Multivariate time series forecasting iswidely used in traffic planning,weather forecasting,and energy consumption.Series decomposition algorithms can help models better understand the underlying patterns of the origin...Multivariate time series forecasting iswidely used in traffic planning,weather forecasting,and energy consumption.Series decomposition algorithms can help models better understand the underlying patterns of the original series to improve the forecasting accuracy of multivariate time series.However,the decomposition kernel of previous decomposition-based models is fixed,and these models have not considered the differences in frequency fluctuations between components.These problems make it difficult to analyze the intricate temporal variations of real-world time series.In this paper,we propose a series decomposition-based Mamba model,DecMamba,to obtain the intricate temporal dependencies and the dependencies among different variables of multivariate time series.A variable-level adaptive kernel combination search module is designed to interact with information on different trends and periods between variables.Two backbone structures are proposed to emphasize the differences in frequency fluctuations of seasonal and trend components.Mamba with superior performance is used instead of a Transformer in backbone structures to capture the dependencies among different variables.A new embedding block is designed to capture the temporal features better,especially for the high-frequency seasonal component whose semantic information is difficult to acquire.A gating mechanism is introduced to the decoder in the seasonal backbone to improve the prediction accuracy.A comparison with ten state-of-the-art models on seven real-world datasets demonstrates that DecMamba can better model the temporal dependencies and the dependencies among different variables,guaranteeing better prediction performance for multivariate time series.展开更多
The multi-objective particle swarm optimization algorithm(MOPSO)is widely used to solve multi-objective optimization problems.In the article,amulti-objective particle swarm optimization algorithmbased on decomposition...The multi-objective particle swarm optimization algorithm(MOPSO)is widely used to solve multi-objective optimization problems.In the article,amulti-objective particle swarm optimization algorithmbased on decomposition and multi-selection strategy is proposed to improve the search efficiency.First,two update strategies based on decomposition are used to update the evolving population and external archive,respectively.Second,a multiselection strategy is designed.The first strategy is for the subspace without a non-dominated solution.Among the neighbor particles,the particle with the smallest penalty-based boundary intersection value is selected as the global optimal solution and the particle far away fromthe search particle and the global optimal solution is selected as the personal optimal solution to enhance global search.The second strategy is for the subspace with a non-dominated solution.In the neighbor particles,two particles are randomly selected,one as the global optimal solution and the other as the personal optimal solution,to enhance local search.The third strategy is for Pareto optimal front(PF)discontinuity,which is identified by the cumulative number of iterations of the subspace without non-dominated solutions.In the subsequent iteration,a new probability distribution is used to select from the remaining subspaces to search.Third,an adaptive inertia weight update strategy based on the dominated degree is designed to further improve the search efficiency.Finally,the proposed algorithmis compared with fivemulti-objective particle swarm optimization algorithms and five multi-objective evolutionary algorithms on 22 test problems.The results show that the proposed algorithm has better performance.展开更多
We presented the preparation and analysis of La_(1-x)K_(x)CoO_(3)(x=0.1-0.4)catalysts,supported on microwave-absorbing ceramic carriers,using the sol-gel method.We systematically investigated the effects of various re...We presented the preparation and analysis of La_(1-x)K_(x)CoO_(3)(x=0.1-0.4)catalysts,supported on microwave-absorbing ceramic carriers,using the sol-gel method.We systematically investigated the effects of various reaction conditions under microwave irradiation(0-50 W).These conditions included reaction temperatures(300-600℃),oxygen concentrations(0-6%),and varying K^(+)doping levels on the catalysts'activity.The crystalline phase,microstructure,and the catalytic activity of the catalyst were analyzed by XRD,TEM,H_2-TPR,and O_(2)-TPD.The experimental results reveal that La_(1-x)K_(x)CoO_(3)(x=0.1-0.4)catalysts consistently form homogeneous perovskite nanoparticles across different doping levels.The NO decomposition efficiency on these catalysts initially increases and then decreases with variations in doping amount,temperature,and microwave power.Additionally,an increase in oxygen concentration positively influences NO conversion rates.The optimal performance is observed with La_(0.7)K_(0.3)CoO_(3)catalyst under conditions of x=0.3,400℃,10 W microwave power,and 4%oxygen concentration,achieving a peak NO conversion rate of La_(0.7)K_(0.3)CoO_(3)catalyst is 93.1%.展开更多
Flammable ionic liquids exhibit high conductivity and a broad electrochemical window,enabling the generation of combustible gases for combustion via electrochemical decomposition and thermal decomposition.This charact...Flammable ionic liquids exhibit high conductivity and a broad electrochemical window,enabling the generation of combustible gases for combustion via electrochemical decomposition and thermal decomposition.This characteristic holds significant implications in the realm of novel satellite propulsion.Introducing a fraction of the electrical energy into energetic ionic liquid fuels,the thermal decomposition process is facilitated by reducing the apparent activation energy required,and electrical energy can trigger the electrochemical decomposition of ionic liquids,presenting a promising approach to enhance combustion efficiency and energy release.This study applied an external voltage during the thermal decomposition of 1-ethyl-3-methylimidazole nitrate([EMIm]NO_(3)),revealing the effective alteration of the activation energy of[EMIm]NO_(3).The pyrolysis,electrochemical decomposition,and electron assisted enhancement products were identified through Thermogravimetry-Differential scanning calorimetry-Fourier transform infrared-Mass spectrometry(TG-DSC-FTIR-MS)and gas chromatography(GC)analyses,elucidating the degradation mechanism of[EMIm]NO_(3).Furthermore,an external voltage was introduced during the combustion of[EMIm]NO_(3),demonstrating the impact of voltage on the combustion process.展开更多
A P-band polarimetric synthetic aperture radar(PolSAR)sensor has deep penetration ability into and through the vegetation canopies in forested environments.Thus,the sensor is of great potential to accurately assess fo...A P-band polarimetric synthetic aperture radar(PolSAR)sensor has deep penetration ability into and through the vegetation canopies in forested environments.Thus,the sensor is of great potential to accurately assess forest parameters such as coverage,stand density,and tree height.Unfortunately,the radar backscatter from complex terrain can adversely impact the backscatter from trees or forests,and forest parameters assessed can be erroneous.Thus,reducing the topographic impact is an urgent must.In this study,a topographic compensation algorithm has been studied.To assess the algorithm’s validity and effectiveness,we applied it to P-band PolSAR datasets in four forested areas in the US.Trees in the forest stands have diverse species,and the topographic conditions of the terrain differ.Significant topographic impact on the P-band PolSAR data exists before the topographic compensation algorithm.After the algorithm,the impact decreases noticeably qualitatively and quantitatively.The algorithm is valid and effective in reducing the topographic influence on the PolSAR data and,consequently,provides a better chance of retrieving accurate forest parameters.展开更多
The remarkable properties of carbon nanotubes(CNTs)have led to promising applications in the field of electromagnetic inter-ference(EMI)shielding.However,for macroscopic CNT assemblies,such as CNT film,achieving high ...The remarkable properties of carbon nanotubes(CNTs)have led to promising applications in the field of electromagnetic inter-ference(EMI)shielding.However,for macroscopic CNT assemblies,such as CNT film,achieving high electrical and mechanical properties remains challenging,which heavily depends on the tube-tube interac-tions of CNTs.Herein,we develop a novel strategy based on metal-organic decomposition(MOD)to fabricate a flexible silver-carbon nanotube(Ag-CNT)film.The Ag particles are introduced in situ into the CNT film through annealing of MOD,leading to enhanced tube-tube interactions.As a result,the electrical conductivity of Ag-CNT film is up to 6.82×10^(5) S m^(-1),and the EMI shielding effectiveness of Ag-CNT film with a thickness of~7.8μm exceeds 66 dB in the ultra-broad frequency range(3-40 GHz).The tensile strength and Young’s modulus of Ag-CNT film increase from 30.09±3.14 to 76.06±6.20 MPa(~253%)and from 1.12±0.33 to 8.90±0.97 GPa(~795%),respectively.Moreover,the Ag-CNT film exhibits excellent near-field shield-ing performance,which can effectively block wireless transmission.This innovative approach provides an effective route to further apply macroscopic CNT assemblies to future portable and wearable electronic devices.展开更多
To study the formation and transformation mechanism of long-period stacked ordered(LPSO)structures,a systematic atomic scale analysis was conducted for the structural evolution of long-period stacked ordered(LPSO)stru...To study the formation and transformation mechanism of long-period stacked ordered(LPSO)structures,a systematic atomic scale analysis was conducted for the structural evolution of long-period stacked ordered(LPSO)structures in the Mg-Gd-Y-Zn-Zr alloy annealed at 300℃~500℃.Various types of metastable LPSO building block clusters were found to exist in alloy structures at different temperatures,which precipitate during the solidification and homogenization process.The stability of Zn/Y clusters is explained by the first principles of density functional theory.The LPSO structure is distinguished by the arrangement of its different Zn/Y enriched LPSO structural units,which comprises local fcc stacking sequences upon a tightly packed plane.The presence of solute atoms causes local lattice distortion,thereby enabling the rearrangement of Mg atoms in the different configurations in the local lattice,and local HCP-FCC transitions occur between Mg and Zn atoms occupying the nearest neighbor positions.This finding indicates that LPSO structures can generate necessary Schockley partial dislocations on specific slip surfaces,providing direct evidence of the transition from 18R to 14H.Growth of the LPSO,devoid of any defects and non-coherent interfaces,was observed separately from other precipitated phases.As a result,the precipitation sequence of LPSO in the solidification stage was as follows:Zn/Ycluster+Mg layers→various metastable LPSO building block clusters→18R/24R LPSO;whereas the precipitation sequence of LPSO during homogenization treatment was observed to be as follows:18R LPSO→various metastable LPSO building block clusters→14H LPSO.Of these,14H LPSO was found to be the most thermodynamically stable structure.展开更多
2,6-bis(picrylamino)-3,5-dinitropyridine(PYX)has excellent thermostability,which makes its thermal decomposition mechanism receive much attention.In this paper,the mechanism of PYX thermal decomposition was investigat...2,6-bis(picrylamino)-3,5-dinitropyridine(PYX)has excellent thermostability,which makes its thermal decomposition mechanism receive much attention.In this paper,the mechanism of PYX thermal decomposition was investigated thoroughly by the ReaxFF-lg force field combined with DFT-B3LYP(6-311++G)method.The detailed decomposition mechanism,small-molecule product evolution,and cluster evolution of PYX were mainly analyzed.In the initial stage of decomposition,the intramolecular hydrogen transfer reaction and the formation of dimerized clusters are earlier than the denitration reaction.With the progress of the reaction,one side of the bitter amino group is removed from the pyridine ring,and then the pyridine ring is cleaved.The final products produced in the thermal decomposition process are CO_(2),H_(2)O,N_(2),and H_(2).Among them,H_(2)O has the earliest generation time,and the reaction rate constant(k_(3))is the largest.Many clusters are formed during the decomposition of PYX,and the formation,aggregation,and decomposition of these clusters are strongly affected by temperature.At low temperatures(2500 K-2750 K),many clusters are formed.At high temperatures(2750 K-3250 K),the clusters aggregate to form larger clusters.At 3500 K,the large clusters decompose and become small.In the late stage of the reaction,H and N in the clusters escaped almost entirely,but more O was trapped in the clusters,which affected the auto-oxidation process of PYX.PYX's initial decomposition activation energy(E_(a))was calculated to be 126.58 kJ/mol.This work contributes to a theoretical understanding of PYX's entire thermal decomposition process.展开更多
When investigating the vortex-induced vibration(VIV)of marine risers,extrapolating the dynamic response on the entire length based on limited sensor measurements is a crucial step in both laboratory experiments and fa...When investigating the vortex-induced vibration(VIV)of marine risers,extrapolating the dynamic response on the entire length based on limited sensor measurements is a crucial step in both laboratory experiments and fatigue monitoring of real risers.The problem is conventionally solved using the modal decomposition method,based on the principle that the response can be approximated by a weighted sum of limited vibration modes.However,the method is not valid when the problem is underdetermined,i.e.,the number of unknown mode weights is more than the number of known measurements.This study proposed a sparse modal decomposition method based on the compressed sensing theory and the Compressive Sampling Matching Pursuit(Co Sa MP)algorithm,exploiting the sparsity of VIV in the modal space.In the validation study based on high-order VIV experiment data,the proposed method successfully reconstructed the response using only seven acceleration measurements when the conventional methods failed.A primary advantage of the proposed method is that it offers a completely data-driven approach for the underdetermined VIV reconstruction problem,which is more favorable than existing model-dependent solutions for many practical applications such as riser structural health monitoring.展开更多
A modified multiple-component scattering power decomposition for analyzing polarimetric synthetic aperture radar(PolSAR)data is proposed.The modified decomposition involves two distinct steps.Firstly,ei⁃genvectors of ...A modified multiple-component scattering power decomposition for analyzing polarimetric synthetic aperture radar(PolSAR)data is proposed.The modified decomposition involves two distinct steps.Firstly,ei⁃genvectors of the coherency matrix are used to modify the scattering models.Secondly,the entropy and anisotro⁃py of targets are used to improve the volume scattering power.With the guarantee of high double-bounce scatter⁃ing power in the urban areas,the proposed algorithm effectively improves the volume scattering power of vegeta⁃tion areas.The efficacy of the modified multiple-component scattering power decomposition is validated using ac⁃tual AIRSAR PolSAR data.The scattering power obtained through decomposing the original coherency matrix and the coherency matrix after orientation angle compensation is compared with three algorithms.Results from the experiment demonstrate that the proposed decomposition yields more effective scattering power for different PolSAR data sets.展开更多
Ammonia decomposition is a key reaction in the context of hydrogen storage, transport, and release. This study combines density functional theory(DFT) calculations with microkinetic modeling to address the promotion m...Ammonia decomposition is a key reaction in the context of hydrogen storage, transport, and release. This study combines density functional theory(DFT) calculations with microkinetic modeling to address the promotion mechanism of Ba species for ammonia decomposition on Co catalysts. The modified adsorption properties of Co upon the addition of metallic Ba or BaO suggest that the promoters play a role in alleviating the competitive adsorption of H. Calculating the full reaction pathway of ammonia decomposition shows that limiting the investigation to the N–N association step, as done previously, overlooks the effect of the promoter on the energy barriers of the NHxdehydrogenation steps. Challenges of modeling the ammonia decomposition reaction are addressed by understanding that the NH_(2) intermediate is stabilized on the step sites rather than the terrace sites. When the effect of H-coverage on the adsorption of NH_(3) is not considered in the microkinetic simulations, the results conflict with the experiments.However, accounting for the effect of H-coverage, as performed here, shows that BaO-doped Co has higher rates than pristine Co and Ba-doped Co at the reaction temperature of 723.15 K. When H is adsorbed on the Ba-doped Co, the adsorption of ammonia becomes significantly endergonic, which makes the rates relatively slow. The superiority of the BaO-promoted catalyst is attributed to a lower energy for the transition state of the rate-determining step, coupled with a reduced impact of the hydrogen coverage on weakening the ammonia adsorption. The kinetic analysis of the influence of Ba and BaO on the Co surface shows that BaO-doped Co aligns more closely with experimental observations than Badoped Co. This implies that Ba on the Co surface is likely to be in an oxide form under reaction conditions.Understanding the kinetics of the ammonia decomposition reaction provides a foundation for developing highly effective catalysts to accelerate the industrial utilization of ammonia as a sustainable hydrogen carrier.展开更多
Natural gas hydrate is an energy resource for methane that has a carbon quantity twice more than all traditional fossil fuels combined.However,their practical application in the field has been limited due to the chall...Natural gas hydrate is an energy resource for methane that has a carbon quantity twice more than all traditional fossil fuels combined.However,their practical application in the field has been limited due to the challenges of long-term preparation,high costs and associated risks.Experimental studies,on the other hand,offer a safe and cost-effective means of exploring the mechanisms of hydrate dissociation and optimizing exploitation conditions.Gas hydrate decomposition is a complicated process along with intrinsic kinetics,mass transfer and heat transfer,which are the influencing factors for hydrate decomposition rate.The identification of the rate-limiting factor for hydrate dissociation during depressurization varies with the scale of the reservoir,making it challenging to extrapolate findings from laboratory experiments to the actual exploitation.This review aims to summarize current knowledge of investigations on hydrate decomposition on the subject of the research scale(core scale,middle scale,large scale and field tests)and to analyze determining factors for decomposition rate,considering the various research scales and their associated influencing factors.展开更多
Decomposition of a complex multi-objective optimisation problem(MOP)to multiple simple subMOPs,known as M2M for short,is an effective approach to multi-objective optimisation.However,M2M facilitates little communicati...Decomposition of a complex multi-objective optimisation problem(MOP)to multiple simple subMOPs,known as M2M for short,is an effective approach to multi-objective optimisation.However,M2M facilitates little communication/collaboration between subMOPs,which limits its use in complex optimisation scenarios.This paper extends the M2M framework to develop a unified algorithm for both multi-objective and manyobjective optimisation.Through bilevel decomposition,an MOP is divided into multiple subMOPs at upper level,each of which is further divided into a number of single-objective subproblems at lower level.Neighbouring subMOPs are allowed to share some subproblems so that the knowledge gained from solving one subMOP can be transferred to another,and eventually to all the subMOPs.The bilevel decomposition is readily combined with some new mating selection and population update strategies,leading to a high-performance algorithm that competes effectively against a number of state-of-the-arts studied in this paper for both multiand many-objective optimisation.Parameter analysis and component analysis have been also carried out to further justify the proposed algorithm.展开更多
In a“low-carbon”context,the power load is affected by the coupling of multiple factors,which gradually evolves from the traditional“pure load”to the generalized load with the dual characteristics of“load+power su...In a“low-carbon”context,the power load is affected by the coupling of multiple factors,which gradually evolves from the traditional“pure load”to the generalized load with the dual characteristics of“load+power supply.”Traditional time-series forecasting methods are no longer suitable owing to the complexity and uncertainty associated with generalized loads.From the perspective of image processing,this study proposes a graphical short-term prediction method for generalized loads based on modal decomposition.First,the datasets are normalized and feature-filtered by comparing the results of Xtreme gradient boosting,gradient boosted decision tree,and random forest algorithms.Subsequently,the generalized load data are decomposed into three sets of modalities by modal decomposition,and red,green,and blue(RGB)images are generated using them as the pixel values of the R,G,and B channels.The generated images are diversified,and an optimized DenseNet neural network was used for training and prediction.Finally,the base load,wind power,and photovoltaic power generation data are selected,and the characteristic curves of the generalized load scenarios under different permeabilities of wind power and photovoltaic power generation are obtained using the density-based spatial clustering of applications with noise algorithm.Based on the proposed graphical forecasting method,the feasibility of the generalized load graphical forecasting method is verified by comparing it with the traditional time-series forecasting method.展开更多
Organic contaminants have posed a direct and substantial risk to human wellness and the environment.In recent years,piezo-electric catalysis has evolved as a novel and effective method for decomposing these contaminan...Organic contaminants have posed a direct and substantial risk to human wellness and the environment.In recent years,piezo-electric catalysis has evolved as a novel and effective method for decomposing these contaminants.Although piezoelectric materials offer a wide range of options,most related studies thus far have focused on inorganic materials and have paid little attention to organic materi-als.Organic materials have advantages,such as being lightweight,inexpensive,and easy to process,over inorganic materials.Therefore,this paper provides a comprehensive review of the progress made in the research on piezoelectric catalysis using organic materials,high-lighting their catalytic efficiency in addressing various pollutants.In addition,the applications of organic materials in piezoelectric cata-lysis for water decomposition to produce hydrogen,disinfect bacteria,treat tumors,and reduce carbon dioxide are presented.Finally,fu-ture developmental trends regarding the piezoelectric catalytic potential of organic materials are explored.展开更多
As an important part of rotating machinery,gearboxes often fail due to their complex working conditions and harsh working environment.Therefore,it is very necessary to effectively extract the fault features of the gea...As an important part of rotating machinery,gearboxes often fail due to their complex working conditions and harsh working environment.Therefore,it is very necessary to effectively extract the fault features of the gearboxes.Gearbox fault signals usually contain multiple characteristic components and are accompanied by strong noise interference.Traditional sparse modeling methods are based on synthesis models,and there are few studies on analysis and balance models.In this paper,a balance nonconvex regularized sparse decomposition method is proposed,which based on a balance model and an arctangent nonconvex penalty function.The sparse dictionary is constructed by using Tunable Q-Factor Wavelet Transform(TQWT)that satisfies the tight frame condition,which can achieve efficient and fast solution.It is optimized and solved by alternating direction method of multipliers(ADMM)algorithm,and the non-convex regularized sparse decomposition algorithm of synthetic and analytical models are given.Through simulation experiments,the determination methods of regularization parameters and balance parameters are given,and compared with the L1 norm regularization sparse decomposition method under the three models.Simulation analysis and engineering experimental signal analysis verify the effectiveness and superiority of the proposed method.展开更多
Dynamic mode decomposition(DMD) aims at extracting intrinsic mechanisms in a time sequence via linear recurrence relation of its observables, thereby predicting later terms in the sequence. Stability is a major concer...Dynamic mode decomposition(DMD) aims at extracting intrinsic mechanisms in a time sequence via linear recurrence relation of its observables, thereby predicting later terms in the sequence. Stability is a major concern in DMD predictions. We adopt a regularized form and propose a Regularized DMD(Re DMD) algorithm to determine the regularization parameter. This leverages stability and accuracy. Numerical tests for Burgers' equation demonstrate that Re DMD effectively stabilizes the DMD prediction while maintaining accuracy. Comparisons are made with the truncated DMD algorithm.展开更多
La_(0.8)A_(0.2)NiO_(3) (A=K,Ba,Y) catalysts supported on the microwave-absorbing ceramic heating carrier were prepared by the sol-gel method.The crystalline phase and the catalytic activity of the La_(0.8)A_(0.2)NiO_(...La_(0.8)A_(0.2)NiO_(3) (A=K,Ba,Y) catalysts supported on the microwave-absorbing ceramic heating carrier were prepared by the sol-gel method.The crystalline phase and the catalytic activity of the La_(0.8)A_(0.2)NiO_(3)catalysts were characterized by XRD and H_(2) temperature-programmed reduction (TPR).The effects of reaction temperature,oxygen concentration,and gas flow rate on the direct decomposition of nitric oxide over the synthesized catalysts were studied under microwave irradiation (2.45 GHz).The XRD results indicated that the La_(0.8)A_(0.2)NiO_(3) catalysts formed an ABO_(3) perovskite structure,and the H_(2)-TPR results revealed that the relative reducibility of the catalysts increased in the order of La_(0.8)K_(0.2)NiO_(3)>La_(0.8)Ba_(0.2)NiO_(3)>La_(0.8)Y_(0.2)Ni O_(3).Under microwave irradiation,the highest NO conversion amounted to 98.9%,which was obtained with the La_(0.8)K_(0.2)NiO_(3) catalyst at 400℃.The oxygen concentration did not inhibit the NO decomposition on the La_(0.8)A_(0.2)NiO_(3) catalysts,thus the N_(2) selectivity exceeded 99.8%under excess oxygen at 550℃.The NOconversion of the La_(0.8)A_(0.2)NiO_(3) catalysts decreased linearly with the increase in the gas flow rate.展开更多
Real and complex Schur forms have been receiving increasing attention from the fluid mechanics community recently,especially related to vortices and turbulence.Several decompositions of the velocity gradient tensor,su...Real and complex Schur forms have been receiving increasing attention from the fluid mechanics community recently,especially related to vortices and turbulence.Several decompositions of the velocity gradient tensor,such as the triple decomposition of motion(TDM)and normal-nilpotent decomposition(NND),have been proposed to analyze the local motions of fluid elements.However,due to the existence of different types and non-uniqueness of Schur forms,as well as various possible definitions of NNDs,confusion has spread widely and is harming the research.This work aims to clean up this confusion.To this end,the complex and real Schur forms are derived constructively from the very basics,with special consideration for their non-uniqueness.Conditions of uniqueness are proposed.After a general discussion of normality and nilpotency,a complex NND and several real NNDs as well as normal-nonnormal decompositions are constructed,with a brief comparison of complex and real decompositions.Based on that,several confusing points are clarified,such as the distinction between NND and TDM,and the intrinsic gap between complex and real NNDs.Besides,the author proposes to extend the real block Schur form and its corresponding NNDs for the complex eigenvalue case to the real eigenvalue case.But their justification is left to further investigations.展开更多
Fe/N-based biomass porous carbon composite(Fe/N-p Carbon) was prepared by a facile high-temperature carbonization method from biomass,and the effect of Fe/N-p Carbon on the thermal decomposition of energetic molecular...Fe/N-based biomass porous carbon composite(Fe/N-p Carbon) was prepared by a facile high-temperature carbonization method from biomass,and the effect of Fe/N-p Carbon on the thermal decomposition of energetic molecular perovskite-based material DAP-4 was studied.Biomass porous carbonaceous materials was considered as the micro/nano support layers for in situ deposition of Fe/N precursors.Fe/Np Carbon was prepared simply by the high-temperature carbonization method.It was found that it showed the inherent catalysis properties for thermal decomposition of DAP-4.The heat release of DAP-4/Fe/N-p Carbon by DSC curves tested had increased slightly,compared from DAP-4/Fe/N-p Carbon-0.The decomposition temperature peak of DAP-4 at the presence of Fe/N-p Carbon had reduced by 79°C from384.4°C(pure DAP-4) to 305.4°C(DAP-4/Fe/N-p Carbon-3).The apparent activation energy of DAP-4thermal decomposition also had decreased by 29.1 J/mol.The possible catalytic decomposition mechanism of DAP-4 with Fe/N-p Carbon was proposed.展开更多
基金supported in part by the Interdisciplinary Project of Dalian University(DLUXK-2023-ZD-001).
文摘Multivariate time series forecasting iswidely used in traffic planning,weather forecasting,and energy consumption.Series decomposition algorithms can help models better understand the underlying patterns of the original series to improve the forecasting accuracy of multivariate time series.However,the decomposition kernel of previous decomposition-based models is fixed,and these models have not considered the differences in frequency fluctuations between components.These problems make it difficult to analyze the intricate temporal variations of real-world time series.In this paper,we propose a series decomposition-based Mamba model,DecMamba,to obtain the intricate temporal dependencies and the dependencies among different variables of multivariate time series.A variable-level adaptive kernel combination search module is designed to interact with information on different trends and periods between variables.Two backbone structures are proposed to emphasize the differences in frequency fluctuations of seasonal and trend components.Mamba with superior performance is used instead of a Transformer in backbone structures to capture the dependencies among different variables.A new embedding block is designed to capture the temporal features better,especially for the high-frequency seasonal component whose semantic information is difficult to acquire.A gating mechanism is introduced to the decoder in the seasonal backbone to improve the prediction accuracy.A comparison with ten state-of-the-art models on seven real-world datasets demonstrates that DecMamba can better model the temporal dependencies and the dependencies among different variables,guaranteeing better prediction performance for multivariate time series.
基金supported by National Natural Science Foundations of China(nos.12271326,62102304,61806120,61502290,61672334,61673251)China Postdoctoral Science Foundation(no.2015M582606)+2 种基金Industrial Research Project of Science and Technology in Shaanxi Province(nos.2015GY016,2017JQ6063)Fundamental Research Fund for the Central Universities(no.GK202003071)Natural Science Basic Research Plan in Shaanxi Province of China(no.2022JM-354).
文摘The multi-objective particle swarm optimization algorithm(MOPSO)is widely used to solve multi-objective optimization problems.In the article,amulti-objective particle swarm optimization algorithmbased on decomposition and multi-selection strategy is proposed to improve the search efficiency.First,two update strategies based on decomposition are used to update the evolving population and external archive,respectively.Second,a multiselection strategy is designed.The first strategy is for the subspace without a non-dominated solution.Among the neighbor particles,the particle with the smallest penalty-based boundary intersection value is selected as the global optimal solution and the particle far away fromthe search particle and the global optimal solution is selected as the personal optimal solution to enhance global search.The second strategy is for the subspace with a non-dominated solution.In the neighbor particles,two particles are randomly selected,one as the global optimal solution and the other as the personal optimal solution,to enhance local search.The third strategy is for Pareto optimal front(PF)discontinuity,which is identified by the cumulative number of iterations of the subspace without non-dominated solutions.In the subsequent iteration,a new probability distribution is used to select from the remaining subspaces to search.Third,an adaptive inertia weight update strategy based on the dominated degree is designed to further improve the search efficiency.Finally,the proposed algorithmis compared with fivemulti-objective particle swarm optimization algorithms and five multi-objective evolutionary algorithms on 22 test problems.The results show that the proposed algorithm has better performance.
文摘We presented the preparation and analysis of La_(1-x)K_(x)CoO_(3)(x=0.1-0.4)catalysts,supported on microwave-absorbing ceramic carriers,using the sol-gel method.We systematically investigated the effects of various reaction conditions under microwave irradiation(0-50 W).These conditions included reaction temperatures(300-600℃),oxygen concentrations(0-6%),and varying K^(+)doping levels on the catalysts'activity.The crystalline phase,microstructure,and the catalytic activity of the catalyst were analyzed by XRD,TEM,H_2-TPR,and O_(2)-TPD.The experimental results reveal that La_(1-x)K_(x)CoO_(3)(x=0.1-0.4)catalysts consistently form homogeneous perovskite nanoparticles across different doping levels.The NO decomposition efficiency on these catalysts initially increases and then decreases with variations in doping amount,temperature,and microwave power.Additionally,an increase in oxygen concentration positively influences NO conversion rates.The optimal performance is observed with La_(0.7)K_(0.3)CoO_(3)catalyst under conditions of x=0.3,400℃,10 W microwave power,and 4%oxygen concentration,achieving a peak NO conversion rate of La_(0.7)K_(0.3)CoO_(3)catalyst is 93.1%.
基金supported by the National Natural Science Foundation of China(Grant No.52206165)。
文摘Flammable ionic liquids exhibit high conductivity and a broad electrochemical window,enabling the generation of combustible gases for combustion via electrochemical decomposition and thermal decomposition.This characteristic holds significant implications in the realm of novel satellite propulsion.Introducing a fraction of the electrical energy into energetic ionic liquid fuels,the thermal decomposition process is facilitated by reducing the apparent activation energy required,and electrical energy can trigger the electrochemical decomposition of ionic liquids,presenting a promising approach to enhance combustion efficiency and energy release.This study applied an external voltage during the thermal decomposition of 1-ethyl-3-methylimidazole nitrate([EMIm]NO_(3)),revealing the effective alteration of the activation energy of[EMIm]NO_(3).The pyrolysis,electrochemical decomposition,and electron assisted enhancement products were identified through Thermogravimetry-Differential scanning calorimetry-Fourier transform infrared-Mass spectrometry(TG-DSC-FTIR-MS)and gas chromatography(GC)analyses,elucidating the degradation mechanism of[EMIm]NO_(3).Furthermore,an external voltage was introduced during the combustion of[EMIm]NO_(3),demonstrating the impact of voltage on the combustion process.
基金supported by the National Natural Science Foundation of China under Grants No.41771401 and No.42350710201.
文摘A P-band polarimetric synthetic aperture radar(PolSAR)sensor has deep penetration ability into and through the vegetation canopies in forested environments.Thus,the sensor is of great potential to accurately assess forest parameters such as coverage,stand density,and tree height.Unfortunately,the radar backscatter from complex terrain can adversely impact the backscatter from trees or forests,and forest parameters assessed can be erroneous.Thus,reducing the topographic impact is an urgent must.In this study,a topographic compensation algorithm has been studied.To assess the algorithm’s validity and effectiveness,we applied it to P-band PolSAR datasets in four forested areas in the US.Trees in the forest stands have diverse species,and the topographic conditions of the terrain differ.Significant topographic impact on the P-band PolSAR data exists before the topographic compensation algorithm.After the algorithm,the impact decreases noticeably qualitatively and quantitatively.The algorithm is valid and effective in reducing the topographic influence on the PolSAR data and,consequently,provides a better chance of retrieving accurate forest parameters.
基金The authors gratefully acknowledge financial support from the National Natural Science Foundation of China(52103090)the Natural Science Foundation of Guangdong Province(2022A1515011780)Autonomous deployment project of China National Key Laboratory of Materials for Integrated Circuits(NKLJC-Z2023-B03).
文摘The remarkable properties of carbon nanotubes(CNTs)have led to promising applications in the field of electromagnetic inter-ference(EMI)shielding.However,for macroscopic CNT assemblies,such as CNT film,achieving high electrical and mechanical properties remains challenging,which heavily depends on the tube-tube interac-tions of CNTs.Herein,we develop a novel strategy based on metal-organic decomposition(MOD)to fabricate a flexible silver-carbon nanotube(Ag-CNT)film.The Ag particles are introduced in situ into the CNT film through annealing of MOD,leading to enhanced tube-tube interactions.As a result,the electrical conductivity of Ag-CNT film is up to 6.82×10^(5) S m^(-1),and the EMI shielding effectiveness of Ag-CNT film with a thickness of~7.8μm exceeds 66 dB in the ultra-broad frequency range(3-40 GHz).The tensile strength and Young’s modulus of Ag-CNT film increase from 30.09±3.14 to 76.06±6.20 MPa(~253%)and from 1.12±0.33 to 8.90±0.97 GPa(~795%),respectively.Moreover,the Ag-CNT film exhibits excellent near-field shield-ing performance,which can effectively block wireless transmission.This innovative approach provides an effective route to further apply macroscopic CNT assemblies to future portable and wearable electronic devices.
基金financially funded by Natural Science Basic Research Program of Shaanxi(grant number 2022JM-239)Key Research and Development Project of Shaanxi Provincial(grant number 2021LLRH-05–08)。
文摘To study the formation and transformation mechanism of long-period stacked ordered(LPSO)structures,a systematic atomic scale analysis was conducted for the structural evolution of long-period stacked ordered(LPSO)structures in the Mg-Gd-Y-Zn-Zr alloy annealed at 300℃~500℃.Various types of metastable LPSO building block clusters were found to exist in alloy structures at different temperatures,which precipitate during the solidification and homogenization process.The stability of Zn/Y clusters is explained by the first principles of density functional theory.The LPSO structure is distinguished by the arrangement of its different Zn/Y enriched LPSO structural units,which comprises local fcc stacking sequences upon a tightly packed plane.The presence of solute atoms causes local lattice distortion,thereby enabling the rearrangement of Mg atoms in the different configurations in the local lattice,and local HCP-FCC transitions occur between Mg and Zn atoms occupying the nearest neighbor positions.This finding indicates that LPSO structures can generate necessary Schockley partial dislocations on specific slip surfaces,providing direct evidence of the transition from 18R to 14H.Growth of the LPSO,devoid of any defects and non-coherent interfaces,was observed separately from other precipitated phases.As a result,the precipitation sequence of LPSO in the solidification stage was as follows:Zn/Ycluster+Mg layers→various metastable LPSO building block clusters→18R/24R LPSO;whereas the precipitation sequence of LPSO during homogenization treatment was observed to be as follows:18R LPSO→various metastable LPSO building block clusters→14H LPSO.Of these,14H LPSO was found to be the most thermodynamically stable structure.
基金funded by the National Natural Science Foundation of China(Grant No.21975024)。
文摘2,6-bis(picrylamino)-3,5-dinitropyridine(PYX)has excellent thermostability,which makes its thermal decomposition mechanism receive much attention.In this paper,the mechanism of PYX thermal decomposition was investigated thoroughly by the ReaxFF-lg force field combined with DFT-B3LYP(6-311++G)method.The detailed decomposition mechanism,small-molecule product evolution,and cluster evolution of PYX were mainly analyzed.In the initial stage of decomposition,the intramolecular hydrogen transfer reaction and the formation of dimerized clusters are earlier than the denitration reaction.With the progress of the reaction,one side of the bitter amino group is removed from the pyridine ring,and then the pyridine ring is cleaved.The final products produced in the thermal decomposition process are CO_(2),H_(2)O,N_(2),and H_(2).Among them,H_(2)O has the earliest generation time,and the reaction rate constant(k_(3))is the largest.Many clusters are formed during the decomposition of PYX,and the formation,aggregation,and decomposition of these clusters are strongly affected by temperature.At low temperatures(2500 K-2750 K),many clusters are formed.At high temperatures(2750 K-3250 K),the clusters aggregate to form larger clusters.At 3500 K,the large clusters decompose and become small.In the late stage of the reaction,H and N in the clusters escaped almost entirely,but more O was trapped in the clusters,which affected the auto-oxidation process of PYX.PYX's initial decomposition activation energy(E_(a))was calculated to be 126.58 kJ/mol.This work contributes to a theoretical understanding of PYX's entire thermal decomposition process.
基金financially supported by the National Natural Science Foundation of China(Grant Nos.51109158,U2106223)the Science and Technology Development Plan Program of Tianjin Municipal Transportation Commission(Grant No.2022-48)。
文摘When investigating the vortex-induced vibration(VIV)of marine risers,extrapolating the dynamic response on the entire length based on limited sensor measurements is a crucial step in both laboratory experiments and fatigue monitoring of real risers.The problem is conventionally solved using the modal decomposition method,based on the principle that the response can be approximated by a weighted sum of limited vibration modes.However,the method is not valid when the problem is underdetermined,i.e.,the number of unknown mode weights is more than the number of known measurements.This study proposed a sparse modal decomposition method based on the compressed sensing theory and the Compressive Sampling Matching Pursuit(Co Sa MP)algorithm,exploiting the sparsity of VIV in the modal space.In the validation study based on high-order VIV experiment data,the proposed method successfully reconstructed the response using only seven acceleration measurements when the conventional methods failed.A primary advantage of the proposed method is that it offers a completely data-driven approach for the underdetermined VIV reconstruction problem,which is more favorable than existing model-dependent solutions for many practical applications such as riser structural health monitoring.
基金Supported by the National Natural Science Foundation of China(62376214)the Natural Science Basic Research Program of Shaanxi(2023-JC-YB-533)Foundation of Ministry of Education Key Lab.of Cognitive Radio and Information Processing(Guilin University of Electronic Technology)(CRKL200203)。
文摘A modified multiple-component scattering power decomposition for analyzing polarimetric synthetic aperture radar(PolSAR)data is proposed.The modified decomposition involves two distinct steps.Firstly,ei⁃genvectors of the coherency matrix are used to modify the scattering models.Secondly,the entropy and anisotro⁃py of targets are used to improve the volume scattering power.With the guarantee of high double-bounce scatter⁃ing power in the urban areas,the proposed algorithm effectively improves the volume scattering power of vegeta⁃tion areas.The efficacy of the modified multiple-component scattering power decomposition is validated using ac⁃tual AIRSAR PolSAR data.The scattering power obtained through decomposing the original coherency matrix and the coherency matrix after orientation angle compensation is compared with three algorithms.Results from the experiment demonstrate that the proposed decomposition yields more effective scattering power for different PolSAR data sets.
基金Saudi Aramco for their fundingsupported by the Supercomputing Laboratory at King Abdullah University of Science&Technology (KAUST) in Thuwal,Saudi Arabiaused Expanse cluster at San Diego Supercomputer Center through allocation TG-CHE170060 from the Advanced Cyberinfrastructure Coordination Ecosystem:Services&Support (ACCESS) program,which is supported by National Science Foundation grants#2138259,#2138286,#2138307,#2137603, and#2138296。
文摘Ammonia decomposition is a key reaction in the context of hydrogen storage, transport, and release. This study combines density functional theory(DFT) calculations with microkinetic modeling to address the promotion mechanism of Ba species for ammonia decomposition on Co catalysts. The modified adsorption properties of Co upon the addition of metallic Ba or BaO suggest that the promoters play a role in alleviating the competitive adsorption of H. Calculating the full reaction pathway of ammonia decomposition shows that limiting the investigation to the N–N association step, as done previously, overlooks the effect of the promoter on the energy barriers of the NHxdehydrogenation steps. Challenges of modeling the ammonia decomposition reaction are addressed by understanding that the NH_(2) intermediate is stabilized on the step sites rather than the terrace sites. When the effect of H-coverage on the adsorption of NH_(3) is not considered in the microkinetic simulations, the results conflict with the experiments.However, accounting for the effect of H-coverage, as performed here, shows that BaO-doped Co has higher rates than pristine Co and Ba-doped Co at the reaction temperature of 723.15 K. When H is adsorbed on the Ba-doped Co, the adsorption of ammonia becomes significantly endergonic, which makes the rates relatively slow. The superiority of the BaO-promoted catalyst is attributed to a lower energy for the transition state of the rate-determining step, coupled with a reduced impact of the hydrogen coverage on weakening the ammonia adsorption. The kinetic analysis of the influence of Ba and BaO on the Co surface shows that BaO-doped Co aligns more closely with experimental observations than Badoped Co. This implies that Ba on the Co surface is likely to be in an oxide form under reaction conditions.Understanding the kinetics of the ammonia decomposition reaction provides a foundation for developing highly effective catalysts to accelerate the industrial utilization of ammonia as a sustainable hydrogen carrier.
基金Financial support received from the National Natural Science Foundation of China(22178379)the National Key Research and Development Program of China(2021YFC2800902)is gratefully acknowledged.
文摘Natural gas hydrate is an energy resource for methane that has a carbon quantity twice more than all traditional fossil fuels combined.However,their practical application in the field has been limited due to the challenges of long-term preparation,high costs and associated risks.Experimental studies,on the other hand,offer a safe and cost-effective means of exploring the mechanisms of hydrate dissociation and optimizing exploitation conditions.Gas hydrate decomposition is a complicated process along with intrinsic kinetics,mass transfer and heat transfer,which are the influencing factors for hydrate decomposition rate.The identification of the rate-limiting factor for hydrate dissociation during depressurization varies with the scale of the reservoir,making it challenging to extrapolate findings from laboratory experiments to the actual exploitation.This review aims to summarize current knowledge of investigations on hydrate decomposition on the subject of the research scale(core scale,middle scale,large scale and field tests)and to analyze determining factors for decomposition rate,considering the various research scales and their associated influencing factors.
基金supported in part by the National Natural Science Foundation of China (62376288,U23A20347)the Engineering and Physical Sciences Research Council of UK (EP/X041239/1)the Royal Society International Exchanges Scheme of UK (IEC/NSFC/211404)。
文摘Decomposition of a complex multi-objective optimisation problem(MOP)to multiple simple subMOPs,known as M2M for short,is an effective approach to multi-objective optimisation.However,M2M facilitates little communication/collaboration between subMOPs,which limits its use in complex optimisation scenarios.This paper extends the M2M framework to develop a unified algorithm for both multi-objective and manyobjective optimisation.Through bilevel decomposition,an MOP is divided into multiple subMOPs at upper level,each of which is further divided into a number of single-objective subproblems at lower level.Neighbouring subMOPs are allowed to share some subproblems so that the knowledge gained from solving one subMOP can be transferred to another,and eventually to all the subMOPs.The bilevel decomposition is readily combined with some new mating selection and population update strategies,leading to a high-performance algorithm that competes effectively against a number of state-of-the-arts studied in this paper for both multiand many-objective optimisation.Parameter analysis and component analysis have been also carried out to further justify the proposed algorithm.
基金supported by the National Natural Science Foundation of China(Grant No.62063016).
文摘In a“low-carbon”context,the power load is affected by the coupling of multiple factors,which gradually evolves from the traditional“pure load”to the generalized load with the dual characteristics of“load+power supply.”Traditional time-series forecasting methods are no longer suitable owing to the complexity and uncertainty associated with generalized loads.From the perspective of image processing,this study proposes a graphical short-term prediction method for generalized loads based on modal decomposition.First,the datasets are normalized and feature-filtered by comparing the results of Xtreme gradient boosting,gradient boosted decision tree,and random forest algorithms.Subsequently,the generalized load data are decomposed into three sets of modalities by modal decomposition,and red,green,and blue(RGB)images are generated using them as the pixel values of the R,G,and B channels.The generated images are diversified,and an optimized DenseNet neural network was used for training and prediction.Finally,the base load,wind power,and photovoltaic power generation data are selected,and the characteristic curves of the generalized load scenarios under different permeabilities of wind power and photovoltaic power generation are obtained using the density-based spatial clustering of applications with noise algorithm.Based on the proposed graphical forecasting method,the feasibility of the generalized load graphical forecasting method is verified by comparing it with the traditional time-series forecasting method.
基金the National Natural Science Foundation of China(No.22179108)the Key Research and Development Projects of Shaanxi Province,China(No.2020GXLH-Z-032)+2 种基金the Doctoral Re-search Start-up Fund project of Xi’an Polytechnic University(No.107020589)the Shaanxi Provincial High-Level Talents Introduction Project(Youth Talent Fund)the Performance subsidy fund for Key Laboratory of Dielectric and Electrolyte Functional Material Hebei Province,China(No.22567627H).
文摘Organic contaminants have posed a direct and substantial risk to human wellness and the environment.In recent years,piezo-electric catalysis has evolved as a novel and effective method for decomposing these contaminants.Although piezoelectric materials offer a wide range of options,most related studies thus far have focused on inorganic materials and have paid little attention to organic materi-als.Organic materials have advantages,such as being lightweight,inexpensive,and easy to process,over inorganic materials.Therefore,this paper provides a comprehensive review of the progress made in the research on piezoelectric catalysis using organic materials,high-lighting their catalytic efficiency in addressing various pollutants.In addition,the applications of organic materials in piezoelectric cata-lysis for water decomposition to produce hydrogen,disinfect bacteria,treat tumors,and reduce carbon dioxide are presented.Finally,fu-ture developmental trends regarding the piezoelectric catalytic potential of organic materials are explored.
基金Supported by National Natural Science Foundation of China(Grant Nos.52075353,52007128).
文摘As an important part of rotating machinery,gearboxes often fail due to their complex working conditions and harsh working environment.Therefore,it is very necessary to effectively extract the fault features of the gearboxes.Gearbox fault signals usually contain multiple characteristic components and are accompanied by strong noise interference.Traditional sparse modeling methods are based on synthesis models,and there are few studies on analysis and balance models.In this paper,a balance nonconvex regularized sparse decomposition method is proposed,which based on a balance model and an arctangent nonconvex penalty function.The sparse dictionary is constructed by using Tunable Q-Factor Wavelet Transform(TQWT)that satisfies the tight frame condition,which can achieve efficient and fast solution.It is optimized and solved by alternating direction method of multipliers(ADMM)algorithm,and the non-convex regularized sparse decomposition algorithm of synthetic and analytical models are given.Through simulation experiments,the determination methods of regularization parameters and balance parameters are given,and compared with the L1 norm regularization sparse decomposition method under the three models.Simulation analysis and engineering experimental signal analysis verify the effectiveness and superiority of the proposed method.
基金supported by the National Nature Science Foundation of China (Grant No.11988102)National Undergraduate Training Program for Innovation and Entrepreneurship。
文摘Dynamic mode decomposition(DMD) aims at extracting intrinsic mechanisms in a time sequence via linear recurrence relation of its observables, thereby predicting later terms in the sequence. Stability is a major concern in DMD predictions. We adopt a regularized form and propose a Regularized DMD(Re DMD) algorithm to determine the regularization parameter. This leverages stability and accuracy. Numerical tests for Burgers' equation demonstrate that Re DMD effectively stabilizes the DMD prediction while maintaining accuracy. Comparisons are made with the truncated DMD algorithm.
文摘La_(0.8)A_(0.2)NiO_(3) (A=K,Ba,Y) catalysts supported on the microwave-absorbing ceramic heating carrier were prepared by the sol-gel method.The crystalline phase and the catalytic activity of the La_(0.8)A_(0.2)NiO_(3)catalysts were characterized by XRD and H_(2) temperature-programmed reduction (TPR).The effects of reaction temperature,oxygen concentration,and gas flow rate on the direct decomposition of nitric oxide over the synthesized catalysts were studied under microwave irradiation (2.45 GHz).The XRD results indicated that the La_(0.8)A_(0.2)NiO_(3) catalysts formed an ABO_(3) perovskite structure,and the H_(2)-TPR results revealed that the relative reducibility of the catalysts increased in the order of La_(0.8)K_(0.2)NiO_(3)>La_(0.8)Ba_(0.2)NiO_(3)>La_(0.8)Y_(0.2)Ni O_(3).Under microwave irradiation,the highest NO conversion amounted to 98.9%,which was obtained with the La_(0.8)K_(0.2)NiO_(3) catalyst at 400℃.The oxygen concentration did not inhibit the NO decomposition on the La_(0.8)A_(0.2)NiO_(3) catalysts,thus the N_(2) selectivity exceeded 99.8%under excess oxygen at 550℃.The NOconversion of the La_(0.8)A_(0.2)NiO_(3) catalysts decreased linearly with the increase in the gas flow rate.
文摘Real and complex Schur forms have been receiving increasing attention from the fluid mechanics community recently,especially related to vortices and turbulence.Several decompositions of the velocity gradient tensor,such as the triple decomposition of motion(TDM)and normal-nilpotent decomposition(NND),have been proposed to analyze the local motions of fluid elements.However,due to the existence of different types and non-uniqueness of Schur forms,as well as various possible definitions of NNDs,confusion has spread widely and is harming the research.This work aims to clean up this confusion.To this end,the complex and real Schur forms are derived constructively from the very basics,with special consideration for their non-uniqueness.Conditions of uniqueness are proposed.After a general discussion of normality and nilpotency,a complex NND and several real NNDs as well as normal-nonnormal decompositions are constructed,with a brief comparison of complex and real decompositions.Based on that,several confusing points are clarified,such as the distinction between NND and TDM,and the intrinsic gap between complex and real NNDs.Besides,the author proposes to extend the real block Schur form and its corresponding NNDs for the complex eigenvalue case to the real eigenvalue case.But their justification is left to further investigations.
基金National Natural Science Foundation of China(Grant No.21975227)the Found of National defence Science and Technology Key Laboratory (Grant No.6142602210306)。
文摘Fe/N-based biomass porous carbon composite(Fe/N-p Carbon) was prepared by a facile high-temperature carbonization method from biomass,and the effect of Fe/N-p Carbon on the thermal decomposition of energetic molecular perovskite-based material DAP-4 was studied.Biomass porous carbonaceous materials was considered as the micro/nano support layers for in situ deposition of Fe/N precursors.Fe/Np Carbon was prepared simply by the high-temperature carbonization method.It was found that it showed the inherent catalysis properties for thermal decomposition of DAP-4.The heat release of DAP-4/Fe/N-p Carbon by DSC curves tested had increased slightly,compared from DAP-4/Fe/N-p Carbon-0.The decomposition temperature peak of DAP-4 at the presence of Fe/N-p Carbon had reduced by 79°C from384.4°C(pure DAP-4) to 305.4°C(DAP-4/Fe/N-p Carbon-3).The apparent activation energy of DAP-4thermal decomposition also had decreased by 29.1 J/mol.The possible catalytic decomposition mechanism of DAP-4 with Fe/N-p Carbon was proposed.
