Global warming and energy crisis are two major challenges in the new-century.Wearable materials that enable all-seasonal self-adapting thermal comfort without additional energy-input attract significant attention as a...Global warming and energy crisis are two major challenges in the new-century.Wearable materials that enable all-seasonal self-adapting thermal comfort without additional energy-input attract significant attention as a solution to the increasing severity of extreme climate-change.Inspired by autologous temperature-regulation and multidimensional-sensing origins of nature-skin composed of nature collagen fibers,this study engineered a nanoscale wearable natural fibers-derived thermochromic material(TMEH-skin)for robust all-season self-adapting thermal management by tactically integrating traditional immersion and spraying methods with layer-by-layer stacking-strategy.Because of the on-demand multi-functional layer-structure design,TMEH-skin achieves spontaneous~38.16%visible lightmodulation and~95.1%infrared-emission,demonstrating outstanding double-self-switching thermal management origins by simple color-changing without additional energy-input.Moreover,TMEH-skin has gratifying tensile strength of 13.18 MPa,water vapor permeability,electrical-conductivity,and hydrophobicity,further broadening the application potential and scenarios as wearable materials.In applications for military-missions or reconnaissance behind enemy-lines,TMEH-skin robustly integrates the multi-functionalities of wearing-comfort,physiological signal-response capability for accurate transmission of Morse-code,and thermal management performances under special circumstances,indicating its tremendous potential for smart military-applications.Simulation results show that TMEH-skin has prominent energy-saving efficiency in cities with different climate zones.This study provides a new reference to the booming innovation of natural-derived wearable materials for all-seasonal self-adapting thermal management.展开更多
Typical p-n junctions have emerged as a promising strategy for contending with charge carrier recombination in solar conversion.However,the photo-corrosion and unsuitable energy band positions still hinder their pract...Typical p-n junctions have emerged as a promising strategy for contending with charge carrier recombination in solar conversion.However,the photo-corrosion and unsuitable energy band positions still hinder their practical application for hydrogen production from water in photoelectrochemical systems.Here,an in-situ photo-oxidation method is proposed for achieving self-adapting activation of BiVO_(4)-based photoanodes with surface-encapsulated CuGaS_(2)particles by the ZnO layer.The self-adapting activation demotes the energy band positions of CuGaS_(2),establishing an S-scheme structure with BiVO_(4),resulting in an efficient p-n junction photoanode.The optimal sample exhibits enhanced photocurrent and an onset potential cathodically shifted by~300 mV compared with BiVO_(4),which is attributed to significantly enhanced charge transport and transfer efficiencies.As expected,it attains the highest photocurrent value of 5.87 mA·cm^(-2),aided by a hole scavenger at 1.23 V versus a reversible hydrogen electrode,which significantly surpasses that of BiVO_(4)(4.32 mA·cm^(-2)).展开更多
This study systematically investigated the influence of deposition rate on the structure,broadband opti⁃cal properties(1.0-13.0μm),and stress characteristics of Germanium(Ge)films.Additionally,a method for enhancing ...This study systematically investigated the influence of deposition rate on the structure,broadband opti⁃cal properties(1.0-13.0μm),and stress characteristics of Germanium(Ge)films.Additionally,a method for enhancing the performance of infrared filters based on rate-modulated deposition of Ge films was proposed.The optical absorption of Ge films in the short-wave infrared(SWIR)and long-wave infrared(LWIR)bands can be effectively reduced by modulating the deposition rate.As the deposition rate increases,the Ge films maintain an amorphous structure.The optical constants of the films in the 1.0-2.5μm and 2.5-13.0μm bands were precisely determined using the Cody-Lorentz model and the classical Lorentz oscillator model,respectively.Notably,high⁃er deposition rates result in a gradual increase in the refractive index.The extinction coefficient increases with the deposition rate in the SWIR region,attributed to the widening of the Urbach tail,while it decreases in the LWIR region due to the reduced absorption caused by the Ge-O stretching mode.Additionally,the films exhibit a tensile stress that decreases with increasing deposition rate.Finally,the effectiveness of the proposed fabrication method for an infrared filter with Ge films deposited at an optimized rate was demonstrated through practical examples.This work provides theoretical and technical support for the application of Ge films in high-performance infrared filters.展开更多
The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recogni...The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recognized to be limited at data boundaries and high frequencies,which can significantly reduce the signal-to-noise ratio(SNR).To solve this problem,a novel method synergistically integrating Principal Component Analysis(PCA)with SG filtering is proposed in this paper.This approach avoids the is-sue of excessive smoothing associated with larger window sizes.The proposed PCA-SG filtering algorithm was applied to a CO gas sensing system based on Cavity Ring-Down Spectroscopy(CRDS).The perform-ance of the PCA-SG filtering algorithm is demonstrated through comparison with Moving Average Filtering(MAF),Wavelet Transformation(WT),Kalman Filtering(KF),and the SG filter.The results demonstrate that the proposed algorithm exhibits superior noise reduction capabilities compared to the other algorithms evaluated.The SNR of the ring-down signal was improved from 11.8612 dB to 29.0913 dB,and the stand-ard deviation of the extracted ring-down time constant was reduced from 0.037μs to 0.018μs.These results confirm that the proposed PCA-SG filtering algorithm effectively improves the smoothness of the ring-down curve data,demonstrating its feasibility.展开更多
An optimization model has been established and solved to determine the optimal threshold value for the event-triggered self-adaptive optimization strategy,which aims to strike a balance between optimization performanc...An optimization model has been established and solved to determine the optimal threshold value for the event-triggered self-adaptive optimization strategy,which aims to strike a balance between optimization performance and control load while ensuring continuous optimization.First,evaluation indicators are introduced to comprehensively analyze the impact of power fluctuations on the objective function and system voltage at both the system-wide and local levels.Based on these indicators,a multi-stage centralized optimization(MCO)is selectively applied,addressing system state deviations to achieve optimal operating states while maintaining a voltage security margin to ensure system safety.Then,distributed optimization(DO)is carried out at each bus with a renewable energy source or random load integration to accommodate short-term uncertainties using a self-adaptive reactive power algorithm.The optimal threshold value for event-triggered DO is calculated to balance control burden and optimization effectiveness.Utilizing the local state deviation evaluation indicator,unnecessary DOs are skipped when minor power fluctuations occur at the local level.Finally,following the linear superposition principle,event-triggered DOs executed at all distributed controllers collectively constitute the self-adaptive optimization strategy for the entire system.A case study on the IEEE New England 39-bus power system illustrates the effectiveness of the proposed strategy.展开更多
Accurate estimation of the State of Charge(SOC),State of Health(SOH),and Terminal Resistance(TR)is crucial for the effective operation of Battery Management Systems(BMS)in lithium-ion batteries.This study conducts a c...Accurate estimation of the State of Charge(SOC),State of Health(SOH),and Terminal Resistance(TR)is crucial for the effective operation of Battery Management Systems(BMS)in lithium-ion batteries.This study conducts a comprehensive comparative analysis of four Kalman filter variants Extended Kalman Filter(EKF),Extended Kalman-Bucy Filter(EKBF),Unscented Kalman Filter(UKF),and Unscented Kalman-Bucy Filter(UKBF)under varying battery parameter conditions.These include temperature fluctuation,self-discharge,current direction,cell capacity,process noise,and measurement noise.Our findings reveal significant variations in the performance of SOC and SOH predictions across filters,emphasizing that UKF demonstrates superior robustness to noise,while EKF performs better under accurate system dynamics.The study underscores the need for adaptive filtering strategies that can dynamically adjust to evolving battery parameters,thereby enhancing BMS reliability and extending battery lifespan.展开更多
1 Introduction Recently,the increasing demand for advanced telecommunication systems has spurred extensive research into bandpass filters(BPFs),with particular emphasis on miniaturization,reduction of insertion loss(I...1 Introduction Recently,the increasing demand for advanced telecommunication systems has spurred extensive research into bandpass filters(BPFs),with particular emphasis on miniaturization,reduction of insertion loss(IL),and enhancement of upper stopband rejection(Huang et al.,2021;Snyder et al.,2021;Lin et al.,2023;Zeng et al.,2023).展开更多
Octopuses,due to their flexible arms,marvelous adaptability,and powerful suckers,are able to effortlessly grasp and disengage various objects in the marine surrounding without causing devastation.However,manipulating ...Octopuses,due to their flexible arms,marvelous adaptability,and powerful suckers,are able to effortlessly grasp and disengage various objects in the marine surrounding without causing devastation.However,manipulating delicate objects such as soft and fragile foods underwater require gentle contact and stable adhesion,which poses a serious challenge to now available soft grippers.Inspired by the sucker infundibulum structure and flexible tentacles of octopus,herein we developed a hydraulically actuated hydrogel soft gripper with adaptive maneuverability by coupling multiple hydrogen bond-mediated supramolecular hydrogels and vat polymerization three-dimensional printing,in which hydrogel bionic sucker is composed of a tunable curvature membrane,a negative pressure cavity,and a pneumatic chamber.The design of the sucker structure with the alterable curvature membrane is conducive to realize the reliable and gentle switchable adhesion of the hydrogel soft gripper.As a proof-of-concept,the adaptive hydrogel soft gripper is capable of implement diversified underwater tasks,including gingerly grasping fragile foods like egg yolks and tofu,as well as underwater robots and vehicles that station-keeping and crawling based on switchable adhesion.This study therefore provides a transformative strategy for the design of novel soft grippers that will render promising utilities for underwater exploration soft robotics.展开更多
In this study,a fifth-degree cubature particle filter(5CPF)is proposed to address the limited estimation accuracy in traditional particle filter algorithms for bearings-only tracking(BOT).This algorithm calculates the...In this study,a fifth-degree cubature particle filter(5CPF)is proposed to address the limited estimation accuracy in traditional particle filter algorithms for bearings-only tracking(BOT).This algorithm calculates the recommended density function by introducing a fifth-degree cubature Kalman filter algorithm to guide particle sampling,which effectively alleviates the problem of particle degradation and significantly improves the estimation accuracy of the filter.However,the 5CPF algorithm exhibits high computational complexity,particularly in scenarios with a large number of particles.Therefore,we propose the extended Kalman filter(EKF)-5CPF algorithm,which employs an EKF to replace the time update step for each particle in the 5CPF.This enhances the algorithm’s real-time capability while maintaining the high precision advantage of the 5CPF algorithm.In addition,we construct bearing-only dual-station and single-motion station target tracking systems,and the filtering performances of 5CPF and EKF-5CPF algorithms under different conditions are analyzed.The results show that both the 5CPF algorithm and EKF-5CPF have strong robustness and can adapt to different noise environments.Furthermore,both algorithms significantly outperform traditional nonlinear filtering algorithms in terms of convergence speed,tracking accuracy,and overall stability.展开更多
Color filters are essential components for optical modulation.However,conventional filters are restricted to operating exclusively in either reflective or transmissive mode.Furthermore,they suffer from limited UV and ...Color filters are essential components for optical modulation.However,conventional filters are restricted to operating exclusively in either reflective or transmissive mode.Furthermore,they suffer from limited UV and thermal stability,low color purity,and exhibit identical coloration on both surfaces.Herein,we propose a novel design strategy for trans-reflective color filters by integrating the absorptive properties of dye-doped polysulfone(PSU)with the diffractive capabilities of photonic crystals.This composite filter achieved broad-spectrum transmission with deep color outputs—yellow(0.410,0.510),magenta(0.446,0.231),and cyan(0.201,0.425)—closely aligned with standard color space coordinates.By tuning the refractive index of CeO_(2)@SiO_(2)nanoparticles to match dye-based PSU matrix,the transmittance of filters exceeded 70%.Moreover,dye-mediated absorption reduces the scattering light,thereby enhancing reflection color purity(full width at half maxima(FWHM)=25 nm)and producing vibrant blue,green,and red hues.The incorporation of UV-absorbing CeO_(2)@SiO_(2)nanoparticles effectively mitigated dye photodegradation,yielding exceptional UV stability(ΔT<2%under prolonged UV exposure).The filters also exhibited outstanding thermal stability(ΔT<1%after 30 min heat treatment at 230°C).This work establishes a robust materials design framework for multifunctional optical filters,advancing the development of highfidelity dual-mode color systems for next-generation display technologies.展开更多
Recommendation systems are an integral and indispensable part of every digital platform,as they can suggest content or items to users based on their respective needs.Collaborative filtering is a technique often used i...Recommendation systems are an integral and indispensable part of every digital platform,as they can suggest content or items to users based on their respective needs.Collaborative filtering is a technique often used in various studies,which produces recommendations by analyzing similarities between users and items based on their behavior.Although often used,traditional collaborative filtering techniques still face the main challenge of sparsity.Sparsity problems occur when the data in the system is sparse,meaning that only a portion of users provide feedback on some items,resulting in inaccurate recommendations generated by the system.To overcome this problem,we developed aHybrid Collaborative Filtering model based onMatrix Factorization andGradient Boosting(HCF-MFGB),a new hybrid approach.Our proposed model integrates SVD++,the XGBoost ensemble learning algorithm,and utilizes user demographic data and meta items.We utilize information,both explicitly and implicitly,to learn user preference patterns using SVD++.The XGBoost algorithm is used to create hundreds of decision trees incrementally,thereby improving model accuracy.Meanwhile,user demographic and meta-item data are clustered using the K-Means Clustering algorithm to capture similarities in user and item characteristics.This combination is designed to improve rating prediction accuracy by reducing reliance on minimal explicit rating data,while addressing sparsity issues in movie recommendation systems.The results of experiments on the MovieLens 100K,MovieLens 1M,and CiaoDVD datasets show significant improvements,outperforming various other baselinemodels in terms of RMSE and MAE.On theMovieLens 100K dataset,the HCF-MFGB model obtained an RMSE value of 0.853 and an MAE value of 0.674.On theMovieLens 1M dataset,the HCF-MFGB model obtained an RMSE value of 0.763 and an MAE value of 0.61.On the CiaoDCD dataset,the HCF-MFGB model achieved an RMSE value of 0.718 and an MAE value of 0.495.These results confirm a significant improvement in movie recommendation accuracy with the proposed approach.展开更多
This article presents an adaptive intelligent control strategy applied to a lumped-parameter evaporator model,i.e.,a simplified dynamic representation treating the evaporator as a single thermal node with uniform temp...This article presents an adaptive intelligent control strategy applied to a lumped-parameter evaporator model,i.e.,a simplified dynamic representation treating the evaporator as a single thermal node with uniform temperature distribution,suitable for control design due to its balance between physical fidelity and computational simplicity.The controller uses a wavelet-based neural proportional,integral,derivative(PID)controller with IIR filtering(infinite impulse response).The dynamic model captures the essential heat and mass transfer phenomena through a nonlinear energy balance,where the cooling capacity“Qevap”is expressed as a non-linear function of the compressor frequency and the temperature difference,specifically,Q_(evap)=k_(1)u(T_(in)−T_(e))with u as compressor frequency,Te evaporator temperature,and Tin inlet fluid temperature.The operating conditions of the system,in general terms,focus on the following variables,the overall thermal capacity is 1000 J/K,typical for small-capacity heat exchangers,The mass flow is 0.05 kg/s,typical for secondary liquid cooling circuits,the overall loss coefficient of 50 W/K that corresponds to small evaporators with partial insulation,the temperatures(inlet)of 10℃and the temperature of environment of 25℃,thermal load of 200 W that corresponds to a small-scaled air conditioning applications.To handle system nonlinearities and improve control performance,aMorlet wavelet-based neural network(Wavenet)is used to dynamically adjust the PID gains online.An IIR filter is incorporated to smooth the adaptive gains,improving stability and reducing oscillations.In contrast to prior wavelet-or neural-adaptive PID controllers in HVAC applications,which typically adjust gains without explicit filtering or not tailored to evaporator dynamics,this work introduces the first PID–Wavenet scheme augmented with an IIR-based stabilization layer,specifically designed to address the combined challenges of nonlinear evaporator behavior,gain oscillation,and real-time implementability.The proposed controller(PID-Wavenet+IIR)is implemented and validated inMATLAB/Simulink,demonstrating superior performance compared to a conventional PID tuned using Simulink’s auto-tuning function.Key results include a reduction in settling time from 13.3 to 8.2 s,a reduction in overshoot from 3.5%to 0.8%,a reduction in steady-state error from 0.12℃ to 0.02℃and a 13%reduction in energy overall consumption.The controller also exhibits greater robustness and adaptability under varying thermal loads.This explicit integration of wavelet-driven adaptation with IIR-filtered gain shaping constitutes the main methodological contribution and novelty of the work.These findings validate the effectiveness of the wavelet-based adaptive approach for advanced thermal management in refrigeration and HVAC systems,with potential applications in controlling variable-speed compressors,liquid chillers,and compact cooling units.展开更多
This article proposes a generalized strongly coupled resonator quartet(GSCRQ)filter along with its synthesis approach.By introducing out-of-band reflection zeros(RZs),the proposed GSCRQ can generate a transmission zer...This article proposes a generalized strongly coupled resonator quartet(GSCRQ)filter along with its synthesis approach.By introducing out-of-band reflection zeros(RZs),the proposed GSCRQ can generate a transmission zero on each side of the passband without negative couplings.The coupling coefficients in this coupling structure change with the positions of the out-of-band RZs.Thus,the GSCRQ configuration admits flexible design solutions.For GSCRQ coaxial combline filters,all couplings can be implemented as inductive couplings,simplifying the design and manufacturing process.In this article,a 6-2 filter in the GSCRQ configuration is synthesized and designed.The simulated results of the designed filter agree very well with the theoretical characteristics.展开更多
Deep graph contrastive clustering has attracted widespread attentions due to its self-supervised representation learning paradigm and superior clustering performance.Although,two challenges emerge and result in high c...Deep graph contrastive clustering has attracted widespread attentions due to its self-supervised representation learning paradigm and superior clustering performance.Although,two challenges emerge and result in high computational costs.Most existing contrastive methods adopt the data augmentation and then representation learning strategy,where representation learning with trainable graph convolution is coupled with complex and fixed data augmentation,inevitably limiting the efficiency and flexibility.The similarity metric between positive-negative sample pairs is complex and contrastive objective is partial,limiting the discriminability of representation learning.To solve these challenges,a novel wide graph clustering network(WGCN)adhering to representation and then augmentation framework is proposed,which mainly consists of multiorder filter fusion(MFF)and double-level contrastive learning(DCL)modules.Specifically,the MFF module integrates multiorder low-pass filters to extract smooth and multi-scale topological features,utilizing self-attention fusion to reduce redundancy and obtain comprehensive embedding representation.Further,the DCL module constructs two augmented views by the parallel parameter-unshared Siamese encoders rather than complex augmentations on graph.To achieve simple yet effective self-supervised learning,representation self-supervision and structural consistency oriented double-level contrastive loss is designed,where representation self-supervision maximizes the agreement between pairwise augmented embedding representations and structural consistency promotes the mutual information correlation between appending neighborhoods with similar semantics.Extensive experiments on six benchmark datasets demonstrate the superiority of the proposed WGCN,especially highlighting its time-saving characteristic.The code could be available in the https://github.com/Tianxiang Zhao0474/WGCN.展开更多
Gassmann＇s equations are commonly used for predicting seismic wave velocity in rock physics research.However the input matrix mineral bulk modulus parameters are not accurate,which greatly influences the prediction r...Gassmann＇s equations are commonly used for predicting seismic wave velocity in rock physics research.However the input matrix mineral bulk modulus parameters are not accurate,which greatly influences the prediction reliability.In this paper,combining the Russell fluid factor with the Gassman-Biot-Geertsma equation and introducing the dry-rock Poisson＇s ratio,we propose an effective matrix mineral bulk modulus extraction method.This method can adaptively invert the equivalent matrix mineral bulk modulus to apply the Gassmann equation to fluid substitution of complex carbonate reservoirs and increase the fluid prediction reliability.The verification of the actual material fluid substitution also shows that this method is reliable,efficient,and adaptable.展开更多
On the basis ofa 2D 4-node Mindlin shell element method, a novel self-adapting delamination finite element method is presented, which is developed to model the delamination damage of composite laminates. In the method...On the basis ofa 2D 4-node Mindlin shell element method, a novel self-adapting delamination finite element method is presented, which is developed to model the delamination damage of composite laminates. In the method, the sublaminate elements are generated automatically when the delamination damage occurs or extends. Thus, the complex process and state of delamination damage can be simulated practically with high efficiency for both analysis and modeling. Based on the self-adapting delamination method, linear dynamic finite element damage analysis is performed to simulate the low-velocity impact damage process of three types of mixed woven composite laminates. Taking the frictional force among sublaminations during delaminating and the transverse normal stress into account, the analytical results are consistent with those of the experimental data.展开更多
Control parameters of original differential evolution （DE） are kept fixed throughout the entire evolutionary process. However, it is not an easy task to properly set control parameters in DE for different optiinizat...Control parameters of original differential evolution （DE） are kept fixed throughout the entire evolutionary process. However, it is not an easy task to properly set control parameters in DE for different optiinization problems. According to the relative position of two different individual vectors selected to generate a difference vector in the searching place, a self-adapting strategy for the scale factor F of the difference vector is proposed. In terms of the convergence status of the target vector in the current population, a self-adapting crossover probability constant CR strategy is proposed. Therefore, good target vectors have a lower CFI while worse target vectors have a large CFI. At the same time, the mutation operator is modified to improve the convergence speed. The performance of these proposed approaches are studied with the use of some benchmark problems and applied to the trajectory planning of a three-joint redundant manipulator. Finally, the experiment results show that the proposed approaches can greatly improve robustness and convergence speed.展开更多
The basie idea and method about determination of the feature line equations and how to apply them to the numerical control of the press bending of panei skins were introduced. Research indicates that it is feasible to...The basie idea and method about determination of the feature line equations and how to apply them to the numerical control of the press bending of panei skins were introduced. Research indicates that it is feasible to realize the self adapting incremental press bending by adopting the feature line equation. The feature line equation, which is based on the database of the status of practical processes, can be adjusted in time, and the forming precision can be improved. It is important to correctly select and reasonably predict the feature line equations to enhance the accuracy of the incremental press bending based on the feature line database and algorithm. The determination of the feature line equation settles necessary data foundation for further research on the database of self-adapting incremental press bending, and it supplies a new clue for the development of self-adapting incremental press bending.展开更多
An improved ensemble empirical mode decomposition(EEMD) algorithm is described in this work, in which the sifting and ensemble number are self-adaptive. In particular, the new algorithm can effectively avoid the mode ...An improved ensemble empirical mode decomposition(EEMD) algorithm is described in this work, in which the sifting and ensemble number are self-adaptive. In particular, the new algorithm can effectively avoid the mode mixing problem. The algorithm has been validated with a simulation signal and locomotive bearing vibration signal. The results show that the proposed self-adaptive EEMD algorithm has a better filtering performance compared with the conventional EEMD. The filter results further show that the feature of the signal can be distinguished clearly with the proposed algorithm, which implies that the fault characteristics of the locomotive bearing can be detected successfully.展开更多
Practical implementations of rechargeable lithium(Li)metal batteries have long been plagued by multiple problems of Li anode,such as Li dendrite growth,large volume change,low Coulombic efficiency.Here,we report a pro...Practical implementations of rechargeable lithium(Li)metal batteries have long been plagued by multiple problems of Li anode,such as Li dendrite growth,large volume change,low Coulombic efficiency.Here,we report a protein-enabled film that can provide effective protection for Li metal.The protective film with an integrated design of high flexibility,strong adhesion and high Li-ion transference number(0.80)is fabricated by incorporating denatured zein(corn protein)with polyethylene oxide(PEO)acting as an age nt for sustaining the denatured protein chains against refolding via the intermolecular interactions between them.Thus,a conformable zein-enabled protective film(zein@PEO)with simultaneous en hancement in flexibility,modulus and adhesion strength is gen erated to offer both functi ons of self-adapting and anion-anchoring abilities.The results show that the zein@PEO film is able to accommodate the volume change,reduce the side reactions,and homogenize the ion deposition.Benefiting from these significant properties/fu nctions,the Li/Cu cell with the zein@PEO film delivers prolonged cycle life for over 500 hours with stable performance.Paired with LiMn_(2)O_(4) cathode,the capacity,cycle stability and rate performance of the cell are remarkably improved as well,demonstrati ng the effectiveness in stabilizing Li metal batteries.展开更多
基金the Institute of Biomass&Functional Materials of Shaanxi University of Science and Technology for funding this research workfinancially supported by the National Natural Science Foundation of China(2207081675,22278257,22308209)+1 种基金the Key R&D Program of Shaanxi Province(2024SF-YBXM-586)the Project of Innovation Capability Support Program in Shaanxi Province(2024ZC-KJXX-005)。
文摘Global warming and energy crisis are two major challenges in the new-century.Wearable materials that enable all-seasonal self-adapting thermal comfort without additional energy-input attract significant attention as a solution to the increasing severity of extreme climate-change.Inspired by autologous temperature-regulation and multidimensional-sensing origins of nature-skin composed of nature collagen fibers,this study engineered a nanoscale wearable natural fibers-derived thermochromic material(TMEH-skin)for robust all-season self-adapting thermal management by tactically integrating traditional immersion and spraying methods with layer-by-layer stacking-strategy.Because of the on-demand multi-functional layer-structure design,TMEH-skin achieves spontaneous~38.16%visible lightmodulation and~95.1%infrared-emission,demonstrating outstanding double-self-switching thermal management origins by simple color-changing without additional energy-input.Moreover,TMEH-skin has gratifying tensile strength of 13.18 MPa,water vapor permeability,electrical-conductivity,and hydrophobicity,further broadening the application potential and scenarios as wearable materials.In applications for military-missions or reconnaissance behind enemy-lines,TMEH-skin robustly integrates the multi-functionalities of wearing-comfort,physiological signal-response capability for accurate transmission of Morse-code,and thermal management performances under special circumstances,indicating its tremendous potential for smart military-applications.Simulation results show that TMEH-skin has prominent energy-saving efficiency in cities with different climate zones.This study provides a new reference to the booming innovation of natural-derived wearable materials for all-seasonal self-adapting thermal management.
基金supported by the open fund from Key Lab of Eco-restoration of Regional Contaminated Environment(Shenyang University),Ministry of Education(No.KF-22-08)the National Natural Science Foundation of China(Nos.22003074 and 42177406)+1 种基金the Youth Innovation Promotion Association CAS,Guangdong Basic and Applied Basic Research Foundation(No.2023A1515011410)S.Liu gratefully acknowledges the financial support by the National Natural Science Foundation of China(No.52302223).
文摘Typical p-n junctions have emerged as a promising strategy for contending with charge carrier recombination in solar conversion.However,the photo-corrosion and unsuitable energy band positions still hinder their practical application for hydrogen production from water in photoelectrochemical systems.Here,an in-situ photo-oxidation method is proposed for achieving self-adapting activation of BiVO_(4)-based photoanodes with surface-encapsulated CuGaS_(2)particles by the ZnO layer.The self-adapting activation demotes the energy band positions of CuGaS_(2),establishing an S-scheme structure with BiVO_(4),resulting in an efficient p-n junction photoanode.The optimal sample exhibits enhanced photocurrent and an onset potential cathodically shifted by~300 mV compared with BiVO_(4),which is attributed to significantly enhanced charge transport and transfer efficiencies.As expected,it attains the highest photocurrent value of 5.87 mA·cm^(-2),aided by a hole scavenger at 1.23 V versus a reversible hydrogen electrode,which significantly surpasses that of BiVO_(4)(4.32 mA·cm^(-2)).
基金Supported by the National Natural Science Foundation of China(62275053,62275256)the National key Research and Development Program of China(2021YFB3701500)+1 种基金the Youth Innovation Promotion Association of the Chinese Academy of Sciences(2023248)the Eastern Talent Plan Youth Project 2022,the Shanghai Key Laboratory of Optical Coatings and Spectral Modulation(23dz2260500).
文摘This study systematically investigated the influence of deposition rate on the structure,broadband opti⁃cal properties(1.0-13.0μm),and stress characteristics of Germanium(Ge)films.Additionally,a method for enhancing the performance of infrared filters based on rate-modulated deposition of Ge films was proposed.The optical absorption of Ge films in the short-wave infrared(SWIR)and long-wave infrared(LWIR)bands can be effectively reduced by modulating the deposition rate.As the deposition rate increases,the Ge films maintain an amorphous structure.The optical constants of the films in the 1.0-2.5μm and 2.5-13.0μm bands were precisely determined using the Cody-Lorentz model and the classical Lorentz oscillator model,respectively.Notably,high⁃er deposition rates result in a gradual increase in the refractive index.The extinction coefficient increases with the deposition rate in the SWIR region,attributed to the widening of the Urbach tail,while it decreases in the LWIR region due to the reduced absorption caused by the Ge-O stretching mode.Additionally,the films exhibit a tensile stress that decreases with increasing deposition rate.Finally,the effectiveness of the proposed fabrication method for an infrared filter with Ge films deposited at an optimized rate was demonstrated through practical examples.This work provides theoretical and technical support for the application of Ge films in high-performance infrared filters.
文摘The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recognized to be limited at data boundaries and high frequencies,which can significantly reduce the signal-to-noise ratio(SNR).To solve this problem,a novel method synergistically integrating Principal Component Analysis(PCA)with SG filtering is proposed in this paper.This approach avoids the is-sue of excessive smoothing associated with larger window sizes.The proposed PCA-SG filtering algorithm was applied to a CO gas sensing system based on Cavity Ring-Down Spectroscopy(CRDS).The perform-ance of the PCA-SG filtering algorithm is demonstrated through comparison with Moving Average Filtering(MAF),Wavelet Transformation(WT),Kalman Filtering(KF),and the SG filter.The results demonstrate that the proposed algorithm exhibits superior noise reduction capabilities compared to the other algorithms evaluated.The SNR of the ring-down signal was improved from 11.8612 dB to 29.0913 dB,and the stand-ard deviation of the extracted ring-down time constant was reduced from 0.037μs to 0.018μs.These results confirm that the proposed PCA-SG filtering algorithm effectively improves the smoothness of the ring-down curve data,demonstrating its feasibility.
基金supported in part by National Key R&D Program of China(2022YFF0610600).
文摘An optimization model has been established and solved to determine the optimal threshold value for the event-triggered self-adaptive optimization strategy,which aims to strike a balance between optimization performance and control load while ensuring continuous optimization.First,evaluation indicators are introduced to comprehensively analyze the impact of power fluctuations on the objective function and system voltage at both the system-wide and local levels.Based on these indicators,a multi-stage centralized optimization(MCO)is selectively applied,addressing system state deviations to achieve optimal operating states while maintaining a voltage security margin to ensure system safety.Then,distributed optimization(DO)is carried out at each bus with a renewable energy source or random load integration to accommodate short-term uncertainties using a self-adaptive reactive power algorithm.The optimal threshold value for event-triggered DO is calculated to balance control burden and optimization effectiveness.Utilizing the local state deviation evaluation indicator,unnecessary DOs are skipped when minor power fluctuations occur at the local level.Finally,following the linear superposition principle,event-triggered DOs executed at all distributed controllers collectively constitute the self-adaptive optimization strategy for the entire system.A case study on the IEEE New England 39-bus power system illustrates the effectiveness of the proposed strategy.
基金supported by the Royal Academy of Engineering,UK,in the scheme of Distinguished International Associate(DIA-2424-5-134).
文摘Accurate estimation of the State of Charge(SOC),State of Health(SOH),and Terminal Resistance(TR)is crucial for the effective operation of Battery Management Systems(BMS)in lithium-ion batteries.This study conducts a comprehensive comparative analysis of four Kalman filter variants Extended Kalman Filter(EKF),Extended Kalman-Bucy Filter(EKBF),Unscented Kalman Filter(UKF),and Unscented Kalman-Bucy Filter(UKBF)under varying battery parameter conditions.These include temperature fluctuation,self-discharge,current direction,cell capacity,process noise,and measurement noise.Our findings reveal significant variations in the performance of SOC and SOH predictions across filters,emphasizing that UKF demonstrates superior robustness to noise,while EKF performs better under accurate system dynamics.The study underscores the need for adaptive filtering strategies that can dynamically adjust to evolving battery parameters,thereby enhancing BMS reliability and extending battery lifespan.
基金supported by the National Natural Science Foundation of China(No.62371263)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.SJCK25_1995).
文摘1 Introduction Recently,the increasing demand for advanced telecommunication systems has spurred extensive research into bandpass filters(BPFs),with particular emphasis on miniaturization,reduction of insertion loss(IL),and enhancement of upper stopband rejection(Huang et al.,2021;Snyder et al.,2021;Lin et al.,2023;Zeng et al.,2023).
基金the financial support from the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB0470303)the National Key Research and Development Program of China (2022YFB4600101)+5 种基金the National Natural Science Foundation of China (52175201)the Research Program of Science and Technology Department of Gansu Province (24JRRA059, 24JRRA044, and 24YFFA014)the Science Fund of Shandong Laboratory of Advanced Materials and Green Manufacturing at Yantai (AMGM2024F12)the Major Program (ZYFZFX-2) of the Lanzhou Institute of Chemical Physics, CASthe Special Research Assistant Project of the Chinese Academy of Sciencesthe Oasis Scholar of Shihezi University
文摘Octopuses,due to their flexible arms,marvelous adaptability,and powerful suckers,are able to effortlessly grasp and disengage various objects in the marine surrounding without causing devastation.However,manipulating delicate objects such as soft and fragile foods underwater require gentle contact and stable adhesion,which poses a serious challenge to now available soft grippers.Inspired by the sucker infundibulum structure and flexible tentacles of octopus,herein we developed a hydraulically actuated hydrogel soft gripper with adaptive maneuverability by coupling multiple hydrogen bond-mediated supramolecular hydrogels and vat polymerization three-dimensional printing,in which hydrogel bionic sucker is composed of a tunable curvature membrane,a negative pressure cavity,and a pneumatic chamber.The design of the sucker structure with the alterable curvature membrane is conducive to realize the reliable and gentle switchable adhesion of the hydrogel soft gripper.As a proof-of-concept,the adaptive hydrogel soft gripper is capable of implement diversified underwater tasks,including gingerly grasping fragile foods like egg yolks and tofu,as well as underwater robots and vehicles that station-keeping and crawling based on switchable adhesion.This study therefore provides a transformative strategy for the design of novel soft grippers that will render promising utilities for underwater exploration soft robotics.
基金Supported by the Guangxi Special Program for Technological Innovation Guidance(No.GuiKeAC25069006).
文摘In this study,a fifth-degree cubature particle filter(5CPF)is proposed to address the limited estimation accuracy in traditional particle filter algorithms for bearings-only tracking(BOT).This algorithm calculates the recommended density function by introducing a fifth-degree cubature Kalman filter algorithm to guide particle sampling,which effectively alleviates the problem of particle degradation and significantly improves the estimation accuracy of the filter.However,the 5CPF algorithm exhibits high computational complexity,particularly in scenarios with a large number of particles.Therefore,we propose the extended Kalman filter(EKF)-5CPF algorithm,which employs an EKF to replace the time update step for each particle in the 5CPF.This enhances the algorithm’s real-time capability while maintaining the high precision advantage of the 5CPF algorithm.In addition,we construct bearing-only dual-station and single-motion station target tracking systems,and the filtering performances of 5CPF and EKF-5CPF algorithms under different conditions are analyzed.The results show that both the 5CPF algorithm and EKF-5CPF have strong robustness and can adapt to different noise environments.Furthermore,both algorithms significantly outperform traditional nonlinear filtering algorithms in terms of convergence speed,tracking accuracy,and overall stability.
基金supported by the Program of the National Natural Science Foundation of China(22238002)the Fundamental Research Funds for the Central Universities(DUT22-LAB610)Research and Innovation Team Project of Dalian University of Technology(DUT2022TB10).
文摘Color filters are essential components for optical modulation.However,conventional filters are restricted to operating exclusively in either reflective or transmissive mode.Furthermore,they suffer from limited UV and thermal stability,low color purity,and exhibit identical coloration on both surfaces.Herein,we propose a novel design strategy for trans-reflective color filters by integrating the absorptive properties of dye-doped polysulfone(PSU)with the diffractive capabilities of photonic crystals.This composite filter achieved broad-spectrum transmission with deep color outputs—yellow(0.410,0.510),magenta(0.446,0.231),and cyan(0.201,0.425)—closely aligned with standard color space coordinates.By tuning the refractive index of CeO_(2)@SiO_(2)nanoparticles to match dye-based PSU matrix,the transmittance of filters exceeded 70%.Moreover,dye-mediated absorption reduces the scattering light,thereby enhancing reflection color purity(full width at half maxima(FWHM)=25 nm)and producing vibrant blue,green,and red hues.The incorporation of UV-absorbing CeO_(2)@SiO_(2)nanoparticles effectively mitigated dye photodegradation,yielding exceptional UV stability(ΔT<2%under prolonged UV exposure).The filters also exhibited outstanding thermal stability(ΔT<1%after 30 min heat treatment at 230°C).This work establishes a robust materials design framework for multifunctional optical filters,advancing the development of highfidelity dual-mode color systems for next-generation display technologies.
基金funded by the Directorate General of Research and Development,Ministry of Higher Education,Science and Technology of the Republic of Indonesia,with grant number 2.6.63/UN32.14.1/LT/2025.
文摘Recommendation systems are an integral and indispensable part of every digital platform,as they can suggest content or items to users based on their respective needs.Collaborative filtering is a technique often used in various studies,which produces recommendations by analyzing similarities between users and items based on their behavior.Although often used,traditional collaborative filtering techniques still face the main challenge of sparsity.Sparsity problems occur when the data in the system is sparse,meaning that only a portion of users provide feedback on some items,resulting in inaccurate recommendations generated by the system.To overcome this problem,we developed aHybrid Collaborative Filtering model based onMatrix Factorization andGradient Boosting(HCF-MFGB),a new hybrid approach.Our proposed model integrates SVD++,the XGBoost ensemble learning algorithm,and utilizes user demographic data and meta items.We utilize information,both explicitly and implicitly,to learn user preference patterns using SVD++.The XGBoost algorithm is used to create hundreds of decision trees incrementally,thereby improving model accuracy.Meanwhile,user demographic and meta-item data are clustered using the K-Means Clustering algorithm to capture similarities in user and item characteristics.This combination is designed to improve rating prediction accuracy by reducing reliance on minimal explicit rating data,while addressing sparsity issues in movie recommendation systems.The results of experiments on the MovieLens 100K,MovieLens 1M,and CiaoDVD datasets show significant improvements,outperforming various other baselinemodels in terms of RMSE and MAE.On theMovieLens 100K dataset,the HCF-MFGB model obtained an RMSE value of 0.853 and an MAE value of 0.674.On theMovieLens 1M dataset,the HCF-MFGB model obtained an RMSE value of 0.763 and an MAE value of 0.61.On the CiaoDCD dataset,the HCF-MFGB model achieved an RMSE value of 0.718 and an MAE value of 0.495.These results confirm a significant improvement in movie recommendation accuracy with the proposed approach.
文摘This article presents an adaptive intelligent control strategy applied to a lumped-parameter evaporator model,i.e.,a simplified dynamic representation treating the evaporator as a single thermal node with uniform temperature distribution,suitable for control design due to its balance between physical fidelity and computational simplicity.The controller uses a wavelet-based neural proportional,integral,derivative(PID)controller with IIR filtering(infinite impulse response).The dynamic model captures the essential heat and mass transfer phenomena through a nonlinear energy balance,where the cooling capacity“Qevap”is expressed as a non-linear function of the compressor frequency and the temperature difference,specifically,Q_(evap)=k_(1)u(T_(in)−T_(e))with u as compressor frequency,Te evaporator temperature,and Tin inlet fluid temperature.The operating conditions of the system,in general terms,focus on the following variables,the overall thermal capacity is 1000 J/K,typical for small-capacity heat exchangers,The mass flow is 0.05 kg/s,typical for secondary liquid cooling circuits,the overall loss coefficient of 50 W/K that corresponds to small evaporators with partial insulation,the temperatures(inlet)of 10℃and the temperature of environment of 25℃,thermal load of 200 W that corresponds to a small-scaled air conditioning applications.To handle system nonlinearities and improve control performance,aMorlet wavelet-based neural network(Wavenet)is used to dynamically adjust the PID gains online.An IIR filter is incorporated to smooth the adaptive gains,improving stability and reducing oscillations.In contrast to prior wavelet-or neural-adaptive PID controllers in HVAC applications,which typically adjust gains without explicit filtering or not tailored to evaporator dynamics,this work introduces the first PID–Wavenet scheme augmented with an IIR-based stabilization layer,specifically designed to address the combined challenges of nonlinear evaporator behavior,gain oscillation,and real-time implementability.The proposed controller(PID-Wavenet+IIR)is implemented and validated inMATLAB/Simulink,demonstrating superior performance compared to a conventional PID tuned using Simulink’s auto-tuning function.Key results include a reduction in settling time from 13.3 to 8.2 s,a reduction in overshoot from 3.5%to 0.8%,a reduction in steady-state error from 0.12℃ to 0.02℃and a 13%reduction in energy overall consumption.The controller also exhibits greater robustness and adaptability under varying thermal loads.This explicit integration of wavelet-driven adaptation with IIR-filtered gain shaping constitutes the main methodological contribution and novelty of the work.These findings validate the effectiveness of the wavelet-based adaptive approach for advanced thermal management in refrigeration and HVAC systems,with potential applications in controlling variable-speed compressors,liquid chillers,and compact cooling units.
基金supported by the National Natural Science Foundation of China under Grant No.62471366。
文摘This article proposes a generalized strongly coupled resonator quartet(GSCRQ)filter along with its synthesis approach.By introducing out-of-band reflection zeros(RZs),the proposed GSCRQ can generate a transmission zero on each side of the passband without negative couplings.The coupling coefficients in this coupling structure change with the positions of the out-of-band RZs.Thus,the GSCRQ configuration admits flexible design solutions.For GSCRQ coaxial combline filters,all couplings can be implemented as inductive couplings,simplifying the design and manufacturing process.In this article,a 6-2 filter in the GSCRQ configuration is synthesized and designed.The simulated results of the designed filter agree very well with the theoretical characteristics.
基金supported by the National Natural Science Foundation of China(62225303,62403043,62433004)the Beijing Natural Science Foundation(4244085)+1 种基金the Postdoctoral Fellowship Program of China Postdoctoral Science Foundation(GZC20230203)the China Postdoctoral Science Foundation(2023M740201)。
文摘Deep graph contrastive clustering has attracted widespread attentions due to its self-supervised representation learning paradigm and superior clustering performance.Although,two challenges emerge and result in high computational costs.Most existing contrastive methods adopt the data augmentation and then representation learning strategy,where representation learning with trainable graph convolution is coupled with complex and fixed data augmentation,inevitably limiting the efficiency and flexibility.The similarity metric between positive-negative sample pairs is complex and contrastive objective is partial,limiting the discriminability of representation learning.To solve these challenges,a novel wide graph clustering network(WGCN)adhering to representation and then augmentation framework is proposed,which mainly consists of multiorder filter fusion(MFF)and double-level contrastive learning(DCL)modules.Specifically,the MFF module integrates multiorder low-pass filters to extract smooth and multi-scale topological features,utilizing self-attention fusion to reduce redundancy and obtain comprehensive embedding representation.Further,the DCL module constructs two augmented views by the parallel parameter-unshared Siamese encoders rather than complex augmentations on graph.To achieve simple yet effective self-supervised learning,representation self-supervision and structural consistency oriented double-level contrastive loss is designed,where representation self-supervision maximizes the agreement between pairwise augmented embedding representations and structural consistency promotes the mutual information correlation between appending neighborhoods with similar semantics.Extensive experiments on six benchmark datasets demonstrate the superiority of the proposed WGCN,especially highlighting its time-saving characteristic.The code could be available in the https://github.com/Tianxiang Zhao0474/WGCN.
基金sponsored by National Natural Science Foundation of China(Grant No.40904035)
文摘Gassmann＇s equations are commonly used for predicting seismic wave velocity in rock physics research.However the input matrix mineral bulk modulus parameters are not accurate,which greatly influences the prediction reliability.In this paper,combining the Russell fluid factor with the Gassman-Biot-Geertsma equation and introducing the dry-rock Poisson＇s ratio,we propose an effective matrix mineral bulk modulus extraction method.This method can adaptively invert the equivalent matrix mineral bulk modulus to apply the Gassmann equation to fluid substitution of complex carbonate reservoirs and increase the fluid prediction reliability.The verification of the actual material fluid substitution also shows that this method is reliable,efficient,and adaptable.
基金National Natural Science Foundation of China (50073002)
文摘On the basis ofa 2D 4-node Mindlin shell element method, a novel self-adapting delamination finite element method is presented, which is developed to model the delamination damage of composite laminates. In the method, the sublaminate elements are generated automatically when the delamination damage occurs or extends. Thus, the complex process and state of delamination damage can be simulated practically with high efficiency for both analysis and modeling. Based on the self-adapting delamination method, linear dynamic finite element damage analysis is performed to simulate the low-velocity impact damage process of three types of mixed woven composite laminates. Taking the frictional force among sublaminations during delaminating and the transverse normal stress into account, the analytical results are consistent with those of the experimental data.
基金This work was supported by the National Natural Science Foundation of China(No.60375001)the High School Doctoral Foundation of China(NO.20030532004).
文摘Control parameters of original differential evolution （DE） are kept fixed throughout the entire evolutionary process. However, it is not an easy task to properly set control parameters in DE for different optiinization problems. According to the relative position of two different individual vectors selected to generate a difference vector in the searching place, a self-adapting strategy for the scale factor F of the difference vector is proposed. In terms of the convergence status of the target vector in the current population, a self-adapting crossover probability constant CR strategy is proposed. Therefore, good target vectors have a lower CFI while worse target vectors have a large CFI. At the same time, the mutation operator is modified to improve the convergence speed. The performance of these proposed approaches are studied with the use of some benchmark problems and applied to the trajectory planning of a three-joint redundant manipulator. Finally, the experiment results show that the proposed approaches can greatly improve robustness and convergence speed.
文摘The basie idea and method about determination of the feature line equations and how to apply them to the numerical control of the press bending of panei skins were introduced. Research indicates that it is feasible to realize the self adapting incremental press bending by adopting the feature line equation. The feature line equation, which is based on the database of the status of practical processes, can be adjusted in time, and the forming precision can be improved. It is important to correctly select and reasonably predict the feature line equations to enhance the accuracy of the incremental press bending based on the feature line database and algorithm. The determination of the feature line equation settles necessary data foundation for further research on the database of self-adapting incremental press bending, and it supplies a new clue for the development of self-adapting incremental press bending.
基金Project(61573381)supported by the National Natural Science Foundation of ChinaProject(2012AA051601)supported by the National High-tech Research and Development Program of China
文摘An improved ensemble empirical mode decomposition(EEMD) algorithm is described in this work, in which the sifting and ensemble number are self-adaptive. In particular, the new algorithm can effectively avoid the mode mixing problem. The algorithm has been validated with a simulation signal and locomotive bearing vibration signal. The results show that the proposed self-adaptive EEMD algorithm has a better filtering performance compared with the conventional EEMD. The filter results further show that the feature of the signal can be distinguished clearly with the proposed algorithm, which implies that the fault characteristics of the locomotive bearing can be detected successfully.
基金supported by NSF CBET 1929236the support on microscopy characterizations from the Franceschi Microscopy & Imaging Center at Washington State University.
文摘Practical implementations of rechargeable lithium(Li)metal batteries have long been plagued by multiple problems of Li anode,such as Li dendrite growth,large volume change,low Coulombic efficiency.Here,we report a protein-enabled film that can provide effective protection for Li metal.The protective film with an integrated design of high flexibility,strong adhesion and high Li-ion transference number(0.80)is fabricated by incorporating denatured zein(corn protein)with polyethylene oxide(PEO)acting as an age nt for sustaining the denatured protein chains against refolding via the intermolecular interactions between them.Thus,a conformable zein-enabled protective film(zein@PEO)with simultaneous en hancement in flexibility,modulus and adhesion strength is gen erated to offer both functi ons of self-adapting and anion-anchoring abilities.The results show that the zein@PEO film is able to accommodate the volume change,reduce the side reactions,and homogenize the ion deposition.Benefiting from these significant properties/fu nctions,the Li/Cu cell with the zein@PEO film delivers prolonged cycle life for over 500 hours with stable performance.Paired with LiMn_(2)O_(4) cathode,the capacity,cycle stability and rate performance of the cell are remarkably improved as well,demonstrati ng the effectiveness in stabilizing Li metal batteries.
