Ammonium dinitramide(ADN)based liquid monopropellants have been identified as environmentally benign substitutes for hydrazine monopropellant.However,new catalysts are to be developed for making ADN monopropellants co...Ammonium dinitramide(ADN)based liquid monopropellants have been identified as environmentally benign substitutes for hydrazine monopropellant.However,new catalysts are to be developed for making ADN monopropellants cold-start capable.In the present study,performance of Co and Ba doped CuCr_2O_4 nanocatalysts prepared by hydrothermal method was evaluated on the decomposition of aqueous ADN solution and ADN liquid monopropellant(LMP103X).The catalysts were characterized by PXRD(Powder X-ray Diffraction),FTIR(Fourier Transform Infrared spectroscopy),SEM(Scanning Electron Microscopy),TEM(Transmission Electron Microscopy),EDS(Energy Dispersive X-ray Spectroscopy),and XPS(X-ray Photoelectron Spectroscopy).The nanosize was confirmed by SEM and TEM,while the nanoflake morphology was confirmed by the SEM analysis.Further,we obtained the elemental composition from the EDS analysis.We investigated the catalytic activity of the catalysts by thermogravimetric(TG)analysis and the developed catalysts lowered the decomposition temperature of ADN monopropellant by about 55℃.The XPS analysis confirmed the presence of metal ions with different chemical states.Apparently,increase in the surface area of the catalysts and the mixed active sites as well as the development of oxygen vacancy on the catalyst surface introduced by metal doping are influencing the decomposition temperature of ADN samples.展开更多
Catalytic decomposition of methane,which produces high-purity hydrogen and high-value-added carbon nanomaterials,has shown considerable potential for development and is expected to yield significant economic benefits ...Catalytic decomposition of methane,which produces high-purity hydrogen and high-value-added carbon nanomaterials,has shown considerable potential for development and is expected to yield significant economic benefits in the future.However,designing catalysts that simultaneously exhibit high activity and long-term stability remains a significant challenge.Tuning the catalyst’s structure and electronic properties is an effective strategy for enhancing the reaction performance.In this work,a series of NixZr/ZSM-5 catalysts were prepared using the incipient wetness impregnation method,and the effect of Zr loadings on catalyst properties and performance was systematically investigated.The calcined and reduced catalysts were characterized by low-temperature N_(2)adsorption-desorption,XRD,SEM,H_(2)-TPR and XPS.The results showed that the addition of Zr significantly increased the specific surface area of the catalyst and reduced the metal particle size.Smaller NiO particles were found to enter the pores of the HZSM-5 support,and electronic interactions between NiO and ZrO_(2)markedly enhanced the metal-support interaction.The catalyst exhibited optimal catalytic performance at a Zr loading of 5%,achieving a maximum methane conversion of 68%at 625℃,maintaining activity for 900 min,and delivering a carbon yield of 1927%.Further increasing the Zr loading yielded only limited improvements in catalytic performance.Characterization of the spent catalysts and carbon products via TEM,Raman spectroscopy,and TGA revealed that the introduction of ZrO_(2)reduced metal sintering and promoted a shift in carbon nanofibers growth mode from tip-growth to base-growth.The mechanism of base-growth enabled the catalyst to maintain reaction activity for an extended period.展开更多
Chemical warfare agents(CWAs)remain a persistent hazard in many parts of the world,necessitating a deeper exploration of their chemical and physical characteristics and reactions under diverse conditions.Diisopropyl m...Chemical warfare agents(CWAs)remain a persistent hazard in many parts of the world,necessitating a deeper exploration of their chemical and physical characteristics and reactions under diverse conditions.Diisopropyl methylphosphonate(DIMP),a commonly used CWA surrogate,is widely studied to enhance our understanding of CWA behavior.The prevailing thermal decomposition model for DIMP,developed approximately 25 years ago,is based on data collected in nitrogen atmospheres at temperatures ranging from 700 K to 800 K.Despite its limitations,this model continues to serve as a foundation for research across various thermal and reactive environments,including combustion studies.Our recent experiments have extended the scope of decomposition analysis by examining DIMP in both nitrogen and zero air across a lower temperature range of 175℃ to 250℃.Infrared spectroscopy results under nitrogen align well with the established model;however,we observed that catalytic effects,stemming from decomposition byproducts and interactions with stainless steel surfaces,alter the reaction kinetics.In zero air environments,we observed a novel infrared absorption band.Spectral fitting suggests this band may represent a combination of propanal and acetone,while GCMS analysis points to vinyl formate and acetone as possible constituents.Although the precise identity of these new products remains unresolved,our findings clearly indicate that the existing decomposition model cannot be reliably extended to lower temperatures or non-nitrogen environments without further revisions.展开更多
Current improved Empirical Mode Decomposition(EMD)methods enhance the accurate identification of peak and valley points in mechanical signals through noise-assisted filtering techniques,thereby improving the mode deco...Current improved Empirical Mode Decomposition(EMD)methods enhance the accurate identification of peak and valley points in mechanical signals through noise-assisted filtering techniques,thereby improving the mode decomposition performance,which is of great significance in extracting fault features from mechanical signals.However,noise-assisted filtering leads to the loss of critical features in mechanical signals and introduces a large amount of residual noise into Intrinsic Mode Functions(IMFs)that obscure signal features.To address these issues,a Precise Identification-based Mode Decomposition(PIMD)method is proposed.This method directly enhances the ability of EMD to precisely identify peak and valley points by using a proposed precise identifi-cation approach,which improves mode decomposition performance and avoids the negative impacts of noise-assisted filtering,thus benefiting the extraction of more mechanical fault features.Simulation results show that the proposed PIMD method can precisely identify peak and valley points of signals with noise of different signal-tonoise ratios and perform a highly rigorous high-low frequency decomposition,significantly outperforming EMD.Finally,mechanical fault diagnostic experiments on four bearing cases and two gear cases demonstrate that,compared to four mainstream methods,the PIMD method exhibits the best mode decomposition perfor-mance and can extract more and clearer mechanical fault features.展开更多
In order to explore the effects of CaO,lignite dust and sawdust on the drying characteristics ofmunicipal sludge at different concentrations,a three-factor three-level regression experiment was carried out based on th...In order to explore the effects of CaO,lignite dust and sawdust on the drying characteristics ofmunicipal sludge at different concentrations,a three-factor three-level regression experiment was carried out based on the results of thermogravimetric experiment and single factor experiment.By fitting three common mathematical models,the Page model with the highest fitting degree was selected to determine the most suitable mathematical model to describe the municipal sludge drying process.In addition,the Box-Behnken design principle in the response surface method was used to analyze the interaction of three factors on the drying characteristics of municipal sludge.The results of the study show that below 100℃is the optimal drying temperature range for municipal sludge.The results of single factor experiments showed that the order of influence of the three factors on sludge drying time was CaO concentration>sawdust concentration>lignite dust concentration.In the single factor experiment,the optimal process parameterswere CaOconcentration 3%,lignite powder concentration 7%,and sawdust concentration 7%.In themulti-factor interaction analysis,the interaction between CaO and sawdust had the most significant effect on the reduction of drying time,and the order of influence was as follows:CaO interaction with sawdust>lignite dust interaction with sawdust>CaO interaction with lignite powder.Further analysis showed that the optimal process ratio was 3%CaO concentration and 3%sawdust concentration.展开更多
The sulfation and decomposition process has proven effective in selectively extracting lithium from lepidolite.It is essential to clarify the thermochemical behavior and kinetic parameters of decomposition reactions.A...The sulfation and decomposition process has proven effective in selectively extracting lithium from lepidolite.It is essential to clarify the thermochemical behavior and kinetic parameters of decomposition reactions.Accordingly,comprehensive kinetic study by employing thermalgravimetric analysis at various heating rates was presented in this paper.Two main weight loss regions were observed during heating.The initial region corresponded to the dehydration of crystal water,whereas the subsequent region with overlapping peaks involved complex decomposition reactions.The overlapping peaks were separated into two individual reaction peaks and the activation energy of each peak was calculated using isoconversional kinetics methods.The activation energy of peak 1 exhibited a continual increase as the reaction conversion progressed,while that of peak 2 steadily decreased.The optimal kinetic models,identified as belonging to the random nucleation and subsequent growth category,provided valuable insights into the mechanism of the decomposition reactions.Furthermore,the adjustment factor was introduced to reconstruct the kinetic mechanism models,and the reconstructed models described the kinetic mechanism model more accurately for the decomposition reactions.This study enhanced the understanding of the thermochemical behavior and kinetic parameters of the lepidolite sulfation product decomposition reactions,further providing theoretical basis for promoting the selective extraction of lithium.展开更多
Lithium-ion batteries(LIBs),while dominant in energy storage due to high energy density and cycling stability,suffer from severe capacity decay,rate capability degradation,and lithium dendrite formation under low-temp...Lithium-ion batteries(LIBs),while dominant in energy storage due to high energy density and cycling stability,suffer from severe capacity decay,rate capability degradation,and lithium dendrite formation under low-temperature(LT)operation.Therefore,a more comprehensive and systematic understanding of LIB behavior at LT is urgently required.This review article comprehensively reviews recent advancements in electrolyte engineering strategies aimed at improving the low-temperature operational capabilities of LIBs.The study methodically examines critical performance-limiting mechanisms through fundamental analysis of four primary challenges:insufficient ionic conductivity under cryogenic conditions,kinetically hindered charge transfer processes,Li+transport limitations across the solidelectrolyte interphase(SEI),and uncontrolled lithium dendrite growth.The work elaborates on innovative optimization approaches encompassing lithium salt molecular design with tailored dissociation characteristics,solvent matrix optimization through dielectric constant and viscosity regulation,interfacial engineering additives for constructing low-impedance SEI layers,and gel-polymer composite electrolyte systems.Notably,particular emphasis is placed on emerging machine learning-guided electrolyte formulation strategies that enable high-throughput virtual screening of constituent combinations and prediction of structure-property relationships.These artificial intelligence-assisted rational design frameworks demonstrate significant potential for accelerating the development of next-generation LT electrolytes by establishing quantitative composition-performance correlations through advanced data-driven methodologies.展开更多
This study focused on improving the cathode performance of Ba_(0.6)Sr_(0.4)Co_(0.85)Nb_(0.15)O_(3-δ)(BSCN)-based perovskite materials through molybdenum(Mo)doping.Pure BSCN and Mo-modified-BSCN—Ea_(0.6)Sr_(0.4)Co_(0...This study focused on improving the cathode performance of Ba_(0.6)Sr_(0.4)Co_(0.85)Nb_(0.15)O_(3-δ)(BSCN)-based perovskite materials through molybdenum(Mo)doping.Pure BSCN and Mo-modified-BSCN—Ea_(0.6)Sr_(0.4)Co_(0.85)Nb_(0.1)Mo_(0.05)O_(3-δ)(B S CNM_(0.05)),Ba_(0.6)Sr_(0.4)Co_(0.85)Nb_(0.05)Mo_(0.1)O_(3-δ)(BSCNM_(0.1)),and Ba_(0.6)Sr_(0.4)Co_(0.85)Mo_(0.15)O_(3-δ)(BSCM)—with Mo doping contents of 5mol%,10mol%,and15mol%,respectively,were successfully prepared using the sol-gel method.The effects of Mo doping on the crystal structure,conductivity,thermal expansion coefficient,oxygen reduction reaction(ORR)activity,and electrochemical performance were systematically evaluated using X-ray diffraction analysis,thermally induced characterization,electrochemical impedance spectroscopy,and single-cell performance tests.The results revealed that Mo doping could improve the conductivity of the materials,suppress their thermal expansion effects,and significantly improve the electrochemical performance.Surface chemical state analysis using X-ray photoelectron spectroscopy revealed that 5mol%Mo doping could facilitate a high adsorbed oxygen concentration leading to enhanced ORR activity in the materials.Density functional theory calculations confirmed that Mo doping promoted the ORR activity in the materials.At an operating temperature of 600℃,the BSCNM_(0.05)cathode material exhibited significantly enhanced electrochemical impedance characteristics,with a reduced area specific resistance of 0.048Ω·cm~2,which was lower than that of the undoped BSCN matrix material by 32.39%.At the same operating temperature,an anode-supported single cell using a BSCNM_(0.05)cathode achieved a peak power density of 1477 mW·cm^(-2),which was 30.71%,56.30%,and 171.50%higher than those of BSCN,BSCNM_(0.1),and B SCM,respectively.The improved ORR activity and electrochemical performance of BSCNM_(0.05)indicate that it can be used as a cathode material in low-temperature solid oxide fuel cells.展开更多
In the image fusion field,fusing infrared images(IRIs)and visible images(VIs)excelled is a key area.The differences between IRIs and VIs make it challenging to fuse both types into a high-quality image.Accordingly,eff...In the image fusion field,fusing infrared images(IRIs)and visible images(VIs)excelled is a key area.The differences between IRIs and VIs make it challenging to fuse both types into a high-quality image.Accordingly,efficiently combining the advantages of both images while overcoming their shortcomings is necessary.To handle this challenge,we developed an end-to-end IRI andVI fusionmethod based on frequency decomposition and enhancement.By applying concepts from frequency domain analysis,we used the layering mechanism to better capture the salient thermal targets from the IRIs and the rich textural information from the VIs,respectively,significantly boosting the image fusion quality and effectiveness.In addition,the backbone network combined Restormer Blocks and Dense Blocks;Restormer blocks utilize global attention to extract shallow features.Meanwhile,Dense Blocks ensure the integration between shallow and deep features,thereby avoiding the loss of shallow attributes.Extensive experiments on TNO and MSRS datasets demonstrated that the suggested method achieved state-of-the-art(SOTA)performance in various metrics:Entropy(EN),Mutual Information(MI),Standard Deviation(SD),The Structural Similarity Index Measure(SSIM),Fusion quality(Qabf),MI of the pixel(FMI_(pixel)),and modified Visual Information Fidelity(VIF_(m)).展开更多
Upper Andean tropical forests are renowned for their extraordinary biodiversity and heterogeneous environmental conditions.Despite the critical role of litter decomposition in carbon and nutrient cycles,its dynamics i...Upper Andean tropical forests are renowned for their extraordinary biodiversity and heterogeneous environmental conditions.Despite the critical role of litter decomposition in carbon and nutrient cycles,its dynamics in this region remains unexplored at finer scales.This study investigates how micro site conditions influence litter decomposition of 15 upper Andean species over time.A reciprocal translocation field experiment was conducted over 18 months in 14 permanent plots within four sites in Colombian Andean mountain forests.Each plot contained three litterbeds(microsites),each with the 15 species,harvested at 3,6,12 and 18 months,totaling 2520 litterbags.Different forest variables,including canopy openness,leaf area index,slope and depth of litter,were measured in each litterbed.ANOVAs and linear mixed models were used to assess variation between sites and plots respectively,while multiple linear regression analyses evaluated the effects of forest variables on decay rates over time at the micro site scale.Results showed differences in absolute decay rates between sites but consistent relative decay rates,indicating varying magnitudes of decomposition,yet maintaining the same order based on their litter quality.Decay rates varied between species,with more variation in labile species compared to recalcitrant ones.Despite substantial variation in forest characteristics within sites,their influence on litter decomposition was minimal and declined over time.This suggests that,at finer spatial scales,the forest microenvironment plays a lesser role in litter decomposition,with litter quality emerging as the primary driver.This study is a step towards understanding the fine-scale dynamics of litter decomposition in upper Andean tropical forests,highlighting the intricate interplay between microenvironmental factors and decomposition processes.展开更多
Litter decomposition is an essential ecosystem process influenced by multiple factors,including substrate quality,climate,edaphic environment,and decomposer communities.However,the role of canopy species identity and ...Litter decomposition is an essential ecosystem process influenced by multiple factors,including substrate quality,climate,edaphic environment,and decomposer communities.However,the role of canopy species identity and diversity on leaf litter decomposition in forests remains understudied.By controlling for macroclimate,soil properties,and litter substrate in a mature common garden,we investigated whether a three-month tea bag incubation of standardized green and rooibos tea substrate is driven by canopy tree species characteristics and diversity.Our study hypothesized two primary pathways:a chemical engineering effect,where trees alter soil properties and decomposer communities through litter input,and a physical engineering effect,where tree canopy structure modulates the local microclimate.The results showed that even under uniform macroclimatic and initial soil conditions,mass loss rates varied widely for green tea(27.4%–73.2%)and rooibos tea(6.1%–34.7%),comparable as found in other research between distinct biomes.While substrate quality was the dominant factor,both engineering pathways and,to a minor extent,tree diversity modulated mass losses.For green tea,tree chemical and physical characteristics seemed equally important,while the physical environment showed an increased importance for rooibos.Incubation depth played a key role,where forest floor decomposition rates are more susceptible to temporal climate variations,and soil-layer decomposition rates are less susceptible to climate variations and more determined by tree species identity.Our findings suggest that tea bag experiments focusing solely on topsoil burial may underestimate processes in the forest floor and the mineralorganic boundary layer.This study underscores the critical role of litter substrate quality in decomposition while demonstrating that tree community composition and the associated herbaceous layer,through both chemical and physical engineering pathways,strongly modulate decomposition rates.展开更多
Theauthor proposes a dual layer source grid load storage collaborative planning model based on Benders decomposition to optimize the low-carbon and economic performance of the distribution network.The model plans the ...Theauthor proposes a dual layer source grid load storage collaborative planning model based on Benders decomposition to optimize the low-carbon and economic performance of the distribution network.The model plans the configuration of photovoltaic(3.8 MW),wind power(2.5 MW),energy storage(2.2 MWh),and SVC(1.2 Mvar)through interaction between upper and lower layers,and modifies lines 2–3,8–9,etc.to improve transmission capacity and voltage stability.The author uses normal distribution and Monte Carlo method to model load uncertainty,and combines Weibull distribution to describe wind speed characteristics.Compared to the traditional three-layer model(TLM),Benders decomposition-based two-layer model(BLBD)has a 58.1%reduction in convergence time(5.36 vs.12.78 h),a 51.1%reduction in iteration times(23 vs.47 times),a 8.07%reduction in total cost(12.436 vs.13.528 million yuan),and a 9.62%reduction in carbon emissions(12,456 vs.13,782 t).After optimization,the peak valley difference decreased from4.1 to 2.9MW,the renewable energy consumption rate reached 93.4%,and the energy storage efficiency was 87.6%.Themodel has been validated in the IEEE 33 node system,demonstrating its superiority in terms of economy,low-carbon,and reliability.展开更多
The integration of a high proportion of renewable energy introduces significant challenges for the adaptability of traditional fault nature identification methods.To address these challenges,this paper presents a nove...The integration of a high proportion of renewable energy introduces significant challenges for the adaptability of traditional fault nature identification methods.To address these challenges,this paper presents a novel fault nature identification method for renewable energy grid-connected interconnection lines,leveraging wavelet packet decomposition and voltage waveform time-frequency morphology comparison algorithms.First,the paper investigates the harmonic injection mechanism during non-full-phase operation following fault isolation in photovoltaic renewable energy systems,and examines the voltage characteristics of faulted phases in renewable energy scenarios.The analysis reveals that substantial differences exist in both the time and frequency domains of phase voltages before and after the extinction of transient faults,whereas permanent faults do not exhibit such variations.Building on this observation,the paper proposes a voltage time-frequency feature extraction method based on wavelet packet decomposition,wherein low-frequency waveform components are selected to characterize fault features.Subsequently,a fault nature identification method is introduced,based on a voltage waveform time-frequency morphology comparison.By employing a windowing technique to quantify waveform differences before and after arc extinction,this method effectively distinguishes between permanent and transient faults and accurately determines the arc extinction time.Finally,a 220 kV renewable energy grid connection line model is developed using PSCAD for verification.The results demonstrate that the proposed method is highly adaptable across various fault locations,transition resistances,and renewable energy control strategies,and can reliably identify fault nature in renewable energy grid connection scenarios.展开更多
The microstructural evolution of Cu−19Ni−6Cr−7Mn alloy during aging treatment was investigated.After aging for 120 min at 500℃,the alloy exhibited excellent mechanical properties,including a tensile strength of 978 M...The microstructural evolution of Cu−19Ni−6Cr−7Mn alloy during aging treatment was investigated.After aging for 120 min at 500℃,the alloy exhibited excellent mechanical properties,including a tensile strength of 978 MPa and an elastic modulus of 145.8 GPa.After aging for 240 min at 500℃,the elastic modulus of the alloy reached 149.5 GPa,which was among the highest values reported for Cu alloys.It was worth mentioning that the tensile strength increased rapidly from 740 to 934 MPa after aging for 5 min at 500℃,which was close to the maximum tensile strength(978 MPa).Analysis of the underlying strengthening mechanisms and phase transformation behavior revealed that the Cu−19Ni−6Cr−7Mn alloy underwent spinodal decomposition and DO_(22) ordering during the first 5 min of aging at 500℃,and L1_(2) ordered phases and bcc-Cr precipitates appeared.Therefore,the enhanced mechanical properties of the Cu−19Ni−6Cr−7Mn alloy can be attributed to the stress field generated by spinodal decomposition and the presence of nanoscale ordered phase and Cr precipitates.展开更多
In dry-coupled ultrasonic thickness measurement,thick rubber layers introduce high-amplitude parasitic echoes that obscure defect signals and degrade thickness accuracy.Existing methods struggle to resolve overlap-pin...In dry-coupled ultrasonic thickness measurement,thick rubber layers introduce high-amplitude parasitic echoes that obscure defect signals and degrade thickness accuracy.Existing methods struggle to resolve overlap-ping echoes under variable coupling conditions and non-stationary noise.This study proposes a novel dual-criterion framework integrating energy contribution and statistical impulsivity metrics to isolate specimen re-flections from coupling-layer interference.By decomposing A-scan signals into Intrinsic Mode Functions(IMFs),the framework employs energy contribution thresholds(>85%)and kurtosis indices(>3)to autonomously select IMFs containing valid specimen echoes.Hybrid time-frequency thresholding further suppresses interference through amplitude filtering and spectral focusing.Experimental results demonstrate the framework’s robustness,achieving 92.3%thickness accuracy for 5 mm steel specimens with 5 mm rubber coupling,outperforming conventional methods by up to 18.7%.The dual-criterion approach reduces operator dependency by 37%and maintainsΔT<0.03 mm under surface roughness up to 6.3μm,offering a practical solution for industrial nondestructive testing with thick dry-coupled interfaces.展开更多
Electrochemical metallurgy at low temperature(<473 K)shows promise for the extraction and refinement of metals and alloys in a green and sustainable manner.However,the kinetics of the electrodeposition process is g...Electrochemical metallurgy at low temperature(<473 K)shows promise for the extraction and refinement of metals and alloys in a green and sustainable manner.However,the kinetics of the electrodeposition process is generally slow at low temperature,resulting in large overpotential and low current efficiency.Thus,the application of external physical fields has emerged as an effective strategy for improving the mass and charge transfer processes during electrochemical reactions.This review highlights the challenges associated with low-temperature electrochemical processes and briefly discusses recent achievements in optimizing electrodeposition processes through the use of external physical fields.The regulating effects on the optimization of the electrodeposition process and the strategies for select-ing various external physical fields,including magnetic,supergravity,and ultrasonic fields are summarized from the perspectives of equipment and mechanisms.Finally,advanced methods for in-situ characterization of external physical field-assisted electrodeposition processes are reviewed to gain a deeper understanding of metallic electrodeposition.An in-depth exploration of the mechanism by which external physical fields affect the electrode process is essential for enhancing the efficiency of metal extraction at low temperatures.展开更多
Lithium-ion batteries are widely recognized as prime candidates for energy storage devices.Ethylene carbonate(EC)has become a critical component in conventional commercial electrolytes due to its exceptional film-form...Lithium-ion batteries are widely recognized as prime candidates for energy storage devices.Ethylene carbonate(EC)has become a critical component in conventional commercial electrolytes due to its exceptional film-forming properties and high dielectric constant.However,the elevated freezing point,high viscosity,and strong solvation energy of EC significantly hinder the transport rate of Li^(+)and the desolvation process at low temperatures.This leads to substantial capacity loss and even lithium plating on graphite anodes.Herein,we have developed an efficient electrolyte system specifically designed for lowtemperature conditions,which consists of 1.0 M lithium bis(fluorosulfonyl)imide(LiFSI)in isoxazole(IZ)with fluorobenzene(FB)as an uncoordinated solvent and fluoroethylene carbonate(FEC)as a filmforming co-solvent.This system effectively lowers the desolvation energy of Li^(+)through dipole-dipole interactions.The weak solvation capability allows more anions to enter the solvation sheath,promoting the formation of contact ion pairs(CIPs)and aggregates(AGGs)that enhance the transport rate of Li^(+)while maintaining high ionic conductivity across a broad temperature range.Moreover,the formation of inorganic-dominant interfacial phases on the graphite anode,induced by fluoroethylene carbonate,significantly enhances the kinetics of Li^(+)transport.At a low temperature of-20℃,this electrolyte system achieves an impressive reversible capacity of 200.9 mAh g^(-1)in graphite half-cell,which is nearly three times that observed with conventional EC-based electrolytes,demonstrating excellent stability throughout its operation.展开更多
To completely recover valuable elements and reduce the amount of waste,the impact of phosphoric acid on the decomposition of rare earth,fluorine and phosphorus during cyclic leaching was studied based on the character...To completely recover valuable elements and reduce the amount of waste,the impact of phosphoric acid on the decomposition of rare earth,fluorine and phosphorus during cyclic leaching was studied based on the characteristics of low-tempe rature sulfuric acid deco mposition.When a single monazite was leached using 75 wt% H_(2)SO_(4) solution with phosphoric acid,the size and number of monazite particles in the washing slag gradually decrease with the increase in phosphoric acid content in the leaching solution.The monazite phase can hardly be found in the slag when the phosphoric acid content reaches 70 g/L,which indicates that phosphoric acid is favorable for monazite decomposition.The mixed rare earth concentrate was leached by 75 wt% H_(2)SO_(4) containing 70 g/L phosphoric acid,the mineral compositions of the washing slag are only gypsum and unwashed rare earth sulfuric acid.After cyclic leaching of75 wt% H_(2)SO_(4),the mineral compositions of the primary leaching washing slag are mainly undecomposed monazite,rare earth sulfate and calcium sulfate.However,monazite is not found in the mineral phase of the second and third leaching washing slag.The leaching rates of rare earth and phosphorus gradually increase with the increase in cyclic leaching times.In addition,the phosphoric acid content in the leaching solution increases with the increase in the number of cyclic leaching time.However,the rising trend decreases when the phosphoric acid content reaches 50 g/L by adsorption and crystallization of phosphoric acid.A small amount of water can be used to clean the leaching residue before washing to recover the more soluble phosphorus acid according to the difference of dissolution between phosphoric acid and rare earth sulfuric acid.展开更多
The deployment of non-precious metal catalysts for the production of COx-free hydrogen via the ammonia decomposition reaction(ADR)presents a promising yet great challenge.In the present study,two crystal structures of...The deployment of non-precious metal catalysts for the production of COx-free hydrogen via the ammonia decomposition reaction(ADR)presents a promising yet great challenge.In the present study,two crystal structures of α-MoC and β-Mo_(2)C catalysts with different Mo/C ratios were synthesized,and their ammonia decomposition performance as well as structural evolution in ADR was investigated.The β-Mo_(2)C catalyst,characterized by a higher Mo/C ratio,demonstrated a remarkable turnover frequency of 1.3 s^(-1),which is over tenfold higher than that ofα-MoC(0.1 s^(-1)).An increase in the Mo/C ratio of molybdenum carbide revealed a direct correlation between the surface Mo/C ratio and the hydrogen yield.The transient response surface reaction indicated that the combination of N*and N*derived from NH_(3) dissociation represents the rate-determining step in the ADR,andβ-Mo2C exhibited exceptional proficiency in facilitating this pivotal step.Concurrently,the accumulation of N*species on the carbide surface could induce the phase transition of molybdenum carbide to nitride,which follows a topological transformation.It is discovered that such phase evolution was affected by the Mo-C surface and reaction temperature simultaneously.When the kinetics of combination of N*was accelerated by rising temperatures and its accumulation on the carbide surface was mitigated,β-Mo_(2)C maintained its carbide phase,preventing nitridation during the ADR at 810℃.Our results contribute to an in-depth understanding of the molybdenum carbides’catalytic properties in ADR and highlight the nature of the carbide-nitride phase transition in the reaction.展开更多
Machine-learning is a robust technique for understanding pollution characteristics of surface ozone,which are at high levels in urban China.This study introduced an innovative approach combining trend decomposition wi...Machine-learning is a robust technique for understanding pollution characteristics of surface ozone,which are at high levels in urban China.This study introduced an innovative approach combining trend decomposition with Random Forest algorithm to investigate ozone dynamics and formation regimes in a coastal area of China.During the period of 2017–2022,significant inter-annual fluctuations emerged,with peaks in mid-2017 attributed to volatile organic compounds(VOCs),and in late-2019 influenced by air temperature.Multifaceted periodicities(daily,weekly,holiday,and yearly)in ozone were revealed,elucidating substantial influences of daily and yearly components on ozone periodicity.A VOC-sensitive ozone formation regime was identified,characterized by lower VOCs/NO_(x) ratios(average=0.88)and significant positive correlations between ozone and VOCs.This interplay manifested in elevated ozone duringweekends,holidays,and pandemic lockdowns.Key variables influencing ozone across diverse timescaleswere uncovered,with solar radiation and temperature driving daily and yearly ozone variations,respectively.Precursor substances,particularly VOCs,significantly shaped weekly/holiday patterns and long-term trends of ozone.Specifically,acetone,ethane,hexanal,and toluene had a notable impact on the multi-year ozone trend,emphasizing the urgency of VOC regulation.Furthermore,our observations indicated that NO_(x) primarily drived the stochastic variations in ozone,a distinguishing characteristic of regions with heavy traffic.This research provides novel insights into ozone dynamics in coastal urban areas and highlights the importance of integrating statistical and machinelearning methods in atmospheric pollution studies,with implications for targeted mitigation strategies beyond this specific region and pollutant.展开更多
基金financial support by DST-SERB (Grant No.SRG/2021/001182)DRDO (Grant No.ARMREB/HEM/2021/241)is gratefully acknowledged。
文摘Ammonium dinitramide(ADN)based liquid monopropellants have been identified as environmentally benign substitutes for hydrazine monopropellant.However,new catalysts are to be developed for making ADN monopropellants cold-start capable.In the present study,performance of Co and Ba doped CuCr_2O_4 nanocatalysts prepared by hydrothermal method was evaluated on the decomposition of aqueous ADN solution and ADN liquid monopropellant(LMP103X).The catalysts were characterized by PXRD(Powder X-ray Diffraction),FTIR(Fourier Transform Infrared spectroscopy),SEM(Scanning Electron Microscopy),TEM(Transmission Electron Microscopy),EDS(Energy Dispersive X-ray Spectroscopy),and XPS(X-ray Photoelectron Spectroscopy).The nanosize was confirmed by SEM and TEM,while the nanoflake morphology was confirmed by the SEM analysis.Further,we obtained the elemental composition from the EDS analysis.We investigated the catalytic activity of the catalysts by thermogravimetric(TG)analysis and the developed catalysts lowered the decomposition temperature of ADN monopropellant by about 55℃.The XPS analysis confirmed the presence of metal ions with different chemical states.Apparently,increase in the surface area of the catalysts and the mixed active sites as well as the development of oxygen vacancy on the catalyst surface introduced by metal doping are influencing the decomposition temperature of ADN samples.
基金Supported by Innovative Research Groups of the National Natural Science Foundation of China(22021004)。
文摘Catalytic decomposition of methane,which produces high-purity hydrogen and high-value-added carbon nanomaterials,has shown considerable potential for development and is expected to yield significant economic benefits in the future.However,designing catalysts that simultaneously exhibit high activity and long-term stability remains a significant challenge.Tuning the catalyst’s structure and electronic properties is an effective strategy for enhancing the reaction performance.In this work,a series of NixZr/ZSM-5 catalysts were prepared using the incipient wetness impregnation method,and the effect of Zr loadings on catalyst properties and performance was systematically investigated.The calcined and reduced catalysts were characterized by low-temperature N_(2)adsorption-desorption,XRD,SEM,H_(2)-TPR and XPS.The results showed that the addition of Zr significantly increased the specific surface area of the catalyst and reduced the metal particle size.Smaller NiO particles were found to enter the pores of the HZSM-5 support,and electronic interactions between NiO and ZrO_(2)markedly enhanced the metal-support interaction.The catalyst exhibited optimal catalytic performance at a Zr loading of 5%,achieving a maximum methane conversion of 68%at 625℃,maintaining activity for 900 min,and delivering a carbon yield of 1927%.Further increasing the Zr loading yielded only limited improvements in catalytic performance.Characterization of the spent catalysts and carbon products via TEM,Raman spectroscopy,and TGA revealed that the introduction of ZrO_(2)reduced metal sintering and promoted a shift in carbon nanofibers growth mode from tip-growth to base-growth.The mechanism of base-growth enabled the catalyst to maintain reaction activity for an extended period.
基金sponsored by the Department of Defense,Defense Threat Reduction Agency under the Materials Science in Extreme Environments University Research Alliance,HDTRA1-20-2-0001。
文摘Chemical warfare agents(CWAs)remain a persistent hazard in many parts of the world,necessitating a deeper exploration of their chemical and physical characteristics and reactions under diverse conditions.Diisopropyl methylphosphonate(DIMP),a commonly used CWA surrogate,is widely studied to enhance our understanding of CWA behavior.The prevailing thermal decomposition model for DIMP,developed approximately 25 years ago,is based on data collected in nitrogen atmospheres at temperatures ranging from 700 K to 800 K.Despite its limitations,this model continues to serve as a foundation for research across various thermal and reactive environments,including combustion studies.Our recent experiments have extended the scope of decomposition analysis by examining DIMP in both nitrogen and zero air across a lower temperature range of 175℃ to 250℃.Infrared spectroscopy results under nitrogen align well with the established model;however,we observed that catalytic effects,stemming from decomposition byproducts and interactions with stainless steel surfaces,alter the reaction kinetics.In zero air environments,we observed a novel infrared absorption band.Spectral fitting suggests this band may represent a combination of propanal and acetone,while GCMS analysis points to vinyl formate and acetone as possible constituents.Although the precise identity of these new products remains unresolved,our findings clearly indicate that the existing decomposition model cannot be reliably extended to lower temperatures or non-nitrogen environments without further revisions.
基金Supported by National Natural Science Foundation of China(Grant No.52075236)Opening Foundation of Intelligent Manufacturing Technology(Shantou University),Ministry of Education(Grant No.STME2024002)+1 种基金Hundred Doctor and Hundred Enterprise,Science and Technology Project,Ji'an City(Grant No.42064001)Guangdong Provincial University Innovation Team Project(Grant No.2020KCXTD012).
文摘Current improved Empirical Mode Decomposition(EMD)methods enhance the accurate identification of peak and valley points in mechanical signals through noise-assisted filtering techniques,thereby improving the mode decomposition performance,which is of great significance in extracting fault features from mechanical signals.However,noise-assisted filtering leads to the loss of critical features in mechanical signals and introduces a large amount of residual noise into Intrinsic Mode Functions(IMFs)that obscure signal features.To address these issues,a Precise Identification-based Mode Decomposition(PIMD)method is proposed.This method directly enhances the ability of EMD to precisely identify peak and valley points by using a proposed precise identifi-cation approach,which improves mode decomposition performance and avoids the negative impacts of noise-assisted filtering,thus benefiting the extraction of more mechanical fault features.Simulation results show that the proposed PIMD method can precisely identify peak and valley points of signals with noise of different signal-tonoise ratios and perform a highly rigorous high-low frequency decomposition,significantly outperforming EMD.Finally,mechanical fault diagnostic experiments on four bearing cases and two gear cases demonstrate that,compared to four mainstream methods,the PIMD method exhibits the best mode decomposition perfor-mance and can extract more and clearer mechanical fault features.
基金the National Natural Science Foundation of China,grant number 52406074the China Postdoctoral Science Foundation under Grant Number 2025T180171+1 种基金the Natural Science Foundation of Guangdong Province(2025A1515011270)the China Southern Power Grid Technology Project(GDKJXM20231415/030100KC23120104).
文摘In order to explore the effects of CaO,lignite dust and sawdust on the drying characteristics ofmunicipal sludge at different concentrations,a three-factor three-level regression experiment was carried out based on the results of thermogravimetric experiment and single factor experiment.By fitting three common mathematical models,the Page model with the highest fitting degree was selected to determine the most suitable mathematical model to describe the municipal sludge drying process.In addition,the Box-Behnken design principle in the response surface method was used to analyze the interaction of three factors on the drying characteristics of municipal sludge.The results of the study show that below 100℃is the optimal drying temperature range for municipal sludge.The results of single factor experiments showed that the order of influence of the three factors on sludge drying time was CaO concentration>sawdust concentration>lignite dust concentration.In the single factor experiment,the optimal process parameterswere CaOconcentration 3%,lignite powder concentration 7%,and sawdust concentration 7%.In themulti-factor interaction analysis,the interaction between CaO and sawdust had the most significant effect on the reduction of drying time,and the order of influence was as follows:CaO interaction with sawdust>lignite dust interaction with sawdust>CaO interaction with lignite powder.Further analysis showed that the optimal process ratio was 3%CaO concentration and 3%sawdust concentration.
基金financially supported by the National Natural Science Foundation of China(Nos.52034002 and U2202254)the Fundamental Research Funds for the Central Universities,China(No.FRF-TT-19-001)。
文摘The sulfation and decomposition process has proven effective in selectively extracting lithium from lepidolite.It is essential to clarify the thermochemical behavior and kinetic parameters of decomposition reactions.Accordingly,comprehensive kinetic study by employing thermalgravimetric analysis at various heating rates was presented in this paper.Two main weight loss regions were observed during heating.The initial region corresponded to the dehydration of crystal water,whereas the subsequent region with overlapping peaks involved complex decomposition reactions.The overlapping peaks were separated into two individual reaction peaks and the activation energy of each peak was calculated using isoconversional kinetics methods.The activation energy of peak 1 exhibited a continual increase as the reaction conversion progressed,while that of peak 2 steadily decreased.The optimal kinetic models,identified as belonging to the random nucleation and subsequent growth category,provided valuable insights into the mechanism of the decomposition reactions.Furthermore,the adjustment factor was introduced to reconstruct the kinetic mechanism models,and the reconstructed models described the kinetic mechanism model more accurately for the decomposition reactions.This study enhanced the understanding of the thermochemical behavior and kinetic parameters of the lepidolite sulfation product decomposition reactions,further providing theoretical basis for promoting the selective extraction of lithium.
基金the financial support from the Key Project of Shaanxi Provincial Natural Science Foundation-Key Project of Laboratory(2025SYS-SYSZD-117)the Natural Science Basic Research Program of Shaanxi(2025JCYBQN-125)+8 种基金Young Talent Fund of Xi'an Association for Science and Technology(0959202513002)the Key Industrial Chain Technology Research Program of Xi'an(24ZDCYJSGG0048)the Key Research and Development Program of Xianyang(L2023-ZDYF-SF-077)Postdoctoral Fellowship Program of CPSF(GZC20241442)Shaanxi Postdoctoral Science Foundation(2024BSHSDZZ070)Research Funds for the Interdisciplinary Projects,CHU(300104240913)the Fundamental Research Funds for the Central Universities,CHU(300102385739,300102384201,300102384103)the Scientific Innovation Practice Project of Postgraduate of Chang'an University(300103725063)the financial support from the Australian Research Council。
文摘Lithium-ion batteries(LIBs),while dominant in energy storage due to high energy density and cycling stability,suffer from severe capacity decay,rate capability degradation,and lithium dendrite formation under low-temperature(LT)operation.Therefore,a more comprehensive and systematic understanding of LIB behavior at LT is urgently required.This review article comprehensively reviews recent advancements in electrolyte engineering strategies aimed at improving the low-temperature operational capabilities of LIBs.The study methodically examines critical performance-limiting mechanisms through fundamental analysis of four primary challenges:insufficient ionic conductivity under cryogenic conditions,kinetically hindered charge transfer processes,Li+transport limitations across the solidelectrolyte interphase(SEI),and uncontrolled lithium dendrite growth.The work elaborates on innovative optimization approaches encompassing lithium salt molecular design with tailored dissociation characteristics,solvent matrix optimization through dielectric constant and viscosity regulation,interfacial engineering additives for constructing low-impedance SEI layers,and gel-polymer composite electrolyte systems.Notably,particular emphasis is placed on emerging machine learning-guided electrolyte formulation strategies that enable high-throughput virtual screening of constituent combinations and prediction of structure-property relationships.These artificial intelligence-assisted rational design frameworks demonstrate significant potential for accelerating the development of next-generation LT electrolytes by establishing quantitative composition-performance correlations through advanced data-driven methodologies.
基金financially supported by the National Natural Science Foundation of China(No.22309067)the Open Project Program of the State Key Laboratory of Materials-Oriented Chemical Engineering,China(No.KL21-05)the Marine Equipment and Technology Institute,Jiangsu University of Science and Technology,China(No.XTCX202404)。
文摘This study focused on improving the cathode performance of Ba_(0.6)Sr_(0.4)Co_(0.85)Nb_(0.15)O_(3-δ)(BSCN)-based perovskite materials through molybdenum(Mo)doping.Pure BSCN and Mo-modified-BSCN—Ea_(0.6)Sr_(0.4)Co_(0.85)Nb_(0.1)Mo_(0.05)O_(3-δ)(B S CNM_(0.05)),Ba_(0.6)Sr_(0.4)Co_(0.85)Nb_(0.05)Mo_(0.1)O_(3-δ)(BSCNM_(0.1)),and Ba_(0.6)Sr_(0.4)Co_(0.85)Mo_(0.15)O_(3-δ)(BSCM)—with Mo doping contents of 5mol%,10mol%,and15mol%,respectively,were successfully prepared using the sol-gel method.The effects of Mo doping on the crystal structure,conductivity,thermal expansion coefficient,oxygen reduction reaction(ORR)activity,and electrochemical performance were systematically evaluated using X-ray diffraction analysis,thermally induced characterization,electrochemical impedance spectroscopy,and single-cell performance tests.The results revealed that Mo doping could improve the conductivity of the materials,suppress their thermal expansion effects,and significantly improve the electrochemical performance.Surface chemical state analysis using X-ray photoelectron spectroscopy revealed that 5mol%Mo doping could facilitate a high adsorbed oxygen concentration leading to enhanced ORR activity in the materials.Density functional theory calculations confirmed that Mo doping promoted the ORR activity in the materials.At an operating temperature of 600℃,the BSCNM_(0.05)cathode material exhibited significantly enhanced electrochemical impedance characteristics,with a reduced area specific resistance of 0.048Ω·cm~2,which was lower than that of the undoped BSCN matrix material by 32.39%.At the same operating temperature,an anode-supported single cell using a BSCNM_(0.05)cathode achieved a peak power density of 1477 mW·cm^(-2),which was 30.71%,56.30%,and 171.50%higher than those of BSCN,BSCNM_(0.1),and B SCM,respectively.The improved ORR activity and electrochemical performance of BSCNM_(0.05)indicate that it can be used as a cathode material in low-temperature solid oxide fuel cells.
基金funded by Anhui Province University Key Science and Technology Project(2024AH053415)Anhui Province University Major Science and Technology Project(2024AH040229)+3 种基金Talent Research Initiation Fund Project of Tongling University(2024tlxyrc019)Tongling University School-Level Scientific Research Project(2024tlxyptZD07)TheUniversity Synergy Innovation Programof Anhui Province(GXXT-2023-050)Tongling City Science and Technology Major Special Project(Unveiling and Commanding Model)(200401JB004).
文摘In the image fusion field,fusing infrared images(IRIs)and visible images(VIs)excelled is a key area.The differences between IRIs and VIs make it challenging to fuse both types into a high-quality image.Accordingly,efficiently combining the advantages of both images while overcoming their shortcomings is necessary.To handle this challenge,we developed an end-to-end IRI andVI fusionmethod based on frequency decomposition and enhancement.By applying concepts from frequency domain analysis,we used the layering mechanism to better capture the salient thermal targets from the IRIs and the rich textural information from the VIs,respectively,significantly boosting the image fusion quality and effectiveness.In addition,the backbone network combined Restormer Blocks and Dense Blocks;Restormer blocks utilize global attention to extract shallow features.Meanwhile,Dense Blocks ensure the integration between shallow and deep features,thereby avoiding the loss of shallow attributes.Extensive experiments on TNO and MSRS datasets demonstrated that the suggested method achieved state-of-the-art(SOTA)performance in various metrics:Entropy(EN),Mutual Information(MI),Standard Deviation(SD),The Structural Similarity Index Measure(SSIM),Fusion quality(Qabf),MI of the pixel(FMI_(pixel)),and modified Visual Information Fidelity(VIF_(m)).
基金supported by the Universidad del Rosario(Small grant ID:IV-FPD003)。
文摘Upper Andean tropical forests are renowned for their extraordinary biodiversity and heterogeneous environmental conditions.Despite the critical role of litter decomposition in carbon and nutrient cycles,its dynamics in this region remains unexplored at finer scales.This study investigates how micro site conditions influence litter decomposition of 15 upper Andean species over time.A reciprocal translocation field experiment was conducted over 18 months in 14 permanent plots within four sites in Colombian Andean mountain forests.Each plot contained three litterbeds(microsites),each with the 15 species,harvested at 3,6,12 and 18 months,totaling 2520 litterbags.Different forest variables,including canopy openness,leaf area index,slope and depth of litter,were measured in each litterbed.ANOVAs and linear mixed models were used to assess variation between sites and plots respectively,while multiple linear regression analyses evaluated the effects of forest variables on decay rates over time at the micro site scale.Results showed differences in absolute decay rates between sites but consistent relative decay rates,indicating varying magnitudes of decomposition,yet maintaining the same order based on their litter quality.Decay rates varied between species,with more variation in labile species compared to recalcitrant ones.Despite substantial variation in forest characteristics within sites,their influence on litter decomposition was minimal and declined over time.This suggests that,at finer spatial scales,the forest microenvironment plays a lesser role in litter decomposition,with litter quality emerging as the primary driver.This study is a step towards understanding the fine-scale dynamics of litter decomposition in upper Andean tropical forests,highlighting the intricate interplay between microenvironmental factors and decomposition processes.
基金funded by the Global PhD Scholarship between KU Leuven and UCLouvain。
文摘Litter decomposition is an essential ecosystem process influenced by multiple factors,including substrate quality,climate,edaphic environment,and decomposer communities.However,the role of canopy species identity and diversity on leaf litter decomposition in forests remains understudied.By controlling for macroclimate,soil properties,and litter substrate in a mature common garden,we investigated whether a three-month tea bag incubation of standardized green and rooibos tea substrate is driven by canopy tree species characteristics and diversity.Our study hypothesized two primary pathways:a chemical engineering effect,where trees alter soil properties and decomposer communities through litter input,and a physical engineering effect,where tree canopy structure modulates the local microclimate.The results showed that even under uniform macroclimatic and initial soil conditions,mass loss rates varied widely for green tea(27.4%–73.2%)and rooibos tea(6.1%–34.7%),comparable as found in other research between distinct biomes.While substrate quality was the dominant factor,both engineering pathways and,to a minor extent,tree diversity modulated mass losses.For green tea,tree chemical and physical characteristics seemed equally important,while the physical environment showed an increased importance for rooibos.Incubation depth played a key role,where forest floor decomposition rates are more susceptible to temporal climate variations,and soil-layer decomposition rates are less susceptible to climate variations and more determined by tree species identity.Our findings suggest that tea bag experiments focusing solely on topsoil burial may underestimate processes in the forest floor and the mineralorganic boundary layer.This study underscores the critical role of litter substrate quality in decomposition while demonstrating that tree community composition and the associated herbaceous layer,through both chemical and physical engineering pathways,strongly modulate decomposition rates.
文摘Theauthor proposes a dual layer source grid load storage collaborative planning model based on Benders decomposition to optimize the low-carbon and economic performance of the distribution network.The model plans the configuration of photovoltaic(3.8 MW),wind power(2.5 MW),energy storage(2.2 MWh),and SVC(1.2 Mvar)through interaction between upper and lower layers,and modifies lines 2–3,8–9,etc.to improve transmission capacity and voltage stability.The author uses normal distribution and Monte Carlo method to model load uncertainty,and combines Weibull distribution to describe wind speed characteristics.Compared to the traditional three-layer model(TLM),Benders decomposition-based two-layer model(BLBD)has a 58.1%reduction in convergence time(5.36 vs.12.78 h),a 51.1%reduction in iteration times(23 vs.47 times),a 8.07%reduction in total cost(12.436 vs.13.528 million yuan),and a 9.62%reduction in carbon emissions(12,456 vs.13,782 t).After optimization,the peak valley difference decreased from4.1 to 2.9MW,the renewable energy consumption rate reached 93.4%,and the energy storage efficiency was 87.6%.Themodel has been validated in the IEEE 33 node system,demonstrating its superiority in terms of economy,low-carbon,and reliability.
基金supported by State Grid Sichuan Electric Power Company science and technology project“Research on Key Technologies for Reclosing of High-Ratio New Energy Grid Connection Lines.”(Program No:52199723002Q).
文摘The integration of a high proportion of renewable energy introduces significant challenges for the adaptability of traditional fault nature identification methods.To address these challenges,this paper presents a novel fault nature identification method for renewable energy grid-connected interconnection lines,leveraging wavelet packet decomposition and voltage waveform time-frequency morphology comparison algorithms.First,the paper investigates the harmonic injection mechanism during non-full-phase operation following fault isolation in photovoltaic renewable energy systems,and examines the voltage characteristics of faulted phases in renewable energy scenarios.The analysis reveals that substantial differences exist in both the time and frequency domains of phase voltages before and after the extinction of transient faults,whereas permanent faults do not exhibit such variations.Building on this observation,the paper proposes a voltage time-frequency feature extraction method based on wavelet packet decomposition,wherein low-frequency waveform components are selected to characterize fault features.Subsequently,a fault nature identification method is introduced,based on a voltage waveform time-frequency morphology comparison.By employing a windowing technique to quantify waveform differences before and after arc extinction,this method effectively distinguishes between permanent and transient faults and accurately determines the arc extinction time.Finally,a 220 kV renewable energy grid connection line model is developed using PSCAD for verification.The results demonstrate that the proposed method is highly adaptable across various fault locations,transition resistances,and renewable energy control strategies,and can reliably identify fault nature in renewable energy grid connection scenarios.
基金supported by the National Key R&D Program of China (No. 2021YFB3700700)the Henan Province Top Talent Training Program Project, China (No. 244500510020)the High-level Talent Research Start-up Project Funding of Henan Academy of Sciences, China (No. 242017001)。
文摘The microstructural evolution of Cu−19Ni−6Cr−7Mn alloy during aging treatment was investigated.After aging for 120 min at 500℃,the alloy exhibited excellent mechanical properties,including a tensile strength of 978 MPa and an elastic modulus of 145.8 GPa.After aging for 240 min at 500℃,the elastic modulus of the alloy reached 149.5 GPa,which was among the highest values reported for Cu alloys.It was worth mentioning that the tensile strength increased rapidly from 740 to 934 MPa after aging for 5 min at 500℃,which was close to the maximum tensile strength(978 MPa).Analysis of the underlying strengthening mechanisms and phase transformation behavior revealed that the Cu−19Ni−6Cr−7Mn alloy underwent spinodal decomposition and DO_(22) ordering during the first 5 min of aging at 500℃,and L1_(2) ordered phases and bcc-Cr precipitates appeared.Therefore,the enhanced mechanical properties of the Cu−19Ni−6Cr−7Mn alloy can be attributed to the stress field generated by spinodal decomposition and the presence of nanoscale ordered phase and Cr precipitates.
基金funded by the National Natural Science Foundation of China,grant number U24A20135Inner Mongolia Natural Science Foundation major project,grant number 2023ZD12+7 种基金Inner Mongolia Autonomous Region key research and development and achievement transformation plan project,grant number 2023YFHH0090Natural Science Foundation of Inner Mongolia,grant number 2022MS05006Inner Mongolia Autonomous Region Talent Development FundUniversity basic research business expenses,grant number 2023RCTD012University basic research business expenses,grant number 2023QNJS075Postgraduate Research Innovation Program and of Inner Mongolia Autonomous Region,grant number KC2024053BUniversity basic research business expenses,grant number 2024YXXS012National Key Laboratory of Special Vehicle Design and Manufacturing Integration Technology,grant number GZ2023KF012.
文摘In dry-coupled ultrasonic thickness measurement,thick rubber layers introduce high-amplitude parasitic echoes that obscure defect signals and degrade thickness accuracy.Existing methods struggle to resolve overlap-ping echoes under variable coupling conditions and non-stationary noise.This study proposes a novel dual-criterion framework integrating energy contribution and statistical impulsivity metrics to isolate specimen re-flections from coupling-layer interference.By decomposing A-scan signals into Intrinsic Mode Functions(IMFs),the framework employs energy contribution thresholds(>85%)and kurtosis indices(>3)to autonomously select IMFs containing valid specimen echoes.Hybrid time-frequency thresholding further suppresses interference through amplitude filtering and spectral focusing.Experimental results demonstrate the framework’s robustness,achieving 92.3%thickness accuracy for 5 mm steel specimens with 5 mm rubber coupling,outperforming conventional methods by up to 18.7%.The dual-criterion approach reduces operator dependency by 37%and maintainsΔT<0.03 mm under surface roughness up to 6.3μm,offering a practical solution for industrial nondestructive testing with thick dry-coupled interfaces.
基金supported by Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(No.SML2023SP243)the National Key Research and Development Program of China(No.2022YFC2906100)the National Natural Science Foundation of China(No.92475202)are acknowledged.
文摘Electrochemical metallurgy at low temperature(<473 K)shows promise for the extraction and refinement of metals and alloys in a green and sustainable manner.However,the kinetics of the electrodeposition process is generally slow at low temperature,resulting in large overpotential and low current efficiency.Thus,the application of external physical fields has emerged as an effective strategy for improving the mass and charge transfer processes during electrochemical reactions.This review highlights the challenges associated with low-temperature electrochemical processes and briefly discusses recent achievements in optimizing electrodeposition processes through the use of external physical fields.The regulating effects on the optimization of the electrodeposition process and the strategies for select-ing various external physical fields,including magnetic,supergravity,and ultrasonic fields are summarized from the perspectives of equipment and mechanisms.Finally,advanced methods for in-situ characterization of external physical field-assisted electrodeposition processes are reviewed to gain a deeper understanding of metallic electrodeposition.An in-depth exploration of the mechanism by which external physical fields affect the electrode process is essential for enhancing the efficiency of metal extraction at low temperatures.
基金financial support from the Department of Science and Technology of Jilin Province(20240304104SF,20240304103SF)the Research and Innovation Fund of the Beihua University for the Graduate Student(Major Project 2023012)。
文摘Lithium-ion batteries are widely recognized as prime candidates for energy storage devices.Ethylene carbonate(EC)has become a critical component in conventional commercial electrolytes due to its exceptional film-forming properties and high dielectric constant.However,the elevated freezing point,high viscosity,and strong solvation energy of EC significantly hinder the transport rate of Li^(+)and the desolvation process at low temperatures.This leads to substantial capacity loss and even lithium plating on graphite anodes.Herein,we have developed an efficient electrolyte system specifically designed for lowtemperature conditions,which consists of 1.0 M lithium bis(fluorosulfonyl)imide(LiFSI)in isoxazole(IZ)with fluorobenzene(FB)as an uncoordinated solvent and fluoroethylene carbonate(FEC)as a filmforming co-solvent.This system effectively lowers the desolvation energy of Li^(+)through dipole-dipole interactions.The weak solvation capability allows more anions to enter the solvation sheath,promoting the formation of contact ion pairs(CIPs)and aggregates(AGGs)that enhance the transport rate of Li^(+)while maintaining high ionic conductivity across a broad temperature range.Moreover,the formation of inorganic-dominant interfacial phases on the graphite anode,induced by fluoroethylene carbonate,significantly enhances the kinetics of Li^(+)transport.At a low temperature of-20℃,this electrolyte system achieves an impressive reversible capacity of 200.9 mAh g^(-1)in graphite half-cell,which is nearly three times that observed with conventional EC-based electrolytes,demonstrating excellent stability throughout its operation.
基金support by the National Natural Science Foundation of Inner Mongolia (2022SHZR1885)Natural Science Foundation of Hebei province (E2022402101,E2022402105)。
文摘To completely recover valuable elements and reduce the amount of waste,the impact of phosphoric acid on the decomposition of rare earth,fluorine and phosphorus during cyclic leaching was studied based on the characteristics of low-tempe rature sulfuric acid deco mposition.When a single monazite was leached using 75 wt% H_(2)SO_(4) solution with phosphoric acid,the size and number of monazite particles in the washing slag gradually decrease with the increase in phosphoric acid content in the leaching solution.The monazite phase can hardly be found in the slag when the phosphoric acid content reaches 70 g/L,which indicates that phosphoric acid is favorable for monazite decomposition.The mixed rare earth concentrate was leached by 75 wt% H_(2)SO_(4) containing 70 g/L phosphoric acid,the mineral compositions of the washing slag are only gypsum and unwashed rare earth sulfuric acid.After cyclic leaching of75 wt% H_(2)SO_(4),the mineral compositions of the primary leaching washing slag are mainly undecomposed monazite,rare earth sulfate and calcium sulfate.However,monazite is not found in the mineral phase of the second and third leaching washing slag.The leaching rates of rare earth and phosphorus gradually increase with the increase in cyclic leaching times.In addition,the phosphoric acid content in the leaching solution increases with the increase in the number of cyclic leaching time.However,the rising trend decreases when the phosphoric acid content reaches 50 g/L by adsorption and crystallization of phosphoric acid.A small amount of water can be used to clean the leaching residue before washing to recover the more soluble phosphorus acid according to the difference of dissolution between phosphoric acid and rare earth sulfuric acid.
文摘The deployment of non-precious metal catalysts for the production of COx-free hydrogen via the ammonia decomposition reaction(ADR)presents a promising yet great challenge.In the present study,two crystal structures of α-MoC and β-Mo_(2)C catalysts with different Mo/C ratios were synthesized,and their ammonia decomposition performance as well as structural evolution in ADR was investigated.The β-Mo_(2)C catalyst,characterized by a higher Mo/C ratio,demonstrated a remarkable turnover frequency of 1.3 s^(-1),which is over tenfold higher than that ofα-MoC(0.1 s^(-1)).An increase in the Mo/C ratio of molybdenum carbide revealed a direct correlation between the surface Mo/C ratio and the hydrogen yield.The transient response surface reaction indicated that the combination of N*and N*derived from NH_(3) dissociation represents the rate-determining step in the ADR,andβ-Mo2C exhibited exceptional proficiency in facilitating this pivotal step.Concurrently,the accumulation of N*species on the carbide surface could induce the phase transition of molybdenum carbide to nitride,which follows a topological transformation.It is discovered that such phase evolution was affected by the Mo-C surface and reaction temperature simultaneously.When the kinetics of combination of N*was accelerated by rising temperatures and its accumulation on the carbide surface was mitigated,β-Mo_(2)C maintained its carbide phase,preventing nitridation during the ADR at 810℃.Our results contribute to an in-depth understanding of the molybdenum carbides’catalytic properties in ADR and highlight the nature of the carbide-nitride phase transition in the reaction.
基金supported by Ningbo Natural Science Foundation(No.2023J059)Ningbo Commonweal Programme Key Project(No.2023S038)Guangxi Key Research and Development Programme(No.GuikeAB21220063).
文摘Machine-learning is a robust technique for understanding pollution characteristics of surface ozone,which are at high levels in urban China.This study introduced an innovative approach combining trend decomposition with Random Forest algorithm to investigate ozone dynamics and formation regimes in a coastal area of China.During the period of 2017–2022,significant inter-annual fluctuations emerged,with peaks in mid-2017 attributed to volatile organic compounds(VOCs),and in late-2019 influenced by air temperature.Multifaceted periodicities(daily,weekly,holiday,and yearly)in ozone were revealed,elucidating substantial influences of daily and yearly components on ozone periodicity.A VOC-sensitive ozone formation regime was identified,characterized by lower VOCs/NO_(x) ratios(average=0.88)and significant positive correlations between ozone and VOCs.This interplay manifested in elevated ozone duringweekends,holidays,and pandemic lockdowns.Key variables influencing ozone across diverse timescaleswere uncovered,with solar radiation and temperature driving daily and yearly ozone variations,respectively.Precursor substances,particularly VOCs,significantly shaped weekly/holiday patterns and long-term trends of ozone.Specifically,acetone,ethane,hexanal,and toluene had a notable impact on the multi-year ozone trend,emphasizing the urgency of VOC regulation.Furthermore,our observations indicated that NO_(x) primarily drived the stochastic variations in ozone,a distinguishing characteristic of regions with heavy traffic.This research provides novel insights into ozone dynamics in coastal urban areas and highlights the importance of integrating statistical and machinelearning methods in atmospheric pollution studies,with implications for targeted mitigation strategies beyond this specific region and pollutant.
