Giant and controllable Goos—Hänchen shift of a reflective beam off a hyperbolic metasurface of polar crystals

We conduct a theoretical analysis of the massive and tunable Goos–Hänchen(GH) shift on a polar crystal covered with periodical black phosphorus(BP)-patches in the THz range. The surface plasmon phonon polaritons(SPPPs), which are coupled by the surface phonon polaritons(SPh Ps) and surface plasmon polaritons(SPPs), can greatly increase GH shifts.Based on the in-plane anisotropy of BP, two typical metasurface models are designed and investigated. An enormous GH shift of about-7565.58 λ_(0) is achieved by adjusting the physical parameters of the BP-patches. In the designed metasurface structure, the maximum sensitivity accompanying large GH shifts can reach about 6.43 × 10^(8) λ_(0)/RIU, which is extremely sensitive to the size, carrier density, and layer number of BP. Compared with a traditional surface plasmon resonance sensor, the sensitivity is increased by at least two orders of magnitude. We believe that investigating metasurface-based SPPPs sensors could lead to high-sensitivity biochemical detection applications.

The manipulation of rectifying contact of Co and nitrogen-doped carbon hierarchical superstructures toward high-performance oxygen reduction reaction

Rational design and construction of oxygen reduction reaction(ORR)electrocatalysts with high activity,good stability,and low price are essential for the practical applications of renewable energy conversion devices,such as metal-air batteries.Electronic modification through constructing metal/semiconductor Schottky heterointerface represents a powerful strategy to enhance the electrochemical performance.Herein,we demonstrate a concept of Schottky electrocatalyst composed of uniform Co nanoparticles in situ anchored on the carbon nanotubes aligned on the carbon nanosheets(denoted as Co@N-CNTs/NSs hereafter)toward ORR.Both experimental findings and theoretical simulation testify that the rectifying contact could impel the voluntary electron flow from Co to N-CNTs/NSs and create an internal electric field,thereby boosting the electron transfer rate and improving the intrinsic activity.As a consequence,the Co@N-CNTs/NSs deliver outstanding ORR activity,impressive long-term durability,excellent methanol tolerance,and good performance as the air-cathode in the Zn-air batteries.The design concept of Schottky contact may provide the innovational inspirations for the synthesis of advanced catalysts in sustainable energy conversion fields.

Application of different fiber structures and arrangements by electrospinning in triboelectric nanogenerators

In recent years,nanogenerators(NGs)have attracted wide attention in the energy field,among which triboelectric nanogenerators(TENGs)have shown superior performance.Multiple reports of electrospinning(ES)-based TENGs have been reported,but there is a lack of deep analysis of the designing method from microstructure,limiting the creative of new ES-based TENGs.Most TENGs use polymer materials to achieve corresponding design,which requires structural design of polymer materials.The existing polymer molding design methods include macroscopic molding methods,such as injection,compression,extrusion,calendering,etc.,combined with liquid-solid changes such as soluting and melting;it also includes micro-nano molding technology,such as melt-blown method,coagulation bath method,ES method,and nanoimprint method.In fact,ES technology has good controllability of thickness dimension and rich means of nanoscale structure regulation.At present,these characteristics have not been reviewed.Therefore,in this paper,we combine recent reports with some microstructure regulation functions of ES to establish a more general TENGs design method.Based on the rich microstructure research results in the field of ES,much more new types of TENGs can be designed in the future.

Design of weak current measurement system and research on temperature impact

A dedicated weak current measurement system was designed to measure the weak currents generated by the neutron ionization chamber.This system incorporates a second-order low-pass filter circuit and the Kalman filtering algorithm to effectively filter out noise and minimize interference in the measurement results.Testing conducted under normal temperature conditions has demonstrated the system's high precision performance.However,it was observed that temperature variations can affect the measurement performance.Data were collected across temperatures ranging from -20 to 70℃,and a temperature correction model was established through linear regression fitting to address this issue.The feasibility of the temperature correction model was confirmed at temperatures of -5 and 40℃,where relative errors remained below 0.1% after applying the temperature correction.The research indicates that the designed measurement system exhibits excellent temperature adaptability and high precision,making it particularly suitable for measuring weak currents.

Recent advances in fabrication and functions of neuromorphic system based on organic field effect transistor

The development of various artificial electronics and machines would explosively increase the amount of information and data,which need to be processed via in-situ remediation.Bioinspired synapse devices can store and process signals in a parallel way,thus improving fault tolerance and decreasing the power consumption of artificial systems.The organic field effect transistor(OFET)is a promising component for bioinspired neuromorphic systems because it is suitable for large-scale integrated circuits and flexible devices.In this review,the organic semiconductor materials,structures and fabrication,and different artificial sensory perception systems functions based on neuromorphic OFET devices are summarized.Subsequently,a summary and challenges of neuromorphic OFET devices are provided.This review presents a detailed introduction to the recent progress of neuromorphic OFET devices from semiconductor materials to perception systems,which would serve as a reference for the development of neuromorphic systems in future bioinspired electronics.

Seismic anisotropy and upper mantle dynamics in Alaska:A review of shear wave splitting analyses

Shear wave splitting(SWS)is regarded as the most effective geophysical method to delineate mantle flow fields by detecting seismic azimuthal anisotropy in the earth's upper mantle,especially in tectonically active regions such as subduction zones.The Aleutian-Alaska subduction zone has a convergence rate of approximately 50 mm/yr,with a trench length reaching nearly 2800 km.Such a long subduction zone has led to intensive continental deformation and numerous strong earthquakes in southern and central Alaska,while northern Alaska is relatively inactive.The sharp contrast makes Alaska a favorable locale to investigate the impact of subduction on mantle dynamics.Moreover,the uniqueness of this subduction zone,including the unusual subducting type,varying slab geometry,and atypical magmatic activity and composition,has intrigued the curiosity of many geoscientists.To identify different sources of seismic anisotropy beneath the Alaska region and probe the influence of a geometrically varying subducting slab on mantle dynamics,extensive SWS analyses have been conducted in the past decades.However,the insufficient station and azimuthal coverage,especially in early studies,not only led to some conflicting results but also strongly limited the in-depth investigation of layered anisotropy and the estimation of anisotropy depth.With the completion of the Transportable Array project in Alaska,recent studies have revealed more detailed mantle structures and characteristics based on the dense station coverage and newly collected massive seismic data.In this study,we review significant regional-and continental-scale SWS studies in the Alaska region and conclude the mantle flow fields therein,to understand how a geometrically varying subducting slab alters the regional mantle dynamics.The summarized mantle flow mechanisms are believed to be conducive to the understanding of seismic anisotropy patterns in other subduction zones with a complicated tectonic setting.

Strain engineering of electronic and magnetic properties of Ga_2S_2 nanoribbons

Using first-principles calculations, we study the tailoring of the electronic and magnetic properties of gallium sulfide nanoribbons（Ga2S2NRs） by mechanical strain. Hydrogen-passivated armchair-and zigzag-edged NRs（ANRs and ZNRs）with different widths are investigated. Significant effects in band gap and magnetic properties are found and analyzed. First,the band gaps and their nature of ANRs can be largely tailored by a strain. The band gaps can be markedly reduced, and show an indirect-direct（I-D） transition under a tensile strain. While under an increasing compressive strain, they undergo a series transitions of I-D-I-D. Five strain zones with distinct band structures and their boundaries are identified. In addition,the carrier effective masses of ANRs are also tunable by the strain, showing jumps at the boundaries. Second, the magnetic moments of（ferromagnetic） ZNRs show jumps under an increasing compressive strain due to spin density redistribution,but are unresponsive to tensile strains. The rich tunable properties by stain suggest potential applications of Ga2S2 NRs in nanoelectronics and optoelectronics.

Photocatalytic removal of heavy metal ions and antibiotics in agricultural wastewater:A review

In recent years,the treatment of agricultural wastewater has been an important aspect of environmental protection.The purpose of photocatalytic technology is to degrade pollutants by utilizing solar light energy to stimulate the migration of photocarriers to the surface of photocatalysts and occur reduction-oxidation reaction with pollutants in agricultural wastewater.Photocatalytic technology has the characteristics of high efficiency,sustainability,low-energy and free secondary pollution.It is an environmental and economical method to recover water quality that only needs sunlight.In this paper,the mechanism and research progress of photocatalytic removal of heavy metal ions and antibiotics from agricultural water pollution were reviewed by combining photocatalytic degradation process with agricultural treatment technology.The mechanism of influencing factors of photocatalytic degradation efficiency was discussed in detail and corresponding strategies were proposed,which has certain reference value for the development of photocatalytic degradation.

Boosting oxygen reduction activity and CO_(2) resistance on bismuth ferrite-based perovskite cathode for low-temperature solid oxide fuel cells below 600℃

Developing efficient and stable cathodes for low-temperature solid oxide fuel cells(LT-SOFCs) is of great importance for the practical commercialization.Herein,we propose a series of Sm-modified Bi_(0.7-x)Sm_xSr_(0.3)FeO_(3-δ) perovskites as highly-active catalysts for LT-SOFCs.Sm doping can significantly enhance the electrocata lytic activity and chemical stability of cathode.At 600℃,Bi_(0.675)Sm_(0.025)Sr_(0.3)FeO_(3-δ)(BSSF25) cathode has been found to be the optimum composition with a polarization resistance of 0.098 Ω cm^2,which is only around 22.8% of Bi_(0.7)Sr_(0.3)FeO_(3-δ)(BSF).A full cell utilizing BSSF25 displays an exceptional output density of 790 mW cm^(-2),which can operate continuously over100 h without obvious degradation.The remarkable electrochemical performance observed can be attributed to the improved O_(2) transport kinetics,superior surface oxygen adsorption capacity,as well as O_(2)p band centers in close proximity to the Fermi level.Moreover,larger average bonding energy(ABE) and the presence of highly acidic Bi,Sm,and Fe ions restrict the adsorption of CO_(2) on the cathode surface,resulting in excellent CO_(2) resistivity.This work provides valuable guidance for systematic design of efficient and durable catalysts for LT-SOFCs.

Simultaneous detection of CH_(4)and CO_(2)through dual modulation off-axis integrated cavity output spectroscopy

This study established a novel method for the simultaneous detection of two-component gases.Radio frequency(RF)white noise disturbance laser current and wavelength modulation were simultaneously used to improve the off-axis integrated cavity output spectroscopy technique,and a high-precision dual modulation OA-ICOS(RF-WM-OA-ICOS)system was established.The two laser beams were coupled into one laser beam that was applied incident to the cavity of RF-WM-OA-ICOS system.The second harmonic signals of CH_(4)and CO_(2)gas simultaneously appeared in the rising or falling edge of a triangular wave.This method was used to measure CH_(4)and CO_(2)with different concentrations.The results indicated that the proposed system has high stability and can accurately and simultaneously measure the concentrations of CH_(4)and CO_(2),with an optimal integration time of 220 s.The minimum detection limit was 10 ppb for CH_(4)and 1.5 ppm for CO_(2).The corresponding noise equivalent absorption sensitivity values were calculated as 2.67×10^(-13)cm^(-1)·Hz^(-1/2)and 5.18×10^(-11)cm^(-1)·Hz^(-1/2),respectively.The proposed dual-component gas simultaneous detection method can also be used for high-precision simultaneous detection of other gases.Therefore,this study may serve as a reference for developing portable multicomponent gas analyzers.

Simultaneous realization of high sulfur utilization and lithium dendrite-free via dual-effect kinetic regulation strategy toward lithium-sulfur batteries

With the high theoretical specific capacity and energy density,lithium-sulfur batteries(LSBs)have been intensively studied as promising candidates for energy storage devices.However,LSBs are largely hindered by inferior sulfur utilization and uncontrollable dendritic growth.Herein,a hierarchical functionalization strategy of stepwise catalytic-adsorption-conversion for sulfur species via the synergetic of the efficiently catalytic host cathode and light multifunctional interlayer has been proposed to concurrently address the issues arising on the dual sides of the LSBs.The multi-layer SnS_(2) micro-flowers embedded into the natural three-dimensional(3D)interconnected carbonized bacterial cellulose(CBC)nanofibers are fabricated as the sulfur host that provides numerous catalytic sites for the rapid catalytic conversion of sulfur species.Moreover,the distinctive CBC-based SnO_(2)-SnS_(2) heterostructure network accompanied high conductive carbon nanofibers as the multifunctional interlayer promotes the rapid anchoringdiffusion-conversion of lithium polysulfides,Li^(+)flux redistribution,and uniform Li deposition.LSBs equipped with our strategy exhibit a high reversible capacity of 1361.5 m A h g^(-1)at 0.2 C and superior cycling stability with an ultra-low capacity fading of 0.031%per cycle in 1000 cycles at 1.5 C and 0.046%at 3 C.A favorable specific capacity of 859.5 m A h g^(-1)at 0.3 C is achieved with a high sulfur mass loading of 5.2 mg cm^(-2),highlighting the potential of practical application.The rational design in this work can provide a feasible solution for high-performance LSBs and promote the development of advanced energy storage devices.

Sea-Land Segmentation of Remote Sensing Images Based on SDW-UNet

Image segmentation of sea-land remote sensing images is of great importance for downstream applications including shoreline extraction,the monitoring of near-shore marine environment,and near-shore target recognition.To mitigate large number of parameters and improve the segmentation accuracy,we propose a new Squeeze-Depth-Wise UNet(SDW-UNet)deep learning model for sea-land remote sensing image segmentation.The proposed SDW-UNet model leverages the squeeze-excitation and depth-wise separable convolution to construct new convolution modules,which enhance the model capacity in combining multiple channels and reduces the model parameters.We further explore the effect of position-encoded information in NLP(Natural Language Processing)domain on sea-land segmentation task.We have conducted extensive experiments to compare the proposed network with the mainstream segmentation network in terms of accuracy,the number of parameters and the time cost for prediction.The test results on remote sensing data sets of Guam,Okinawa,Taiwan China,San Diego,and Diego Garcia demonstrate the effectiveness of SDW-UNet in recognizing different types of sea-land areas with a smaller number of parameters,reduces prediction time cost and improves performance over other mainstream segmentation models.We also show that the position encoding can further improve the accuracy of model segmentation.

Synchronous implementation of optoelectronic NOR and XNOR logic gates using parallel synchronization of three chaotic lasers

The parallel synchronization of three chaotic lasers is used to emulate optoelectronic logic NOR and XNOR gates via modulating the light and the current. We deduce a logical computational equation that governs the chaotic synchronization, logical input, and logical output. We construct fundamental gates based on the three chaotic lasers and define the computational principle depending on the parallel synchronization. The logic gate can be implemented by appropriately synchronizing two chaotic lasers. The system shows practicability and flexibility because it can emulate synchronously an XNOR gate, two NOR gates, and so on. The synchronization can still be deteceted when mismatches exist with a certain range.

Probing structural and electronic properties of divalent metal Mg_(n+1) and SrMgn (n=2–12) clusters and their anions

Divalent metal clusters have received great attention due to the interesting size-induced nonmetal-to-metal transition and fascinating properties dependent on cluster size,shape,and doping.In this work,the combination of the CALYPSO code and density functional theory(DFT)optimization is employed to explore the structural properties of neutral and anionic Mg_(n+1) and SrMgn(n=2-12)clusters.The results exhibit that as the atomic number of Mg increases,Sr atoms are more likely to replace Mg atoms located in the skeleton convex cap.By analyzing the binding energy,second-order energy difference and the charge transfer,it can be found the SrMg9 cluster with tower framework presents outstanding stability in a studied size range.Further,bonding characteristic analysis reveals that the stability of SrMg9 can be improved due to the strong s-p interaction among the atomic orbitals of Sr and Mg atoms.

VSe_(2)/V_(2)C heterocatalyst with built-in electric field for efficient lithium-sulfur batteries:Remedies polysulfide shuttle and conversion kinetics

Lithium sulfur(Li-S)battery is a kind of burgeoning energy storage system with high energy density.However,the electrolyte-soluble intermediate lithium polysulfides(Li PSs)undergo notorious shuttle effect,which seriously hinders the commercialization of Li-S batteries.Herein,a unique VSe_(2)/V_(2)C heterostructure with local built-in electric field was rationally engineered from V_(2)C parent via a facile thermal selenization process.It exquisitely synergizes the strong affinity of V_(2)C with the effective electrocatalytic activity of VSe_(2).More importantly,the local built-in electric field at the heterointerface can sufficiently promote the electron/ion transport ability and eventually boost the conversion kinetics of sulfur species.The Li-S battery equipped with VSe_(2)/V_(2)C-CNTs-PP separator achieved an outstanding initial specific capacity of 1439.1 m A h g^(-1)with a high capacity retention of 73%after 100 cycles at0.1 C.More impressively,a wonderful capacity of 571.6 mA h g^(-1)was effectively maintained after 600cycles at 2 C with a capacity decay rate of 0.07%.Even under a sulfur loading of 4.8 mg cm^(-2),areal capacity still can be up to 5.6 m A h cm^(-2).In-situ Raman tests explicitly illustrate the effectiveness of VSe_(2)/V_(2)C-CNTs modifier in restricting Li PSs shuttle.Combined with density functional theory calculations,the underlying mechanism of VSe_(2)/V_(2)C heterostructure for remedying Li PSs shuttling and conversion kinetics was deciphered.The strategy of constructing VSe_(2)/V_(2)C heterocatalyst in this work proposes a universal protocol to design metal selenide-based separator modifier for Li-S battery.Besides,it opens an efficient avenue for the separator engineering of Li-S batteries.

A Novel CCA-NMF Whitening Method for Practical Machine Learning Based Underwater Direction of Arrival Estimation

Underwater direction of arrival(DOA)estimation has always been a very challenging theoretical and practical problem.Due to the serious non-stationary,non-linear,and non-Gaussian characteristics,machine learning based DOA estimation methods trained on simulated Gaussian noised array data cannot be directly applied to actual underwater DOA estimation tasks.In order to deal with this problem,environmental data with no target echoes can be employed to analyze the non-Gaussian components.Then,the obtained information about non-Gaussian components can be used to whiten the array data.Based on these considerations,a novel practical sonar array whitening method was proposed.Specifically,based on a weak assumption that the non-Gaussian components in adjacent patches with and without target echoes are almost the same,canonical cor-relation analysis(CCA)and non-negative matrix factorization(NMF)techniques are employed for whitening the array data.With the whitened array data,machine learning based DOA estimation models trained on simulated Gaussian noised datasets can be used to perform underwater DOA estimation tasks.Experimental results illustrated that,using actual underwater datasets for testing with known machine learning based DOA estimation models,accurate and robust DOA estimation performance can be achieved by using the proposed whitening method in different underwater con-ditions.

Conversion of LiPSs Accelerated by Pt-Doped Biomass-Derived Hyphae Carbon Nanobelts as Self-Supporting Hosts for Long-Lifespan Li-S Batteries

Rechargeable Li-S batteries(LSBs)are emerging as an important alternative to lithium-ion batteries(LIBs),owing to their high energy densities and low cost;yet sluggish redox kinetics of LiPSs results in inferior cycle life.Herein,we prepared multifunctional self-supporting hyphae carbon nanobelt(HCNB)as hosts by carbonization of hyphae balls of Rhizopus,which could increase the S loading of the cathode without sacrificing reaction kinetics.Trace platinum(Pt)nanoparticles were introduced into HCNBs(PtHCNBs)by ion-beam sputtering deposition.Based on the X-ray photoelectron spectroscopy analyses,the introduced trace Pt regulated the local electronic states of heteroatoms in HCNBs.Electrochemical kinetics investigation combined with operando Raman measurements revealed the accelerated reaction mechanics of sulfur species.Benefiting from the synergistic catalytic effect and the unique structures,the as-prepared PtHCNB/MWNCT/S cathodes delivered a stable capacity retention of 77%for 400 cycles at 0.5 C with a sulfur loading of 4.6 mg cm^(-2).More importantly,remarkable cycling performance was achieved with an high areal S loading of 7.6 mg cm^(-2).This finding offers a new strategy to prolong the cycle life of LSBs.

A Deep Learning Framework for Mass-Forming Chronic Pancreatitis and Pancreatic Ductal Adenocarcinoma Classification Based on Magnetic Resonance Imaging

Pancreatic diseases, including mass-forming chronic pancreatitis (MFCP) and pancreatic ductal adenocarcinoma(PDAC), present with similar imaging features, leading to diagnostic complexities. Deep Learning (DL) methodshave been shown to perform well on diagnostic tasks. Existing DL pancreatic lesion diagnosis studies basedon Magnetic Resonance Imaging (MRI) utilize the prior information to guide models to focus on the lesionregion. However, over-reliance on prior information may ignore the background information that is helpful fordiagnosis. This study verifies the diagnostic significance of the background information using a clinical dataset.Consequently, the Prior Difference Guidance Network (PDGNet) is proposed, merging decoupled lesion andbackground information via the Prior Normalization Fusion (PNF) strategy and the Feature Difference Guidance(FDG) module, to direct the model to concentrate on beneficial regions for diagnosis. Extensive experiments inthe clinical dataset demonstrate that the proposed method achieves promising diagnosis performance: PDGNetsbased on conventional networks record an ACC (Accuracy) and AUC (Area Under the Curve) of 87.50% and89.98%, marking improvements of 8.19% and 7.64% over the prior-free benchmark. Compared to lesion-focusedbenchmarks, the uplift is 6.14% and 6.02%. PDGNets based on advanced networks reach an ACC and AUC of89.77% and 92.80%. The study underscores the potential of harnessing background information in medical imagediagnosis, suggesting a more holistic view for future research.

Investigation on Binding between Cations and Amides using UV Raman Spectroscopy

The interaction of proteins with salt ions plays an important role in life activities.We used butyramide as a model molecule to investigate the interaction of protein backbones with cations.The experiment was performed in an aqueous solution of metal chloride using UV Raman spectroscopy.It was found that well-hydrated metal cations(Ca^(2+),Mg^(2+))tend to bind to C=O in the amide bond,resulting in redistribution of the amide I band peaks.Specifically,the peak intensity ratio of 1655 cm^(-1)to 1610 cm^(-1)increases significantly with increasing concentrations.However,this phenomenon is not obviously observed in NaCl solution.Furthermore,we studied the effect of salt ions on the water structures.The addition of Ca^(2+)and Mg^(2+)is beneficial to the enhancement of the water signal at the 3400 cm^(-1)position,while the Na^(+)at the same concentration is not obvious.The results have shown that the interaction between cations and amides satisfies the following order:Ca^(2+)>Mg^(2+)>Na^(+),which conforms to the Hofmeister series.

Wireless Positioning:Technologies,Applications,Challenges,and Future Development Trends

The development of the fifth-generation(5G)mobile communication systems has entered the commercialization stage.5G has a high data rate,low latency,and high reliability that can meet the basic demands of most industries and daily life,such as the Internet of Things(IoT),intelligent transportation systems,positioning,and navigation.The continuous progress and development of society have aroused wide concern.Positioning accuracy is the core demand for the applications,especially in complex environments such as airports,warehouses,supermarkets,and basements.However,many factors also affect the accuracy of positioning in those environments,for example,multipath effects,non-line-of-sight,and clock synchronization errors.This paper provides a comprehensive review of the existing works about positioning for the future wireless network and discusses its key techniques and algorithms,as well as the current development and future directions.We first outline the current traditional positioning technologies and algorithms,which are discussed and analyzed with the relevant literature.In addition,we also discuss application scenarios for wireless localization.By comparing different positioning systems,the challenges and future development directions of existing wireless positioning systems are prospected.