Metaheuristics are commonly used in various fields,including real-life problem-solving and engineering applications.The present work introduces a novel metaheuristic algorithm named the Artificial Circulatory System A...Metaheuristics are commonly used in various fields,including real-life problem-solving and engineering applications.The present work introduces a novel metaheuristic algorithm named the Artificial Circulatory System Algorithm(ACSA).The control of the circulatory system inspires it and mimics the behavior of hormonal and neural regulators involved in this process.The work initially evaluates the effectiveness of the suggested approach on 16 two-dimensional test functions,identified as classical benchmark functions.The method was subsequently examined by application to 12 CEC 2022 benchmark problems of different complexities.Furthermore,the paper evaluates ACSA in comparison to 64 metaheuristic methods that are derived from different approaches,including evolutionary,human,physics,and swarm-based.Subsequently,a sequence of statistical tests was undertaken to examine the superiority of the suggested algorithm in comparison to the 7 most widely used algorithms in the existing literature.The results show that the ACSA strategy can quickly reach the global optimum,avoid getting trapped in local optima,and effectively maintain a balance between exploration and exploitation.ACSA outperformed 42 algorithms statistically,according to post-hoc tests.It also outperformed 9 algorithms quantitatively.The study concludes that ACSA offers competitive solutions in comparison to popüler methods.展开更多
There is an urgent need for the application of broadband Microwave Absorption(MA)structures on the leading edges of aircraft wings,which requires the MA structures to possess both the broadband MA performance and grea...There is an urgent need for the application of broadband Microwave Absorption(MA)structures on the leading edges of aircraft wings,which requires the MA structures to possess both the broadband MA performance and great surface conformability.To meet these requirements,we designed and fabricated a flexible bioinspired meta-structure with ultra-broadband MA,thin thickness and excellent surface conformality.The carbonyl iron powder-carbon nanotubes-polydimethylsiloxane composite was synthesized by physical blending method for fabricating the MA meta-structure.Through geometry-electromagnetic optimal design by heuristic optimization algorithm,the meta-structure mimicking to the nipple photonic nanostructures on the eyes of moth can achieve ultra-broadband MA performance of 35.14 GHz MA bandwidth(reflection loss≤–10 dB),covering 4.86–40.00 GHz,with thickness of only 4.3 mm.Through simple fabrication processes,the meta-structure has been successfully fabricated and bonded on wings’leading edges,exhibiting excellent surface conformability.Furthermore,the designed flexible MA meta-structure possesses significant Radar Cross-Section(RCS)reduction capability,as demonstrated by the RCS analysis of an unmanned aerial vehicle.This flexible ultra-broadband MA meta-structure provides an outstanding candidate to meet the radar stealth requirement of variable curvature structures on aircraft.展开更多
To further understand the performance of the energy harvesters under the influence of the wind force and the random excitation,this paper investigates the stochastic response of the bio-inspired energy harvesters subj...To further understand the performance of the energy harvesters under the influence of the wind force and the random excitation,this paper investigates the stochastic response of the bio-inspired energy harvesters subjected to Gaussian white noise and galloping excitation,simulating the flapping pattern of a seagull and its interaction with wind force.The equivalent linearization method is utilized to convert the original nonlinear model into the Itôstochastic differential equation by minimizing the mean squared error.Then,the second-order steady-state moments about the displacement,velocity,and voltage are derived by combining the moment analysis theory.The theoretical results are simulated numerically to analyze the stochastic response performance under different noise intensities,wind speeds,stiffness coefficients,and electromechanical coupling coefficients,time domain analysis is also conducted to study the performance of the harvester with different parameters.The results reveal that the mean square displacement and voltage increase with increasing the noise intensity and wind speed,larger absolute values of stiffness coefficient correspond to smaller mean square displacement and voltage,and larger electromechanical coupling coefficients can enhance the mean square voltage.Finally,the influence of wind speed and electromechanical coupling coefficient on the stationary probability density function(SPDF)is investigated,revealing the existence of a bimodal distribution under varying environmental conditions.展开更多
Oxygen reduction reaction(ORR)catalysts play a critical role in energy storage and conversion devices and have been attracted enormous interests,and however,it remains challenging to develop highly active cheap cataly...Oxygen reduction reaction(ORR)catalysts play a critical role in energy storage and conversion devices and have been attracted enormous interests,and however,it remains challenging to develop highly active cheap catalysts in a simple and green route.Inspired by the heme-copper oxidases(HOCs),in which the ORR active center is originated from the incorporation of Fe-N_(4)with copper atom,we here developed a fine manganese oxide nanosheets(MnO_(x)NSs)integrated with iron phthalocyanine(FePc)anchored on highly conductive graphene(MnO_(x)/FePc-G)through a green route only involve ethanol as the reagent.The bio-inspired catalyst MnO_(x)/Fe Pc-G demonstrated high ORR activity with a half-wave potential(E_(1/2))of 0.887 V,about 57 mV more positive than that of Pt/C.And the current density(j)at 0.9 V is about 1.9 m A cm^(-2),which is three times of Pt/C and FePc-G.More importantly,the bio-inspired systems show superior stability in comparison to commercial Pt/C,showing a potential of 0.863 V to deliver a j of 3 mA cm^(-2)after 18000 s polarization,about 80 mV higher than that of 0.783 V for Pt/C.The high activity is contributed by the integration of the Fe Pc and MnO_(x)NSs that plays the role to assist the cleavage of the O_(2)bond.Our approach provides a new evidence to develop highly efficient ORR catalysts through imitate the naturally involved systems through a simple route.展开更多
Bio-inspired visual systems have garnered significant attention in robotics owing to their energy efficiency,rapid dynamic response,and environmental adaptability.Among these,event cameras-bio-inspired sensors that as...Bio-inspired visual systems have garnered significant attention in robotics owing to their energy efficiency,rapid dynamic response,and environmental adaptability.Among these,event cameras-bio-inspired sensors that asynchronously report pixel-level brightness changes called’events’,stand out because of their ability to capture dynamic changes with minimal energy consumption,making them suitable for challenging conditions,such as low light or high-speed motion.However,current mapping and localization methods for event cameras depend primarily on point and line features,which struggle in sparse or low-feature environments and are unsuitable for static or slow-motion scenarios.We addressed these challenges by proposing a bio-inspired vision mapping and localization method using active LED markers(ALMs)combined with reprojection error optimization and asynchronous Kalman fusion.Our approach replaces traditional features with ALMs,thereby enabling accurate tracking under dynamic and low-feature conditions.The global mapping accuracy significantly improved by minimizing the reprojection error,with corner errors reduced from 16.8 cm to 3.1 cm after 400 iterations.The asynchronous Kalman fusion of multiple camera pose estimations from ALMs ensures precise localization with a high temporal efficiency.This method achieved a mean translation error of 0.078 m and a rotational error of 5.411°while evaluating dynamic motion.In addition,the method supported an output rate of 4.5 kHz while maintaining high localization accuracy in UAV spiral flight experiments.These results demonstrate the potential of the proposed approach for real-time robot localization in challenging environments.展开更多
Biological load-bearing materials,like the nacre in shells,have a unique staggered structure that supports their superior mechanical properties.Engineers have been encouraged to imitate it to create load-bearing bio-i...Biological load-bearing materials,like the nacre in shells,have a unique staggered structure that supports their superior mechanical properties.Engineers have been encouraged to imitate it to create load-bearing bio-inspired materials which have excellent properties not present in conventional composites.To create such materials with desirable mechanical properties,the optimum structural parameters combination must be selected.Moreover,the optimal design of bio-inspired composites needs to take into account the trade-offs between various mechanical properties.In this paper,multi-objective optimization models were developed using structural parameters as design variables and mechanical properties as optimization objectives,including stiffness,strength,toughness,and dynamic damping.Using the NSGA-II optimization algorithm,a set of optimal solutions were solved.Additionally,three different structures in natural nacre were introduced in order to utilize the better structure when design bio-inspired materials.The range of optimal solutions that obtained using results from previous research were examined and explained why this collection of optimal solution ranges is better.Also,optimal solutions were compared with the structural features and mechanical properties of real nacre and artificial biomimetic composites to validate our models.Finally,the optimum design strategies can be obtained for nacre-like composites.Our research methodically proposes an optimization method for achieving load-bearing bio-inspired materials with excellent properties and creates a set of optimal solutions from which designers can select the one that best suits their preferences,allowing the fabricated materials to demonstrate preferred performance.展开更多
Inspired by the collective behaviors observed in bird flocks and fish schools,this paper proposes a novel Decentralized Model Predictive Flocking Control(DMPFC)framework to enable UAV swarms to autonomously track pred...Inspired by the collective behaviors observed in bird flocks and fish schools,this paper proposes a novel Decentralized Model Predictive Flocking Control(DMPFC)framework to enable UAV swarms to autonomously track predefined reference trajectories while avoiding collisions and maintaining a stable quasi[Math Processing Error]-lattice formation.Unlike traditional approaches that rely on switching between predefined swarm formations,this framework utilizes identical local interaction rules for each UAV,allowing them to dynamically adjust their control inputs based on the motion states of neighboring UAVs,external environmental factors,and the desired reference trajectory,thereby enabling the swarm to adapt its formation dynamically.Through iterative state updates,the UAVs achieve consensus,allowing the swarm to follow the reference trajectory while self-organizing into a cohesive and stable group structure.To enhance computational efficiency,the framework integrates a closed-form solution for the optimization process,enabling real-time implementation even on computationally constrained micro-quadrotors.Theoretical analysis demonstrates that the proposed method ensures swarm consensus,maintains desired inter-agent distances,and stabilizes the swarm formation.Extensive simulations and real-world experiments validate the approach’s effectiveness and practicality,demonstrating that the proposed method achieves velocity consensus within approximately 200 ms and forms a stable quasi[Math Processing Error]-lattice structure nearly ten times faster than traditional models,with trajectory tracking errors on the order of millimeters.This underscores its potential for robust and efficient UAV swarm coordination in complex scenarios.展开更多
This paper considers the swarm vigilance problem for multi-agent systems(MAS),where multiple agents are deployed within a rectangular region for perception-based vigilance.There are two main challenges,namely the task...This paper considers the swarm vigilance problem for multi-agent systems(MAS),where multiple agents are deployed within a rectangular region for perception-based vigilance.There are two main challenges,namely the task allocation for vigilance roles and the coverage planning of the perception ranges.Firstly,vigilance behavioral patterns and processes in animal populations within natural habitats are investigated.Inspired by these biological vigilance behaviors,an efficient vigilance task allocation model for MAS is proposed.Secondly,the subsequent optimization of task layouts can achieve efficient surveillance coverage with fewer agents,minimizing resource consumption.Thirdly,an improved particle swarm optimization(IPSO)algorithm is proposed,which incorporates fitness-driven adaptive inertia weight dynamics.According to simulation analysis and comparative studies,optimal parameter configurations for genetic algorithm(GA)and IPSO are determined.Finally,the results indicate the proposed IPSO's superior performance to both GA and standard particle swarm optimization(PSO)in vigilance task allocation optimization,with satisfying advantages in computational efficiency and solution quality.展开更多
IntuiGrasp is a novel three-fingered dexterous hand that pioneers bio-inspired demonstrations with intuitive priors(BDIP)to bridge the gap between human tactile intuition and robotic execution.Unlike conven-tional pro...IntuiGrasp is a novel three-fingered dexterous hand that pioneers bio-inspired demonstrations with intuitive priors(BDIP)to bridge the gap between human tactile intuition and robotic execution.Unlike conven-tional programming,BDIP leverages human's innate priors(e.g.,“A pack of tissues requires gentle grasps,cups demand firm contact”)by enabling real-time transfer of gesture and force policies during physical demon-stration.When a human demonstrator wears IntuiGrasp,driven rings provide real-time haptic feedback on contact stress and slip,while inte-grated tactile sensors translate these human policies into image data,offering valuable data for imitation learning.In this study,human teachers use IntuiGrasp to demonstrate how to grasp three types of objects:a cup,a crumpled tissue pack,and a thin playing card.IntuiGrasp translates the policies for grasping these objects into image information that describes tactile sensations in real time.展开更多
Natural Language Processing(NLP)has become essential in text classification,sentiment analysis,machine translation,and speech recognition applications.As these tasks become complex,traditionalmachine learning and deep...Natural Language Processing(NLP)has become essential in text classification,sentiment analysis,machine translation,and speech recognition applications.As these tasks become complex,traditionalmachine learning and deep learning models encounter challenges with optimization,parameter tuning,and handling large-scale,highdimensional data.Bio-inspired algorithms,which mimic natural processes,offer robust optimization capabilities that can enhance NLP performance by improving feature selection,optimizing model parameters,and integrating adaptive learning mechanisms.This review explores the state-of-the-art applications of bio-inspired algorithms—such as Genetic Algorithms(GA),Particle Swarm Optimization(PSO),and Ant Colony Optimization(ACO)—across core NLP tasks.We analyze their comparative advantages,discuss their integration with neural network models,and address computational and scalability limitations.Through a synthesis of existing research,this paper highlights the unique strengths and current challenges of bio-inspired approaches in NLP,offering insights into hybrid models and lightweight,resource-efficient adaptations for real-time processing.Finally,we outline future research directions that emphasize the development of scalable,effective bio-inspired methods adaptable to evolving data environments.展开更多
The scaled suction caisson repre sents an innovative design featuring a bio-inspired sidewall modeled after snake skin,commonly utilized in offshore mooring platforms.In comparison with traditional suction caissons,th...The scaled suction caisson repre sents an innovative design featuring a bio-inspired sidewall modeled after snake skin,commonly utilized in offshore mooring platforms.In comparison with traditional suction caissons,this bio-inspired design demonstrates reduced penetration resistance and enhanced pull-out capacity due to the anisotropic shear behaviors of its sidewall.To investigate the shear behavior of the bio-inspired sidewall under pull-out load,direct shear tests were conducted between the bio-inspired surface and sand.The research demonstrates that the interface shear strength of the bio-inspired surface significantly surpasses that of the smooth surface due to interlocking effects.Additionally,the interface shear strength correlates with the aspect ratio of the bio-inspired surface,shear angle,and particle diameter distribution,with values increasing as the uniformity coefficient Cudecreases,while initially increasing and subsequently decreasing with increases in both aspect ratio and shear angle.The ratio between the interface friction angleδand internal friction angle δ_(s) defines the interface effect factor k.For the bio-inspired surface,the interface effect factor k varies with shear angleβ,ranging from 0.9 to 1.12.The peak value occurs at a shear angleβof 60°,substantially exceeding that of the smooth surface.A method for calculating the relative roughness R_(N) is employed to evaluate the interface roughness of the bio-inspired surface,taking into account scale dimension and particle diameter distribution effects.展开更多
Small-scale magnetic soft robots are promising candidates for minimally invasive medical applications;however,they struggle to achieve efficient locomotion across various interfaces.In this study,we propose a magnetic...Small-scale magnetic soft robots are promising candidates for minimally invasive medical applications;however,they struggle to achieve efficient locomotion across various interfaces.In this study,we propose a magnetic soft robot that integrates two distinct bio-inspired locomotion modes for enhanced interface navigation.Inspired by water striders’superhydrophobic legs and the meniscus climbing behavior of Pyrrhalta nymphaeae larvae,we developed a rectangular sheet-based robot with hydrophobic surface treatment and novel control strategies.The proposed robot implements two locomotion modes:a bipedal peristaltic locomotion mode(BPLM)and a single-region contact-vibration locomotion mode(SCLM).The BPLM achieves stable movement at 20 mm/s through coordinated front-rear contact points,whereas the SCLM reaches an ultrafast speed of 52 mm/s by optimizing surface tension interactions.The proposed robot demonstrates precise trajectory control with minimal deviations and successfully navigates confined spaces while manipulating objects.Theoretical analysis and experimental validation demonstrate that the integration of triangular wave control signals and steady-state components enables smooth transitions between locomotion modes.This study presents a new paradigm for bio-inspired design of small-scale robots and demonstrates the potential for medical applications requiring precise navigation across multiple terrains.展开更多
Melanoma is the deadliest form of skin cancer,with an increasing incidence over recent years.Over the past decade,researchers have recognized the potential of computer vision algorithms to aid in the early diagnosis o...Melanoma is the deadliest form of skin cancer,with an increasing incidence over recent years.Over the past decade,researchers have recognized the potential of computer vision algorithms to aid in the early diagnosis of melanoma.As a result,a number of works have been dedicated to developing efficient machine learning models for its accurate classification;still,there remains a large window for improvement necessitating further research efforts.Limitations of the existing methods include lower accuracy and high computational complexity,which may be addressed by identifying and selecting the most discriminative features to improve classification accuracy.In this work,we apply transfer learning to a Nasnet-Mobile CNN model to extract deep features and augment it with a novel nature-inspired feature selection algorithm called Mutated Binary Artificial Bee Colony.The selected features are fed to multiple classifiers for final classification.We use PH2,ISIC-2016,and HAM10000 datasets for experimentation,supported by Monte Carlo simulations for thoroughly evaluating the proposed feature selection mechanism.We carry out a detailed comparison with various benchmark works in terms of convergence rate,accuracy histogram,and reduction percentage histogram,where our method reports 99.15%(2-class)and 97.5%(3-class)accuracy on the PH^(2) dataset,while 96.12%and 94.1%accuracy for the other two datasets,respectively,against minimal features.展开更多
Bio-inspired helicoidal composite laminates,inspired by the intricate helical structures found in nature,present a promising frontier for enhancing the mechanical properties of structural designs.Hence,this study prov...Bio-inspired helicoidal composite laminates,inspired by the intricate helical structures found in nature,present a promising frontier for enhancing the mechanical properties of structural designs.Hence,this study provides a comprehensive investigation into the nonlinear free vibration and nonlinear bending behavior of bio-inspired composite plates.The inverse hyperbolic shear deformation theory(IHSDT)of plates is employed to characterize the displacement field,with the incorporation of Green-Lagrange nonlinearity.The problem is modeled using the C0finite element method(FEM),and an in-house code is developed in the MATLAB environment to solve it numerically.Various helicoidal layup configurations including helicoidal recursive(HR),helicoidal exponential(HE),helicoidal semi-circular(HS),linear helicoidal(LH),and Fibonacci helicoidal(FH)with different layup sequences and quasi-isotropic configurations are studied.The model is validated,and parametric studies are conducted.These studies investigate the effects of layup configurations,side-to-thickness ratio,modulus ratios,boundary conditions,and loading conditions at different load amplitudes on the nonlinear vibration and nonlinear bending behaviors of bio-inspired composite plates.The results show that the laminate sequence exerts a substantial impact on both nonlinear natural frequencies and nonlinear bending behaviors.Moreover,this influence varies across different side-to-thickness ratios and boundary conditions of the bio-inspired composite plate.展开更多
Electrochemical water splitting represents a sustainable technology for hydrogen(H_(2))production.However,its large-scale implementation is hindered by the high overpotentials required for both the cathodic hydrogen e...Electrochemical water splitting represents a sustainable technology for hydrogen(H_(2))production.However,its large-scale implementation is hindered by the high overpotentials required for both the cathodic hydrogen evolution reaction(HER)and the anodic oxygen evolution reaction(OER).Transition metal-based catalysts have garnered significant research interest as promising alternatives to noble-metal catalysts,owing to their low cost,tunable composition,and noble-metal-like catalytic activity.Nevertheless,systematic reviews on their application as bifunctional catalysts for overall water splitting(OWS)are still limited.This review comprehensively outlines the principal categories of bifunctional transition metal electrocatalysts derived from electrospun nanofibers(NFs),including metals,oxides,phosphides,sulfides,and carbides.Key strategies for enhancing their catalytic performance are systematically summarized,such as heterointerface engineering,heteroatom doping,metal-nonmetal-metal bridging architectures,and single-atom site design.Finally,current challenges and future research directions are discussed,aiming to provide insightful perspectives for the rational design of high-performance electrocatalysts for OWS.展开更多
Against the backdrop of escalating global climate change and energy crises,the resource utilization of carbon dioxide(CO_(2)),a major greenhouse gas,has become a crucial pathway for achieving carbon peaking and carbon...Against the backdrop of escalating global climate change and energy crises,the resource utilization of carbon dioxide(CO_(2)),a major greenhouse gas,has become a crucial pathway for achieving carbon peaking and carbon neutrality goals.The hydrogenation of CO_(2)to methanol not only enables carbon sequestration and recycling,but also provides a route to produce high value-added fuels and basic chemical feedstocks,holding significant environmental and economic potential.However,this conversion process is thermodynamically and kinetically limited,and traditional catalyst systems(e.g.,Cu/ZnO/Al_(2)O_(3))exhibit inadequate activity,selectivity,and stability under mild conditions.Therefore,the development of novel high-performance catalysts with precisely tunable structures and functionalities is imperative.Metal-organic frameworks(MOFs),as crystalline porous materials with high surface area,tunable pore structures,and diverse metal-ligand compositions,have the great potential in CO_(2)hydrogenation catalysis.Their structural design flexibility allows for the construction of well-dispersed active sites,tailored electronic environments,and enhanced metal-support interactions.This review systematically summarizes the recent advances in MOF-based and MOF-derived catalysts for CO_(2)hydrogenation to methanol,focusing on four design strategies:(1)spatial confinement and in situ construction,(2)defect engineering and ion-exchange,(3)bimetallic synergy and hybrid structure design,and(4)MOF-derived nanomaterial synthesis.These approaches significantly improve CO_(2)conversion and methanol selectivity by optimizing metal dispersion,interfacial structures,and reaction pathways.The reaction mechanism is further explored by focusing on the three main reaction pathways:the formate pathway(HCOO*),the RWGS(Reverse Water Gas Shift reaction)+CO*hydrogenation pathway,and the trans-COOH pathway.In situ spectroscopic studies and density functional theory(DFT)calculations elucidate the formation and transformation of key intermediates,as well as the roles of active sites,metal-support interfaces,oxygen vacancies,and promoters.Additionally,representative catalytic performance data for MOFbased systems are compiled and compared,demonstrating their advantages over traditional catalysts in terms of CO_(2)conversion,methanol selectivity,and space-time yield.Future perspectives for MOF-based CO_(2)hydrogenation catalysts will prioritize two main directions:structural design and mechanistic understanding.The precise construction of active sites through multi-metallic synergy,defect engineering,and interfacial electronic modulation should be made to enhance catalyst selectivity and stability.In addition,advanced in situ characterization techniques combined with theoretical modeling are essential to unravel the detailed reaction mechanisms and intermediate behaviors,thereby guiding rational catalyst design.Moreover,to enable industrial application,challenges related to thermal/hydrothermal stability,catalyst recyclability,and cost-effective large-scale synthesis must be addressed.The development of green,scalable preparation methods and the integration of MOF catalysts into practical reaction systems(e.g.,flow reactors)will be crucial for bridging the gap between laboratory research and commercial deployment.Ultimately,multi-scale structure-performance optimization and catalytic system integration will be vital for accelerating the industrialization of MOF-based CO_(2)-to-methanol technologies.展开更多
To elucidate the effect of calcite-regulated activated carbon(AC)structure on low-temperature denitrification performance of SCR catalysts,this work prepared a series of Mn-Ce/De-AC-xCaCO_(3)(x is the calcite content ...To elucidate the effect of calcite-regulated activated carbon(AC)structure on low-temperature denitrification performance of SCR catalysts,this work prepared a series of Mn-Ce/De-AC-xCaCO_(3)(x is the calcite content in coal)catalysts were prepared by the incipient wetness impregnation method,followed by acid washing to remove calcium-containing minerals.Comprehensive characterization and low-temperature denitrification tests revealed that calcite-induced structural modulation of coal-derived AC significantly enhances catalytic activity.Specifically,NO conversion increased from 88.3%of Mn-Ce/De-AC to 91.7%of Mn-Ce/De-AC-1CaCO_(3)(210℃).The improved SCR denitrification activity results from the enhancement of physicochemical properties including higher Mn^(4+)content and Ce^(4+)/Ce^(3+)ratio,an abundance of chemisorbed oxygen and acidic sites,which could strengthen the SCR reaction pathways(richer NH_(3)activated species and bidentate nitrate active species).Therefore,NO removal is enhanced.展开更多
Seawater zinc-air batteries are promising energy storage devices due to their high energy density and utilization of seawater electrolytes.However,their efficiency is hindered by the sluggish oxygen reduction reaction...Seawater zinc-air batteries are promising energy storage devices due to their high energy density and utilization of seawater electrolytes.However,their efficiency is hindered by the sluggish oxygen reduction reaction(ORR)and chlorideinduced degradation over conventional catalysts.In this study,we proposed a universal synthetic strategy to construct heteroatom axially coordinated Fe–N_(4) single-atom seawater catalyst materials(Cl–Fe–N_(4) and S–Fe–N_(4)).X-ray absorption spectroscopy confirmed their five-coordinated square pyramidal structure.Systematic evaluation of catalytic activities revealed that compared with S–Fe–N_(4),Cl–Fe–N_(4) exhibits smaller electrochemical active surface area and specific surface area,yet demonstrates higher limiting current density(5.8 mA cm^(−2)).The assembled zinc-air batteries using Cl–Fe–N_(4) showed superior power density(187.7 mW cm^(−2) at 245.1 mA cm^(−2)),indicating that Cl axial coordination more effectively enhances the intrinsic ORR activity.Moreover,Cl–Fe–N_(4) demonstrates stronger Cl−poisoning resistance in seawater environments.Chronoamperometry tests and zinc-air battery cycling performance evaluations confirmed its enhanced stability.Density functional theory calculations revealed that the introduction of heteroatoms in the axial direction regulates the electron center of Fe single atom,leading to more active reaction intermediates and increased electron density of Fe single sites,thereby enhancing the reduction in adsorbed intermediates and hence the overall ORR catalytic activity.展开更多
High‐entropy amorphous catalysts(HEACs)integrate multielement synergy with structural disorder,making them promising candidates for water splitting.Their distinctive features—including flexible coordination environm...High‐entropy amorphous catalysts(HEACs)integrate multielement synergy with structural disorder,making them promising candidates for water splitting.Their distinctive features—including flexible coordination environments,tunable electronic structures,abundant unsaturated active sites,and dynamic structural reassembly—collectively enhance electrochemical activity and durability under operating conditions.This review summarizes recent advances in HEACs for hydrogen evolution,oxygen evolution,and overall water splitting,highlighting their disorder-driven advantages over crystalline counterparts.Catalytic performance benchmarks are presented,and mechanistic insights are discussed,focusing on how multimetallic synergy,amorphization effect,and in‐situ reconstruction cooperatively regulate reaction pathways.These insights provide guidance for the rational design of next‐generation amorphous high‐entropy electrocatalysts with improved efficiency and durability.展开更多
Using photoelectrocatalytic CO_(2) reduction reaction(CO_(2)RR)to produce valuable fuels is a fascinating way to alleviate environmental issues and energy crises.Bismuth-based(Bi-based)catalysts have attracted widespr...Using photoelectrocatalytic CO_(2) reduction reaction(CO_(2)RR)to produce valuable fuels is a fascinating way to alleviate environmental issues and energy crises.Bismuth-based(Bi-based)catalysts have attracted widespread attention for CO_(2)RR due to their high catalytic activity,selectivity,excellent stability,and low cost.However,they still need to be further improved to meet the needs of industrial applications.This review article comprehensively summarizes the recent advances in regulation strategies of Bi-based catalysts and can be divided into six categories:(1)defect engineering,(2)atomic doping engineering,(3)organic framework engineering,(4)inorganic heterojunction engineering,(5)crystal face engineering,and(6)alloying and polarization engineering.Meanwhile,the corresponding catalytic mechanisms of each regulation strategy will also be discussed in detail,aiming to enable researchers to understand the structure-property relationship of the improved Bibased catalysts fundamentally.Finally,the challenges and future opportunities of the Bi-based catalysts in the photoelectrocatalytic CO_(2)RR application field will also be featured from the perspectives of the(1)combination or synergy of multiple regulatory strategies,(2)revealing formation mechanism and realizing controllable synthesis,and(3)in situ multiscale investigation of activation pathways and uncovering the catalytic mechanisms.On the one hand,through the comparative analysis and mechanism explanation of the six major regulatory strategies,a multidimensional knowledge framework of the structure-activity relationship of Bi-based catalysts can be constructed for researchers,which not only deepens the atomic-level understanding of catalytic active sites,charge transport paths,and the adsorption behavior of intermediate products,but also provides theoretical guiding principles for the controllable design of new catalysts;on the other hand,the promising collaborative regulation strategies,controllable synthetic paths,and the in situ multiscale characterization techniques presented in this work provides a paradigm reference for shortening the research and development cycle of high-performance catalysts,conducive to facilitating the transition of photoelectrocatalytic CO_(2)RR technology from the laboratory routes to industrial application.展开更多
文摘Metaheuristics are commonly used in various fields,including real-life problem-solving and engineering applications.The present work introduces a novel metaheuristic algorithm named the Artificial Circulatory System Algorithm(ACSA).The control of the circulatory system inspires it and mimics the behavior of hormonal and neural regulators involved in this process.The work initially evaluates the effectiveness of the suggested approach on 16 two-dimensional test functions,identified as classical benchmark functions.The method was subsequently examined by application to 12 CEC 2022 benchmark problems of different complexities.Furthermore,the paper evaluates ACSA in comparison to 64 metaheuristic methods that are derived from different approaches,including evolutionary,human,physics,and swarm-based.Subsequently,a sequence of statistical tests was undertaken to examine the superiority of the suggested algorithm in comparison to the 7 most widely used algorithms in the existing literature.The results show that the ACSA strategy can quickly reach the global optimum,avoid getting trapped in local optima,and effectively maintain a balance between exploration and exploitation.ACSA outperformed 42 algorithms statistically,according to post-hoc tests.It also outperformed 9 algorithms quantitatively.The study concludes that ACSA offers competitive solutions in comparison to popüler methods.
基金supported by the Basic Research Development Program of China(No.JCKY2021607B036)the National Natural Science Foundation of China(No.52275512).
文摘There is an urgent need for the application of broadband Microwave Absorption(MA)structures on the leading edges of aircraft wings,which requires the MA structures to possess both the broadband MA performance and great surface conformability.To meet these requirements,we designed and fabricated a flexible bioinspired meta-structure with ultra-broadband MA,thin thickness and excellent surface conformality.The carbonyl iron powder-carbon nanotubes-polydimethylsiloxane composite was synthesized by physical blending method for fabricating the MA meta-structure.Through geometry-electromagnetic optimal design by heuristic optimization algorithm,the meta-structure mimicking to the nipple photonic nanostructures on the eyes of moth can achieve ultra-broadband MA performance of 35.14 GHz MA bandwidth(reflection loss≤–10 dB),covering 4.86–40.00 GHz,with thickness of only 4.3 mm.Through simple fabrication processes,the meta-structure has been successfully fabricated and bonded on wings’leading edges,exhibiting excellent surface conformability.Furthermore,the designed flexible MA meta-structure possesses significant Radar Cross-Section(RCS)reduction capability,as demonstrated by the RCS analysis of an unmanned aerial vehicle.This flexible ultra-broadband MA meta-structure provides an outstanding candidate to meet the radar stealth requirement of variable curvature structures on aircraft.
文摘To further understand the performance of the energy harvesters under the influence of the wind force and the random excitation,this paper investigates the stochastic response of the bio-inspired energy harvesters subjected to Gaussian white noise and galloping excitation,simulating the flapping pattern of a seagull and its interaction with wind force.The equivalent linearization method is utilized to convert the original nonlinear model into the Itôstochastic differential equation by minimizing the mean squared error.Then,the second-order steady-state moments about the displacement,velocity,and voltage are derived by combining the moment analysis theory.The theoretical results are simulated numerically to analyze the stochastic response performance under different noise intensities,wind speeds,stiffness coefficients,and electromechanical coupling coefficients,time domain analysis is also conducted to study the performance of the harvester with different parameters.The results reveal that the mean square displacement and voltage increase with increasing the noise intensity and wind speed,larger absolute values of stiffness coefficient correspond to smaller mean square displacement and voltage,and larger electromechanical coupling coefficients can enhance the mean square voltage.Finally,the influence of wind speed and electromechanical coupling coefficient on the stationary probability density function(SPDF)is investigated,revealing the existence of a bimodal distribution under varying environmental conditions.
基金funded by an Australian Research Council LIEF grant(LE120100026)supported by the National Natural Science Foundation of China(U19A2017)
文摘Oxygen reduction reaction(ORR)catalysts play a critical role in energy storage and conversion devices and have been attracted enormous interests,and however,it remains challenging to develop highly active cheap catalysts in a simple and green route.Inspired by the heme-copper oxidases(HOCs),in which the ORR active center is originated from the incorporation of Fe-N_(4)with copper atom,we here developed a fine manganese oxide nanosheets(MnO_(x)NSs)integrated with iron phthalocyanine(FePc)anchored on highly conductive graphene(MnO_(x)/FePc-G)through a green route only involve ethanol as the reagent.The bio-inspired catalyst MnO_(x)/Fe Pc-G demonstrated high ORR activity with a half-wave potential(E_(1/2))of 0.887 V,about 57 mV more positive than that of Pt/C.And the current density(j)at 0.9 V is about 1.9 m A cm^(-2),which is three times of Pt/C and FePc-G.More importantly,the bio-inspired systems show superior stability in comparison to commercial Pt/C,showing a potential of 0.863 V to deliver a j of 3 mA cm^(-2)after 18000 s polarization,about 80 mV higher than that of 0.783 V for Pt/C.The high activity is contributed by the integration of the Fe Pc and MnO_(x)NSs that plays the role to assist the cleavage of the O_(2)bond.Our approach provides a new evidence to develop highly efficient ORR catalysts through imitate the naturally involved systems through a simple route.
基金Supported by Beijing Natural Science Foundation(Grant No.L231004)Young Elite Scientists Sponsorship Program by CAST(Grant No.2022QNRC001)+2 种基金Fundamental Research Funds for the Central Universities(Grant No.2025JBMC039)National Key Research and Development Program(Grant No.2022YFC2805200)National Natural Science Foundation of China(Grant No.52371338).
文摘Bio-inspired visual systems have garnered significant attention in robotics owing to their energy efficiency,rapid dynamic response,and environmental adaptability.Among these,event cameras-bio-inspired sensors that asynchronously report pixel-level brightness changes called’events’,stand out because of their ability to capture dynamic changes with minimal energy consumption,making them suitable for challenging conditions,such as low light or high-speed motion.However,current mapping and localization methods for event cameras depend primarily on point and line features,which struggle in sparse or low-feature environments and are unsuitable for static or slow-motion scenarios.We addressed these challenges by proposing a bio-inspired vision mapping and localization method using active LED markers(ALMs)combined with reprojection error optimization and asynchronous Kalman fusion.Our approach replaces traditional features with ALMs,thereby enabling accurate tracking under dynamic and low-feature conditions.The global mapping accuracy significantly improved by minimizing the reprojection error,with corner errors reduced from 16.8 cm to 3.1 cm after 400 iterations.The asynchronous Kalman fusion of multiple camera pose estimations from ALMs ensures precise localization with a high temporal efficiency.This method achieved a mean translation error of 0.078 m and a rotational error of 5.411°while evaluating dynamic motion.In addition,the method supported an output rate of 4.5 kHz while maintaining high localization accuracy in UAV spiral flight experiments.These results demonstrate the potential of the proposed approach for real-time robot localization in challenging environments.
基金Supported by National Natural Science Foundation of China(Grant Nos.52222505,52321002)Shanghai Municipal Natural Science Foundation o China(Grant No.23ZR1415500)。
文摘Biological load-bearing materials,like the nacre in shells,have a unique staggered structure that supports their superior mechanical properties.Engineers have been encouraged to imitate it to create load-bearing bio-inspired materials which have excellent properties not present in conventional composites.To create such materials with desirable mechanical properties,the optimum structural parameters combination must be selected.Moreover,the optimal design of bio-inspired composites needs to take into account the trade-offs between various mechanical properties.In this paper,multi-objective optimization models were developed using structural parameters as design variables and mechanical properties as optimization objectives,including stiffness,strength,toughness,and dynamic damping.Using the NSGA-II optimization algorithm,a set of optimal solutions were solved.Additionally,three different structures in natural nacre were introduced in order to utilize the better structure when design bio-inspired materials.The range of optimal solutions that obtained using results from previous research were examined and explained why this collection of optimal solution ranges is better.Also,optimal solutions were compared with the structural features and mechanical properties of real nacre and artificial biomimetic composites to validate our models.Finally,the optimum design strategies can be obtained for nacre-like composites.Our research methodically proposes an optimization method for achieving load-bearing bio-inspired materials with excellent properties and creates a set of optimal solutions from which designers can select the one that best suits their preferences,allowing the fabricated materials to demonstrate preferred performance.
基金supported in part by the Guangdong Provincial Universities'Characteristic Innovation Project under Grant 2024KTSCX360in part by the Guangdong Educational Science Planning Project under Grant 2023GXJK837.
文摘Inspired by the collective behaviors observed in bird flocks and fish schools,this paper proposes a novel Decentralized Model Predictive Flocking Control(DMPFC)framework to enable UAV swarms to autonomously track predefined reference trajectories while avoiding collisions and maintaining a stable quasi[Math Processing Error]-lattice formation.Unlike traditional approaches that rely on switching between predefined swarm formations,this framework utilizes identical local interaction rules for each UAV,allowing them to dynamically adjust their control inputs based on the motion states of neighboring UAVs,external environmental factors,and the desired reference trajectory,thereby enabling the swarm to adapt its formation dynamically.Through iterative state updates,the UAVs achieve consensus,allowing the swarm to follow the reference trajectory while self-organizing into a cohesive and stable group structure.To enhance computational efficiency,the framework integrates a closed-form solution for the optimization process,enabling real-time implementation even on computationally constrained micro-quadrotors.Theoretical analysis demonstrates that the proposed method ensures swarm consensus,maintains desired inter-agent distances,and stabilizes the swarm formation.Extensive simulations and real-world experiments validate the approach’s effectiveness and practicality,demonstrating that the proposed method achieves velocity consensus within approximately 200 ms and forms a stable quasi[Math Processing Error]-lattice structure nearly ten times faster than traditional models,with trajectory tracking errors on the order of millimeters.This underscores its potential for robust and efficient UAV swarm coordination in complex scenarios.
基金The National Natural Science Foundation of China(62203015,62233001,62273351)The Beijing Natural Science Foundation(4242038)。
文摘This paper considers the swarm vigilance problem for multi-agent systems(MAS),where multiple agents are deployed within a rectangular region for perception-based vigilance.There are two main challenges,namely the task allocation for vigilance roles and the coverage planning of the perception ranges.Firstly,vigilance behavioral patterns and processes in animal populations within natural habitats are investigated.Inspired by these biological vigilance behaviors,an efficient vigilance task allocation model for MAS is proposed.Secondly,the subsequent optimization of task layouts can achieve efficient surveillance coverage with fewer agents,minimizing resource consumption.Thirdly,an improved particle swarm optimization(IPSO)algorithm is proposed,which incorporates fitness-driven adaptive inertia weight dynamics.According to simulation analysis and comparative studies,optimal parameter configurations for genetic algorithm(GA)and IPSO are determined.Finally,the results indicate the proposed IPSO's superior performance to both GA and standard particle swarm optimization(PSO)in vigilance task allocation optimization,with satisfying advantages in computational efficiency and solution quality.
文摘IntuiGrasp is a novel three-fingered dexterous hand that pioneers bio-inspired demonstrations with intuitive priors(BDIP)to bridge the gap between human tactile intuition and robotic execution.Unlike conven-tional programming,BDIP leverages human's innate priors(e.g.,“A pack of tissues requires gentle grasps,cups demand firm contact”)by enabling real-time transfer of gesture and force policies during physical demon-stration.When a human demonstrator wears IntuiGrasp,driven rings provide real-time haptic feedback on contact stress and slip,while inte-grated tactile sensors translate these human policies into image data,offering valuable data for imitation learning.In this study,human teachers use IntuiGrasp to demonstrate how to grasp three types of objects:a cup,a crumpled tissue pack,and a thin playing card.IntuiGrasp translates the policies for grasping these objects into image information that describes tactile sensations in real time.
基金supported by AIT Laboratory,FPT University,Danang Campus,Vietnam,2024.
文摘Natural Language Processing(NLP)has become essential in text classification,sentiment analysis,machine translation,and speech recognition applications.As these tasks become complex,traditionalmachine learning and deep learning models encounter challenges with optimization,parameter tuning,and handling large-scale,highdimensional data.Bio-inspired algorithms,which mimic natural processes,offer robust optimization capabilities that can enhance NLP performance by improving feature selection,optimizing model parameters,and integrating adaptive learning mechanisms.This review explores the state-of-the-art applications of bio-inspired algorithms—such as Genetic Algorithms(GA),Particle Swarm Optimization(PSO),and Ant Colony Optimization(ACO)—across core NLP tasks.We analyze their comparative advantages,discuss their integration with neural network models,and address computational and scalability limitations.Through a synthesis of existing research,this paper highlights the unique strengths and current challenges of bio-inspired approaches in NLP,offering insights into hybrid models and lightweight,resource-efficient adaptations for real-time processing.Finally,we outline future research directions that emphasize the development of scalable,effective bio-inspired methods adaptable to evolving data environments.
基金supported by the National Natural Science Foundation of China(Grant Nos.52371301 and 52471289)。
文摘The scaled suction caisson repre sents an innovative design featuring a bio-inspired sidewall modeled after snake skin,commonly utilized in offshore mooring platforms.In comparison with traditional suction caissons,this bio-inspired design demonstrates reduced penetration resistance and enhanced pull-out capacity due to the anisotropic shear behaviors of its sidewall.To investigate the shear behavior of the bio-inspired sidewall under pull-out load,direct shear tests were conducted between the bio-inspired surface and sand.The research demonstrates that the interface shear strength of the bio-inspired surface significantly surpasses that of the smooth surface due to interlocking effects.Additionally,the interface shear strength correlates with the aspect ratio of the bio-inspired surface,shear angle,and particle diameter distribution,with values increasing as the uniformity coefficient Cudecreases,while initially increasing and subsequently decreasing with increases in both aspect ratio and shear angle.The ratio between the interface friction angleδand internal friction angle δ_(s) defines the interface effect factor k.For the bio-inspired surface,the interface effect factor k varies with shear angleβ,ranging from 0.9 to 1.12.The peak value occurs at a shear angleβof 60°,substantially exceeding that of the smooth surface.A method for calculating the relative roughness R_(N) is employed to evaluate the interface roughness of the bio-inspired surface,taking into account scale dimension and particle diameter distribution effects.
基金supported by the Shenzhen Science and Technology Program(Nos.JCYJ20210324132810026,KQTD20210811090146075,and GXWD20220811164014001)the National Natural Science Foundation of China(Nos.52375175,52005128,62473277,and 52475075)+4 种基金the National Key Research and Development Program of China(No.2022YFC3802302)Guangdong Basic and Applied Basic Research Foundation(No.2024A1515240015)Jiangsu Provincial Outstanding Youth Program(No.BK20230072)Suzhou Industrial Foresight and Key Core Technology Project(No.SYC2022044)a grant from Open Foundation of the State Key Laboratory of Fluid Power and Mechatronic Systems,and grants from Jiangsu Qinglan Project and Jiangsu 333 High-level Talents.
文摘Small-scale magnetic soft robots are promising candidates for minimally invasive medical applications;however,they struggle to achieve efficient locomotion across various interfaces.In this study,we propose a magnetic soft robot that integrates two distinct bio-inspired locomotion modes for enhanced interface navigation.Inspired by water striders’superhydrophobic legs and the meniscus climbing behavior of Pyrrhalta nymphaeae larvae,we developed a rectangular sheet-based robot with hydrophobic surface treatment and novel control strategies.The proposed robot implements two locomotion modes:a bipedal peristaltic locomotion mode(BPLM)and a single-region contact-vibration locomotion mode(SCLM).The BPLM achieves stable movement at 20 mm/s through coordinated front-rear contact points,whereas the SCLM reaches an ultrafast speed of 52 mm/s by optimizing surface tension interactions.The proposed robot demonstrates precise trajectory control with minimal deviations and successfully navigates confined spaces while manipulating objects.Theoretical analysis and experimental validation demonstrate that the integration of triangular wave control signals and steady-state components enables smooth transitions between locomotion modes.This study presents a new paradigm for bio-inspired design of small-scale robots and demonstrates the potential for medical applications requiring precise navigation across multiple terrains.
基金Prince Sattam bin Abdulaziz University for funding this research work through the project number(PSAU/2024/03/31540).
文摘Melanoma is the deadliest form of skin cancer,with an increasing incidence over recent years.Over the past decade,researchers have recognized the potential of computer vision algorithms to aid in the early diagnosis of melanoma.As a result,a number of works have been dedicated to developing efficient machine learning models for its accurate classification;still,there remains a large window for improvement necessitating further research efforts.Limitations of the existing methods include lower accuracy and high computational complexity,which may be addressed by identifying and selecting the most discriminative features to improve classification accuracy.In this work,we apply transfer learning to a Nasnet-Mobile CNN model to extract deep features and augment it with a novel nature-inspired feature selection algorithm called Mutated Binary Artificial Bee Colony.The selected features are fed to multiple classifiers for final classification.We use PH2,ISIC-2016,and HAM10000 datasets for experimentation,supported by Monte Carlo simulations for thoroughly evaluating the proposed feature selection mechanism.We carry out a detailed comparison with various benchmark works in terms of convergence rate,accuracy histogram,and reduction percentage histogram,where our method reports 99.15%(2-class)and 97.5%(3-class)accuracy on the PH^(2) dataset,while 96.12%and 94.1%accuracy for the other two datasets,respectively,against minimal features.
文摘Bio-inspired helicoidal composite laminates,inspired by the intricate helical structures found in nature,present a promising frontier for enhancing the mechanical properties of structural designs.Hence,this study provides a comprehensive investigation into the nonlinear free vibration and nonlinear bending behavior of bio-inspired composite plates.The inverse hyperbolic shear deformation theory(IHSDT)of plates is employed to characterize the displacement field,with the incorporation of Green-Lagrange nonlinearity.The problem is modeled using the C0finite element method(FEM),and an in-house code is developed in the MATLAB environment to solve it numerically.Various helicoidal layup configurations including helicoidal recursive(HR),helicoidal exponential(HE),helicoidal semi-circular(HS),linear helicoidal(LH),and Fibonacci helicoidal(FH)with different layup sequences and quasi-isotropic configurations are studied.The model is validated,and parametric studies are conducted.These studies investigate the effects of layup configurations,side-to-thickness ratio,modulus ratios,boundary conditions,and loading conditions at different load amplitudes on the nonlinear vibration and nonlinear bending behaviors of bio-inspired composite plates.The results show that the laminate sequence exerts a substantial impact on both nonlinear natural frequencies and nonlinear bending behaviors.Moreover,this influence varies across different side-to-thickness ratios and boundary conditions of the bio-inspired composite plate.
基金Supported by the National Natural Science Foundation of China(No.52273056)the Science and Technology Development Program of Jilin Province,China(No.YDZJ202501ZYTS305)。
文摘Electrochemical water splitting represents a sustainable technology for hydrogen(H_(2))production.However,its large-scale implementation is hindered by the high overpotentials required for both the cathodic hydrogen evolution reaction(HER)and the anodic oxygen evolution reaction(OER).Transition metal-based catalysts have garnered significant research interest as promising alternatives to noble-metal catalysts,owing to their low cost,tunable composition,and noble-metal-like catalytic activity.Nevertheless,systematic reviews on their application as bifunctional catalysts for overall water splitting(OWS)are still limited.This review comprehensively outlines the principal categories of bifunctional transition metal electrocatalysts derived from electrospun nanofibers(NFs),including metals,oxides,phosphides,sulfides,and carbides.Key strategies for enhancing their catalytic performance are systematically summarized,such as heterointerface engineering,heteroatom doping,metal-nonmetal-metal bridging architectures,and single-atom site design.Finally,current challenges and future research directions are discussed,aiming to provide insightful perspectives for the rational design of high-performance electrocatalysts for OWS.
基金Supported by the National Key Research and Development Program of China(2023YFB4104500,2023YFB4104502)the National Natural Science Foundation of China(22138013)the Taishan Scholar Project(ts201712020).
文摘Against the backdrop of escalating global climate change and energy crises,the resource utilization of carbon dioxide(CO_(2)),a major greenhouse gas,has become a crucial pathway for achieving carbon peaking and carbon neutrality goals.The hydrogenation of CO_(2)to methanol not only enables carbon sequestration and recycling,but also provides a route to produce high value-added fuels and basic chemical feedstocks,holding significant environmental and economic potential.However,this conversion process is thermodynamically and kinetically limited,and traditional catalyst systems(e.g.,Cu/ZnO/Al_(2)O_(3))exhibit inadequate activity,selectivity,and stability under mild conditions.Therefore,the development of novel high-performance catalysts with precisely tunable structures and functionalities is imperative.Metal-organic frameworks(MOFs),as crystalline porous materials with high surface area,tunable pore structures,and diverse metal-ligand compositions,have the great potential in CO_(2)hydrogenation catalysis.Their structural design flexibility allows for the construction of well-dispersed active sites,tailored electronic environments,and enhanced metal-support interactions.This review systematically summarizes the recent advances in MOF-based and MOF-derived catalysts for CO_(2)hydrogenation to methanol,focusing on four design strategies:(1)spatial confinement and in situ construction,(2)defect engineering and ion-exchange,(3)bimetallic synergy and hybrid structure design,and(4)MOF-derived nanomaterial synthesis.These approaches significantly improve CO_(2)conversion and methanol selectivity by optimizing metal dispersion,interfacial structures,and reaction pathways.The reaction mechanism is further explored by focusing on the three main reaction pathways:the formate pathway(HCOO*),the RWGS(Reverse Water Gas Shift reaction)+CO*hydrogenation pathway,and the trans-COOH pathway.In situ spectroscopic studies and density functional theory(DFT)calculations elucidate the formation and transformation of key intermediates,as well as the roles of active sites,metal-support interfaces,oxygen vacancies,and promoters.Additionally,representative catalytic performance data for MOFbased systems are compiled and compared,demonstrating their advantages over traditional catalysts in terms of CO_(2)conversion,methanol selectivity,and space-time yield.Future perspectives for MOF-based CO_(2)hydrogenation catalysts will prioritize two main directions:structural design and mechanistic understanding.The precise construction of active sites through multi-metallic synergy,defect engineering,and interfacial electronic modulation should be made to enhance catalyst selectivity and stability.In addition,advanced in situ characterization techniques combined with theoretical modeling are essential to unravel the detailed reaction mechanisms and intermediate behaviors,thereby guiding rational catalyst design.Moreover,to enable industrial application,challenges related to thermal/hydrothermal stability,catalyst recyclability,and cost-effective large-scale synthesis must be addressed.The development of green,scalable preparation methods and the integration of MOF catalysts into practical reaction systems(e.g.,flow reactors)will be crucial for bridging the gap between laboratory research and commercial deployment.Ultimately,multi-scale structure-performance optimization and catalytic system integration will be vital for accelerating the industrialization of MOF-based CO_(2)-to-methanol technologies.
基金Supported by the Science and Technology Cooperation and Exchange special project of Cooperation of Shanxi Province(202404041101014)the Fundamental Research Program of Shanxi Province(202403021212333)+3 种基金the Joint Funds of the National Natural Science Foundation of China(U24A20555)the Lvliang Key R&D of University-Local Cooperation(2023XDHZ10)the Initiation Fund for Doctoral Research of Taiyuan University of Science and Technology(20242026)the Outstanding Doctor Funding Award of Shanxi Province(20242080).
文摘To elucidate the effect of calcite-regulated activated carbon(AC)structure on low-temperature denitrification performance of SCR catalysts,this work prepared a series of Mn-Ce/De-AC-xCaCO_(3)(x is the calcite content in coal)catalysts were prepared by the incipient wetness impregnation method,followed by acid washing to remove calcium-containing minerals.Comprehensive characterization and low-temperature denitrification tests revealed that calcite-induced structural modulation of coal-derived AC significantly enhances catalytic activity.Specifically,NO conversion increased from 88.3%of Mn-Ce/De-AC to 91.7%of Mn-Ce/De-AC-1CaCO_(3)(210℃).The improved SCR denitrification activity results from the enhancement of physicochemical properties including higher Mn^(4+)content and Ce^(4+)/Ce^(3+)ratio,an abundance of chemisorbed oxygen and acidic sites,which could strengthen the SCR reaction pathways(richer NH_(3)activated species and bidentate nitrate active species).Therefore,NO removal is enhanced.
基金funded by the Innovative Research Group Project of the National Natural Science Foundation of China(52121004)the Research Development Fund(No.RDF-21-02-060)by Xi’an Jiaotong-Liverpool University+1 种基金support received from the Suzhou Industrial Park High Quality Innovation Platform of Functional Molecular Materials and Devices(YZCXPT2023105)the XJTLU Advanced Materials Research Center(AMRC).
文摘Seawater zinc-air batteries are promising energy storage devices due to their high energy density and utilization of seawater electrolytes.However,their efficiency is hindered by the sluggish oxygen reduction reaction(ORR)and chlorideinduced degradation over conventional catalysts.In this study,we proposed a universal synthetic strategy to construct heteroatom axially coordinated Fe–N_(4) single-atom seawater catalyst materials(Cl–Fe–N_(4) and S–Fe–N_(4)).X-ray absorption spectroscopy confirmed their five-coordinated square pyramidal structure.Systematic evaluation of catalytic activities revealed that compared with S–Fe–N_(4),Cl–Fe–N_(4) exhibits smaller electrochemical active surface area and specific surface area,yet demonstrates higher limiting current density(5.8 mA cm^(−2)).The assembled zinc-air batteries using Cl–Fe–N_(4) showed superior power density(187.7 mW cm^(−2) at 245.1 mA cm^(−2)),indicating that Cl axial coordination more effectively enhances the intrinsic ORR activity.Moreover,Cl–Fe–N_(4) demonstrates stronger Cl−poisoning resistance in seawater environments.Chronoamperometry tests and zinc-air battery cycling performance evaluations confirmed its enhanced stability.Density functional theory calculations revealed that the introduction of heteroatoms in the axial direction regulates the electron center of Fe single atom,leading to more active reaction intermediates and increased electron density of Fe single sites,thereby enhancing the reduction in adsorbed intermediates and hence the overall ORR catalytic activity.
基金supported by the Australian Research Council(ARC)Projects(DP220101139,DP220101142,and LP240100542).
文摘High‐entropy amorphous catalysts(HEACs)integrate multielement synergy with structural disorder,making them promising candidates for water splitting.Their distinctive features—including flexible coordination environments,tunable electronic structures,abundant unsaturated active sites,and dynamic structural reassembly—collectively enhance electrochemical activity and durability under operating conditions.This review summarizes recent advances in HEACs for hydrogen evolution,oxygen evolution,and overall water splitting,highlighting their disorder-driven advantages over crystalline counterparts.Catalytic performance benchmarks are presented,and mechanistic insights are discussed,focusing on how multimetallic synergy,amorphization effect,and in‐situ reconstruction cooperatively regulate reaction pathways.These insights provide guidance for the rational design of next‐generation amorphous high‐entropy electrocatalysts with improved efficiency and durability.
基金supports from the National Natural Science Foundation of China(Grant Nos.12305372 and 22376217)the National Key Research&Development Program of China(Grant Nos.2022YFA1603802 and 2022YFB3504100)+1 种基金the projects of the key laboratory of advanced energy materials chemistry,ministry of education(Nankai University)key laboratory of Jiangxi Province for persistent pollutants prevention control and resource reuse(2023SSY02061)are gratefully acknowledged.
文摘Using photoelectrocatalytic CO_(2) reduction reaction(CO_(2)RR)to produce valuable fuels is a fascinating way to alleviate environmental issues and energy crises.Bismuth-based(Bi-based)catalysts have attracted widespread attention for CO_(2)RR due to their high catalytic activity,selectivity,excellent stability,and low cost.However,they still need to be further improved to meet the needs of industrial applications.This review article comprehensively summarizes the recent advances in regulation strategies of Bi-based catalysts and can be divided into six categories:(1)defect engineering,(2)atomic doping engineering,(3)organic framework engineering,(4)inorganic heterojunction engineering,(5)crystal face engineering,and(6)alloying and polarization engineering.Meanwhile,the corresponding catalytic mechanisms of each regulation strategy will also be discussed in detail,aiming to enable researchers to understand the structure-property relationship of the improved Bibased catalysts fundamentally.Finally,the challenges and future opportunities of the Bi-based catalysts in the photoelectrocatalytic CO_(2)RR application field will also be featured from the perspectives of the(1)combination or synergy of multiple regulatory strategies,(2)revealing formation mechanism and realizing controllable synthesis,and(3)in situ multiscale investigation of activation pathways and uncovering the catalytic mechanisms.On the one hand,through the comparative analysis and mechanism explanation of the six major regulatory strategies,a multidimensional knowledge framework of the structure-activity relationship of Bi-based catalysts can be constructed for researchers,which not only deepens the atomic-level understanding of catalytic active sites,charge transport paths,and the adsorption behavior of intermediate products,but also provides theoretical guiding principles for the controllable design of new catalysts;on the other hand,the promising collaborative regulation strategies,controllable synthetic paths,and the in situ multiscale characterization techniques presented in this work provides a paradigm reference for shortening the research and development cycle of high-performance catalysts,conducive to facilitating the transition of photoelectrocatalytic CO_(2)RR technology from the laboratory routes to industrial application.
