition effect was the best. Meanwhile, the validity of the model was verified by inspecting additional 299 samples outside the model, and the recognition accuracy rate of the established model also exceeded 99%, which verified the effectiveness of the model. These results show that this near-infrared qualitative analysis model can more accurately classify and identify waste textiles, especially polyester waste textiles. In addition, it provides a new idea for the recycling and reuse of waste textiles for enterprises.

Internet applications remain exposed to pervasive Domain Name System (DNS)–based threats. Blockchain technologies provide a new way for tackling DNS vulnerability issues, and have been highlighted recently. However, traditional blockchain is still not well suited for big data applications such as DNS, because the performance of blockchain consensus greatly limits its practical adoption. In this paper, we present DagGridLedger, a sharded directed acyclic graph (DAG) blockchain that provides scalable big data architecture for trustful DNS management. To achieve this goal, DagGridLedger proposes a radical new architecture that combines blockchain sharding and DAG techniques on the DNS resolver side, thereby making it a promising solution to enhance the security and stability of large-scale DNS system. To be specific, DagGridLedger provides a blockchain structure targeting DNS application, which employs a high-performance DAG consensus algorithm named DagGrid. DagGrid consensus realizes a multi-DNS negotiation mechanism through block sharding in generating a block. With an improved asynchronous leaderless Byzantine consensus, DagGrid implements total order determination, which guarantees the trustful DNS management. Further experiments verified the performance of DagGridLedger as well as the applicability of the proposed blockchain architecture in traditional DNS. To this end, DagGridLedger consistently achieves a big data architecture for secure DNS record management, with a novel shared DAG consensus designed for high throughput. This makes DagGridLedger a promising architecture for highly secure and efficient DNS solution.

The aim of this article is to investigate a new system for the smart city vertical market, highlight the smart city vertical market's vitality, and promote smart city development. While constructing smart cities under the support of IoT, cloud computing, and the Internet, smart cities' vertical market system is modeled from the economy's viewpoint. The model's security and confidentiality are analyzed via simulation. The details on the vertical market are explored from the economic perspective. System performance analysis proves the built system's security performance for data transmission under six different channels. From the vertical market's perspective, the total joint operation mode sales exceed those of self-operation mode. The sales volume of every supplier is lower than the self-operated retailer. From the operating costs' perspective, self-operated retailers have the advantage of higher retail prices and lower unit operating costs compared to joint-operated suppliers. Therefore, the built system has good stability, and the self-operated retailers have more advantages from the vertical market perspective, which can provide an experimental reference for the construction of smart cities and economic development in the future.

By analyzing solid holdup signals in the jet influence zone of risers, the characteristics of clusters were studied. The solid holdups inside clusters and their distribution ranges were calculated under the cases of both upward and downward feed jets. Moreover, the effects of the jet velocity on the cluster characteristics were analyzed. The solid holdups inside clusters have higher values and wider distribution ranges in the upward feed injection zone than in the downward zone, implying that the number of individual particles in a cluster is unstable under the influence of upward jets. For the case of downward jets, cluster formations in the jet influence zone of risers can more easily maintain stability, offering a better mixing environment for jets and particles. As the jet velocity increases, the solid holdups inside clusters in the riser wall of the upward injection zone increase accordingly, while the distributions of solid holdups inside clusters have no significant changes if the feed jets are downward. This phenomenon confirms that improved operational flexibility can be obtained if downward jets are mixed with the prelift gas–solid flow in risers.

Based on the comprehensive understanding on microfractures and matrix pores in reservoir rocks, numerical algorithms are used to construct fractured porous media and fracture-pore media models. Connectivity coefficient and strike factor are introduced into the models to quantitatively characterize the connectivity and strike of fracture network, respectively. The influences of fracture aperture, fracture strike and fracture connectivity on the permeability of porous media are studied by using multi-relaxation-time lattice Boltzmann model to simulate fluid flow in them. The greater the strike factor and the smaller the tortuosity of the fractured porous media, the greater the permeability of the fractured porous media. The greater the connectivity coefficient of the fracture network is, the greater the permeability of the fracture-pore media is, and the more likely dominant channel effect occurs. The fracture network connectivity has stronger influence on seepage ability of fracture-pore media than fracture aperture and fracture strike. The tortuosity and strike factor of fracture network in fractured porous media are in polynomial relation, while the permeability and fracture network connectivity coefficient of the fracture-pore media meet an exponential relation.

Contact engineering is of critical importance for two-dimensional (2D) transition metal dichalcogenide (TMD)-based devices. However, there are only a few solutions to overcome this obstacle because of the complexity of the TMD-contact interface. In this work, we propose a novel method using a soft plasma treatment followed by the seamless deposition of a metal electrode to reduce the contact resistance of MoS2 field effect transistors (FETs). The treated FETs exhibit three times higher mobility than the control FETs without plasma treatment. The soft plasma treatment can remove the facial sulfur atoms and expose the middle Mo atoms so that they come into direct contact with the metal electrode, thus greatly improving the contact behavior. First-principles calculation is also performed to support the experimental results. Our potentially scalable strategy can be extended to the whole family of TMD based FETs to provide a possible route of device processsing technology for 2D device application.

Ferroptosis had shown huge potential for antitumor treatment due to its capacity of improving the limited efficiency of traditional antitumor strategies. On the other hand, low confidence in clinical application prospects impeded their development as a result of use of toxic-dose iron. Herein, we prepared a nano-activator (DAR) which was assembled by doxorubicin (DOX), tannic-acid (TA) and IR820 as a photosensitizer to make full use of endogenous iron stored in endo-lysosome, realizing ferroptosis and its related oxidative stress through artificially intracellular positive feedback loop. Interestingly, this process could also promote immunogenic cell death (ICD)-associated immunotherapy through endoplasmic reticulum (ER) stress. After DAR + laser treatment, the intracellular oxidative stress response was intensified. The produced ROS could be effectively distributed in intracellular lysosomes and ERs to facilitate ferroptosis and immunotherapy respectively. The pharmacodynamics study revealed that DAR + laser had excellent antitumor combination therapy efficiency even under the adverse combined drug ratio of DOX and IR820 due to the unique synergism activation effect of DAR mediated ferroptosis-immunotherapy. In summary, our study provided an innovative solution for the development of antitumor treatment based on ferroptosis-immunotherapy.

High-pressure investigation has been shown to be of paramount significance for changing the conventional lattice or bringing fascinating properties, especially inducing superconducting phases. Here we studied the application of pressure to the recently synthesized 2M-WS2 with the record Tc (8.8 K) among transition metal dichalcogenides (TMDs) at ambient pressure by electrical resistance investigations, synchrotron X-ray studies, and theoretical calculations. Tc in the initial 2M-WS2 dropped from the maximum to become undetected, accompanied by a phase transition into a semiconductor, 3R-WS2, at 15 GPa. The successive metallization and superconducting transitions in 3R-WS2 were observed at 48.8 GPa with Tc ≈ 2.5 K. This is the first experimental case in which superconductivity has been realized in the 3R phase among TMDs. We propose that the degradation of superconductivity in 2M-WS2 and the reemergence of superconductivity in 3R-WS2 are mainly attributable to changes in the density of states near the Fermi surface driven by the interlayer coupling.

Increasing threats from both pathogenic infections and antibiotic resistance highlight the pressing demand for nonantibiotic agents and alternative therapies. Herein, we report several new phenothiazinium-based derivatives, which could be readily synthesized via fragment-based assembly, which exhibited remarkable bactericidal activities both in vitro and in vivo. Importantly, in contrast to numerous clinically and preclinically used antibacterial photosensitizers, these compounds were able to eliminate various types of microorganisms, including Gram-(+) Staphylococcus aureus (S. aureus), Gram-(-) Escherichia coli, multidrug-resistant S. aureus, and their associated biofilms, at low drug and light dosages (e.g., 0.21 ng/mL in vitro and 1.63 ng/cm2 in vivo to eradicate S. aureus at 30 J/cm2). This study thus unveils the potential of these novel phenothiaziniums as potent antimicrobial agents for highly efficient photodynamic antibacterial chemotherapy.

The rational design and construction of hierarchically porous nanostructure for oxygen reduction reaction (ORR) electrocatalysts is crucial to facilitate the exposure of accessible active sites and promote the mass/electron transfer under the gas-solid-liquid triple-phase condition. Herein, an ingenious method through the pyrolysis of creative polyvinylimidazole coordination with Zn/Fe salt precursors is developed to fabricate hierarchically porous Fe-N-doped carbon framework as efficient ORR electrocatalyst. The volatilization of Zn species combined with the nanoscale Kirkendall effect of Fe dopants during the pyrolysis build the hierarchical micro-, meso-, and macroporous nanostructure with a high specific surface area (1,586 m2·g−1), which provide sufficient exposed active sites and multiscale mass/charge transport channels. The optimized electrocatalyst exhibits superior ORR activity and robust stability in both alkaline and acidic electrolytes. The Zn-air battery fabricated by such attractive electrocatalyst as air cathode displays a higher peak power density than that of Pt/C-based Zn-air battery, suggesting the great potential of this electrocatalyst for Zn-air batteries.

The sluggish kinetics of the four-electron-proton coupled oxygen evolution reaction (OER) limits the efficiency of water splitting. Herein, Ni–S–CoFe2O4 magnetic nanosheets supported on Ni Foam (Magn-Ni-S-CoFe2O4/NF) as highly active OER electrocatalysts are synthesized via an extremely simple magnetic-field guided co-electrodeposition strategy. With the application of magnetic fields, the flower-like structures consisting of numerous nanosheets are obtained. This special interconnected structure can effectively reduce the transfer resistance to electrons during catalysis. The ultra-thin amorphous Ni–S layer at the edge of well-defined crystalline CoFe2O4 provides more active sites for the reaction because of the abundant defects, which greatly enhances the OER performance. At the same time, the application of magnetic fields changes the chemical state of the electrocatalyst. The well-designed Magn-Ni-S-CoFe2O4/NF exhibits excellent OER activity with a low overpotential of 228 mV at the current density of 10 mA cm−2, which is lower than the value of 253 mV for the Ni–S–CoFe2O4/NF without applied magnetic field, a small Tafel slope of 72 mV dec−1 and excellent stability for at least 24 h. This work provides a simple magnetic field-assisted synthesis method to prepare electrocatalysts with excellent OER activity.

Luminescence color and application environment of anti-counterfeiting materials are closely related to the excitation modes, which play a decisive role in information security. Ca1.997-xNb2O7:xEr3+/0.003Pr3+ (x = 0.002, 0.006, 0.01, 0.015, 0.02) ferroelectric ceramics have been prepared via traditional solid-state reaction method. Four-modal luminescence comprising color-tunable (red/yellow/green) photoluminescence (PL), up-conversion luminescence (UCL), photostimulated luminescence (PSL) and thermoluminescence (TL) have been realized in the prepared ceramics. The corresponding mechanisms were also discussed and proposed. PSL using near infrared (NIR) light excitation was first reported in this material. Besides, the as-synthesized phosphors and commercial ZnS:Cu2+ were incorporated into a polydimethylsiloxane (PDMS) matrix to fabricate a multifunctional optical device. The obtained device successfully provides multidimensional codes with colorful (red/pink/white/cyan/green/blue) and multimodal (upconverted/downshifted and photon-/thermo-/mechano-drived) emission, showing the promising prospects in optical information storage and anti-counterfeiting.

Dan Yu,1,2,* Qilong Yin,1,3,* Jiwei Wang,1,* Jian Yang,1 Zimeng Chen,1 Zihan Gao,1 Qingli Huang,1,4 Shibao Li1,3 1Medical Technology School of Xuzhou Medical University, Xuzhou, Jiangsu, 221000, People’s Republic of China; 2Jiangsu Key Laboratory of Medical Science and Laboratory Medicine, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu, 212013, People’s Republic of China; 3Department of Laboratory Medicine, Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, 221000, People’s Republic of China; 4Public Experimental Research of Xuzhou Medical University, Xuzhou, Jiangsu, 221000, People’s Republic of China*These authors contributed equally to this workCorrespondence: Qingli HuangPublic Experimental Research of Xuzhou Medical University, Xuzhou, Jiangsu, 221000, People’s Republic of ChinaTel +86 15150043097Fax +86 516 83262091Email qlhuang@xzhmu.edu.cnShibao LiDepartment of Laboratory Medicine, Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, 221000, People’s Republic of ChinaTel +86 15895212960Fax +86 516 83353651Email sdjnshlb@xzhmu.edu.cnPurpose: Developing a sensitive SERS-based method to quantitatively detect serum biomarkers (Aβ 1-42 and P-Tau-181) for the early diagnosis of Alzheimer’s disease (AD).Methods: In this study, a novel SERS-based sandwich immunoassay, which consists of tannin-capped silver nanoparticles and magnetic graphene oxide (Fe3O4@GOs), was developed. We firstly applied this method for the detection of protein standards in buffer solution, obtaining the regression equation. Then, its potential value on real serum samples of AD was further explored.Results: The detection linear range of Aβ 1-42 and P-Tau-181 protein standards were observed to range from 100 pg mL− 1 to 10 fg mL− 1, 100 pg mL− 1 to 1 fg mL− 1 respectively. We finally explored clinical application of the proposed method in 63 serum samples. As a result, P-tau-181 differentiated AD from non-AD dementia patients (AUC = 0.770), with a more favored ROC than Aβ 1-42 (AUC =  0.383).Conclusion: The developed SERS-based immunoassay is successfully applied to the determination of Aβ 1-42 and P-Tau-181 in human serum specimens, which provides a promising tool for the early diagnosis of AD.Keywords: surface-enhanced Raman scattering, silver probe, Alzheimer’s disease, biomarker, diagnosis