Kinetic impact is the most practical planetary-defense technique,with momentum-transfer efficiency central to deflection design.We present a Monte Carlo photometric framework that couples ejecta sampling,dynamical evo...Kinetic impact is the most practical planetary-defense technique,with momentum-transfer efficiency central to deflection design.We present a Monte Carlo photometric framework that couples ejecta sampling,dynamical evolution,and image synthesis to compare directly with HST,LICIACube,ground-based and Lucy observations of the DART impact.Decomposing ejecta into(1)a highvelocity(~1600 m/s)plume exhibiting Na/K resonance,(2)a low-velocity(~1 m/s)conical component shaped by binary gravity and solar radiation pressure,and(3)meter-scale boulders,we quantify each component’s mass and momentum.Fitting photometric decay curves and morphological evolution yields size-velocity distributions and,via scaling laws,estimates of Dimorphos’bulk density,cratering parameters,and cohesive strength that agree with dynamical constraints.Photometric ejecta modeling therefore provides a robust route to constrain momentum enhancement and target properties,improving predictive capability for kinetic-deflection missions.展开更多
This study explores the thin-layer convective solar drying of Marrubium vulgare L.leaves under conditions typical of sun-rich semi-arid climates.Drying experiments were conducted at three inlet-air temperatures(40℃,5...This study explores the thin-layer convective solar drying of Marrubium vulgare L.leaves under conditions typical of sun-rich semi-arid climates.Drying experiments were conducted at three inlet-air temperatures(40℃,50℃,60℃)and two air velocities(1.5 and 2.5 m·s^(-1))using an indirect solar dryer with auxiliary temperature control.Moisture-ratio data were fitted with eight widely used thin-layer models and evaluated using correlation coefficient(r),root-mean-square error(RMSE),and Akaike information criterion(AIC).A complementary heattransfer analysis based on Reynolds and Prandtl numbers with appropriate Nusselt correlations was used to relate flow regime to drying performance,and an energy balance quantified the relative contributions of solar and auxiliary heat.The logarithmic model consistently achieved the lowest RMSE/AIC with r>0.99 across all conditions.Higher temperature and air velocity significantly reduced drying time during the decreasing-rate period,with no constantrate stage observed.On average,solar input supplied the large majority of the thermal demand,while the auxiliary heater compensated short irradiance drops to maintain setpoints.These findings provide a reproducible dataset and a modelling benchmark for M.vulgare leaves,and they support energy-aware design of hybrid solar dryers formedicinal plants in sun-rich regions.展开更多
The increasing production and release of synthetic organic chemicals,including pharmaceuticals,into our envi-ronment has allowed these substances to accumulate in our surface water systems.Current purification technol...The increasing production and release of synthetic organic chemicals,including pharmaceuticals,into our envi-ronment has allowed these substances to accumulate in our surface water systems.Current purification technolo-gies have been unable to eliminate these pollutants,resulting in their ongoing release into aquatic ecosystems.This study focuses on cloperastine(CPS),a cough suppressant and antihistamine medication.The environmental impact of CPS usage has become a concern,mainly due to its increased detection during the COVID-19 pandemic.CPS has been found in wastewater treatment facilities,effluents from senior living residences,river waters,and sewage sludge.However,the photosensitivity of CPS and its photodegradation profile remain largely unknown.This study investigates the photodegradation process of CPS under simulated tertiary treatment conditions using UV photolysis,a method commonly applied in some wastewater treatment plants.Several transformation prod-ucts were identified,evaluating their kinetic profiles using chemometric approaches(i.e.,curve fitting and the hard-soft multivariate curve resolution-alternating least squares(HS-MCR-ALS)algorithm)and calculating the reaction quantum yield.As a result,three different transformation products have been detected and correctly identified.In addition,a comprehensive description of the kinetic pathway involved in the photodegradation process of the CPS drug has been provided,including observed kinetic rate constants.展开更多
Under the backdrop of“Carbon Peak and Carbon Neutrality”(dual carbon)goal in China,the methane-carbon dioxide reforming reaction has attracted considerable attention due to its environmental benefits of converting t...Under the backdrop of“Carbon Peak and Carbon Neutrality”(dual carbon)goal in China,the methane-carbon dioxide reforming reaction has attracted considerable attention due to its environmental benefits of converting two greenhouse gases(methane and carbon dioxide)into syngas and its promising industrial applications.Nickel(Ni)-based catalysts,with high catalytic activity,low cost,and abundant resources,are considered ideal candidates for industrial applications.In this article,three reaction kinetic models were briefly introduced,namely the Power-Law(PL)model,the Eley-Rideal(ER)model,and the Langmuir-Hinshelwood-Hougen-Watson(LHHW)model.Based on the LHHW model,the reaction kinetics and mechanisms of different catalytic systems were systematically discussed,including the properties of supports,the doping of noble metals and transition metals,the role of promoters,and the influence of the geometric and electronic structures of Ni on the reaction mechanism.Furthermore,the kinetics of carbon deposition and elimination on various catalysts were analyzed.Based on the reaction rate expressions for carbon elimination,the reasons for the high activity of transition metal iron(Fe)-doped catalysts and core-shell structured catalysts in carbon elimination were explained.Based on the detailed collation and comparative analysis of the reaction mechanisms and kinetic characteristics across diverse Ni-based catalytic systems,a theoretical guidance for the designing of high-performance catalysts was provided in this work.展开更多
Hydrocarbon generation kinetics are influenced by complex factors,including temperature,reaction time,pressure,and molecular structure,which render simple modeling approaches inadequate for accurately simulating metha...Hydrocarbon generation kinetics are influenced by complex factors,including temperature,reaction time,pressure,and molecular structure,which render simple modeling approaches inadequate for accurately simulating methane generation.The closed-system pyrolysis experiment,a common method to study hydrocarbon generation,poses challenges for kinetic parameter regression due to limited data points.This limitation necessitates the application of sophisticated data analysis techniques to extract meaningful insights from sparse experimental data.This paper establishes a quantitative relationship between methane production and the thermal process through closed system pyrolysis experiments.A nonlinear regression model using multiple algorithms is established based on this quantitative relationship.Accordingly,a method that can quantitatively invert the methane generation kinetic parameters corresponding to the samples based on the experimental data is provided.Based on this theoretical model,a computer program capable of processing experimental data is designed and implemented.Practical analyses are performed using the method above for three samples:a coal sample from the Yulong,Guizhou;a solid bitumen sample from Guangyuan,Sichuan;and a marlstone sample containing type Ⅰ kerogen from Luquan,Yunnan.The results obtained agree with the qualitative estimates based on hydrocarbon generation kinetic theory using the previous method.Thus,the validity of the new data processing method,the new mathematical model,and the data processing procedures are verified.展开更多
1.Colors of chemical reaction engineering models Kinetic models of chemical reactions are a crucial asset for understanding and optimizing chemical processes[1].These models are critical for reactor design,process opt...1.Colors of chemical reaction engineering models Kinetic models of chemical reactions are a crucial asset for understanding and optimizing chemical processes[1].These models are critical for reactor design,process optimization,catalyst design,scale-up,and process control,making them indispensable in the chemical industry.Kinetic models predict the change in temperature and concentration of the relevant species,given an actual concentration and temperature.Reaction predictions are made by integrating the kinetic model with a reactor model,which accounts for external constraints,such as flow,inlet concentration。展开更多
Industrial ebullated-bed is an important device for promoting the cleaning and upgrading of oil products. The lumped kinetic model is a powerful tool for predicting the product yield of the ebullated-bed residue hydro...Industrial ebullated-bed is an important device for promoting the cleaning and upgrading of oil products. The lumped kinetic model is a powerful tool for predicting the product yield of the ebullated-bed residue hydrogenation (EBRH) unit, However, during the long-term operation of the device, there are phenomena such as low frequency of material property analysis leading to limited operating data and diverse operating modes at the same time scale, which poses a huge challenge to building an accurate product yield prediction model. To address these challenges, a data augmentation-based eleven lumped reaction kinetics mechanism model was constructed. This model combines generative adversarial networks, outlier elimination, and L2 norm data filtering to expand the dataset and utilizes kernel principal component analysis-fuzzy C-means for operating condition partitioning. Based on the hydrogenation reaction mechanism, a single and sub operating condition eleven lumped reaction kinetics model of an ebullated-bed residue hydrogenation unit, comprising 55 reaction paths and 110 parameters, was constructed before and after data augmentation. Compared to the single model before data enhancement, the average absolute error of the sub-models under data enhancement division was reduced by 23%. Thus, these findings can help guide the operation and optimization of the production process.展开更多
Hydrocracking is one of the most important petroleum refining processes that converts heavy oils into gases,naphtha,diesel,and other products through cracking reactions.Multi-objective optimization algorithms can help...Hydrocracking is one of the most important petroleum refining processes that converts heavy oils into gases,naphtha,diesel,and other products through cracking reactions.Multi-objective optimization algorithms can help refining enterprises determine the optimal operating parameters to maximize product quality while ensuring product yield,or to increase product yield while reducing energy consumption.This paper presents a multi-objective optimization scheme for hydrocracking based on an improved SPEA2-PE algorithm,which combines path evolution operator and adaptive step strategy to accelerate the convergence speed and improve the computational accuracy of the algorithm.The reactor model used in this article is simulated based on a twenty-five lumped kinetic model.Through model and test function verification,the proposed optimization scheme exhibits significant advantages in the multiobjective optimization process of hydrocracking.展开更多
We study the thermodynamic properties of the classical one-dimensional generalized nonlinear Klein-Gordon lattice model(n≥2)by using the cluster variation method with linear response theory.The results of this method...We study the thermodynamic properties of the classical one-dimensional generalized nonlinear Klein-Gordon lattice model(n≥2)by using the cluster variation method with linear response theory.The results of this method are exact in the thermodynamic limit.We present the single-site reduced densityρ^((1))(z),averages such as(z^(2)),<|z^(n)|>,and<(z_(1)-z_(2))^(2)>,the specific heat C_(v),and the static correlation functions.We analyze the scaling behavior of these quantities and obtain the exact scaling powers at the low and high temperatures.Using these results,we gauge the accuracy of the projective truncation approximation for theφ^(4)lattice model.展开更多
The continuous growth behavior of austenite grain in 20Cr peritectic steel was analyzed by experiment and theoretical modeling.The peculiar casting experiment with different cooling rates was achieved by multigradient...The continuous growth behavior of austenite grain in 20Cr peritectic steel was analyzed by experiment and theoretical modeling.The peculiar casting experiment with different cooling rates was achieved by multigradient operation scheme,and different morphologies in austenite grain were observed at the target location.The increase in austenite grain size with increasing cooling rate was firstly revealed in steels.The anomalous grain growth theoretically results from the mechanism of peritectic transformation transiting from the diffusional to massive type,and the additional energy storage stimulates the grain boundary migration.A new kinetic model to predict the growth behavior of austenite grain during continuous cooling process was developed,and the energy storage induced by massive type peritectic transformation was novelly taken into account.The parameters in the model were fitted by multiphase field modeling and experimental results.The kinetic model was finally verified by austenite grain size in laboratory test as well as the trial data at different locations in continuously cast bloom.The coarsening behavior of austenite grain during continuous casting was predicted based on the simulated temperature history.It is found that the grain coarsening occurs generally in the mold zone at high temperature for 20Cr steel and then almost levels off in the following process.The austenite finish transformation temperature Tγand primary cooling intensity show great influence on the grain coarsening.As Tγdecreases by 1℃,the austenite grain size decreases by 4μm linearly.However,the variation of Tγagainst heat flux is in a nonlinear relationship,suggesting that low cooling rate is much more harmful for austenite grain coarsening in continuous casting.展开更多
The cold-rolled quenching and partitioning(Q&P)steel with an initial microstructure of deformed ferrite and pearlite was studied.The microstructural evolution under various heating rates of 1.78,50,and 300℃/s was...The cold-rolled quenching and partitioning(Q&P)steel with an initial microstructure of deformed ferrite and pearlite was studied.The microstructural evolution under various heating rates of 1.78,50,and 300℃/s was investigated using microstructural characterization and theoretical modeling.At the same time,the characteristics of recrystallization and austenite formation kinetics were decoupled by examining recrystallized ferrite and deformed ferrite as initial conditions.The findings revealed that the austenite formation during continuous heating can be simplified into two stages:(i)the early nucleation-dominated formation stage and(ii)the later grain growth-dominated stage,resulting in the development of a modified two-stage model based on Johnson-Mehl-Avrami-Kolmogorov.Further experiments confirmed that when the austenite volume fraction exceeded approximately 5% at a heating rate of 1.78℃/s,ferrite recrystallization was suppressed.In consequence,a mixed model including recrystallization kinetics was employed to couple the austenite formation occurring in deformed ferrite and recrystallized ferrite,thereby describing the austenite formation kinetics affected by recrystallization.Precise predictions of non-isothermal austenite formation kinetics in cold-rolled Q&P steel were achieved during slow and ultrafast heating processes by integrating the suppression effect into the model for austenite formation.展开更多
Kinetic energy(KE) functional is crucial to speed up density functional theory calculation. However, deriving it accurately through traditional physics reasoning is challenging. We develop a generally applicable KE fu...Kinetic energy(KE) functional is crucial to speed up density functional theory calculation. However, deriving it accurately through traditional physics reasoning is challenging. We develop a generally applicable KE functional estimator for a one-dimensional (1D) extended system using a machine learning method. Our end-to-end solution combines the dimensionality reduction method with the Gaussian process regression, and simple scaling method to adapt to various 1D lattices. In addition to reaching chemical accuracy in KE calculation, our estimator also performs well on KE functional derivative prediction. Integrating this machine learning KE functional into the current orbital free density functional theory scheme is able to provide us with expected ground state electron density.展开更多
To investigate the growth conditions of white-rot fungus and simulate its metabolism kinetic models, the rules how the factors such as biomass, culture fluid, pH value, glucose consumption and exopolysaccharides gener...To investigate the growth conditions of white-rot fungus and simulate its metabolism kinetic models, the rules how the factors such as biomass, culture fluid, pH value, glucose consumption and exopolysaccharides generation, etc., changed during the batch culture process of white-rot fungi by using an air-lift fermenter, as well as metabolic kinetics of white-rot fungi were studied. Based on Logistic equation, Luedeking-Piret equation and experimental data, the correlation model parameters of mycelia biomass, glucose consumption and exopolysaccharide generation were obtained and found to be change with time in metabolism process. Detailedly, μm=0.071 8 h-1,α= 0.831 8 g/(g·h), β= 0.002 g/(g·h), b1=0.016 3 g/(g·h) and b2=3.023 3 g/(g·h). Hence the mycelial growth kinetic model, exopolysaccharide generation kinetic model and substrate consumption kinetic model which describe fermentation process of white-rot fungi were established. Meanwhile, the experimental data were verified by this model, and a good fitting result with an average relative error less than 10% between the data obtained from experiments and the model was yielded. The results show that these models can predict the growth and metabolic rules of white-rot fungus, the fermentation process of exopolysaccharides and the kinetic mechanism of white-rot fungus accurately.展开更多
Pyrolysis of benzene at 30 Torr was studied from 1360 K to 1820 K in this work. Synchrotron vacuum ultraviolet photoionization mass spectrometry was employed to detect the pyroly- sis products such as radicals, isomer...Pyrolysis of benzene at 30 Torr was studied from 1360 K to 1820 K in this work. Synchrotron vacuum ultraviolet photoionization mass spectrometry was employed to detect the pyroly- sis products such as radicals, isomers and polycyclic aromatic hydrocarbons, and measure their mole fraction profiles versus temperature. A low-pressure pyrolysis model of benzene was developed and validated by the experimental results. Rate of production analysis was performed to reveal the major reaction networks in both fuel decomposition and aromatic growth processes. It is concluded that benzene is mainly decomposed via H-abstraction reaction to produce phenyl and partly decomposed via unimolecular decomposition reac- tions to produce propargyl or phenyl. The decomposition process stops at the formation of acetylene and polyyne species like diacetylene and 1,3,5-hexatriyne due to their high thermal stabilities. Besides, the aromatic growth process in the low-pressure pyrolysis of benzene is concluded to initiate from benzene and phenyl, and is controlled by the even carbon growth mechanism due to the inhibited formation of C5 and C7 species which play important roles in the odd carbon growth mechanism.展开更多
In the present study, we studied the inhibitory effects of chelidonine and rutaecarpin on porcine pancreatic a-amylase （PPA） catalyzed hydrolysis using 2-chloro-4-nitrophenyl-4-O-β-D-galactopyranosylmaltoside （Gal...In the present study, we studied the inhibitory effects of chelidonine and rutaecarpin on porcine pancreatic a-amylase （PPA） catalyzed hydrolysis using 2-chloro-4-nitrophenyl-4-O-β-D-galactopyranosylmaltoside （Gal-G2-α-CNP）. We, for the first time, provided kinetic report and detailed inhibitory effects of both compounds on PPA. Lineweaver-Burk plot revealed that the inhibition was a mixed-noncompetitive type, and only one molecule of inhibitor bound to the enzyme or to the enzyme-substrate complex. Kinetic constants calculated from secondary plots were in millimole range. Dissociation constants of enzyme-inhibitor complex （KEI） were 0.9 mM and 3.5 mM, respectively. Moreover, dissociation constants of enzyme-inhibitor-substrate complex （KESI） were 0.04 mM and 0.31 mM, respectively. These data indicated that the inhibition was more inclined to competitive to Gal-G2-α-CNP hydrolysis. Further molecular docking study manifested that hydrogen bonding formed between acarbose and aspartic acid （Asp300）, histidine （His305） and glycine （Gly3-6）, while hydrogen bonding was observed between chelidonine and glutamic acid （Glu233）, lysine （Lys200） and His305. In addition, rutaecarpine had only one hydrogen bond with Lys200. Our data indicated that chelidonine and rutaecarpine were two promising drug candidates, and chelidonine possessed stronger inhibitory effect compared with rutaecarpine.展开更多
The utilization of iron coke provides a green pathway for low-carbon ironmaking.To uncover the influence mechanism of iron ore on the behavior and kinetics of iron coke gasification,the effect of iron ore on the micro...The utilization of iron coke provides a green pathway for low-carbon ironmaking.To uncover the influence mechanism of iron ore on the behavior and kinetics of iron coke gasification,the effect of iron ore on the microstructure of iron coke was investigated.Furthermore,a comparative study of the gasification reactions between iron coke and coke was conducted through non-isothermal thermogravimetric method.The findings indicate that compared to coke,iron coke exhibits an augmentation in micropores and specific surface area,and the micropores further extend and interconnect.This provides more adsorption sites for CO_(2) molecules during the gasification process,resulting in a reduction in the initial gasification temperature of iron coke.Accelerating the heating rate in non-isothermal gasification can enhance the reactivity of iron coke.The metallic iron reduced from iron ore is embedded in the carbon matrix,reducing the orderliness of the carbon structure,which is primarily responsible for the heightened reactivity of the carbon atoms.The kinetic study indicates that the random pore model can effectively represent the gasification process of iron coke due to its rich pore structure.Moreover,as the proportion of iron ore increases,the activation energy for the carbon gasification gradually decreases,from 246.2 kJ/mol for coke to 192.5 kJ/mol for iron coke 15wt%.展开更多
Lithium and cobalt recovery from spent lithium-ion batteries(LIBs) is a major focus because of their increased production and usage. The conventional method for recycling spent LIBs using inorganic acids produces harm...Lithium and cobalt recovery from spent lithium-ion batteries(LIBs) is a major focus because of their increased production and usage. The conventional method for recycling spent LIBs using inorganic acids produces harmful byproducts. In this work, the leaching agent was substituted with a less expensive and more environmentally friendly alternative—acetic acid—and a mathematical model was developed to describe the kinetics of the recovery process. The variables used were the pH value, temperature, H_2O_2 concentration, and the solid-to-liquid(S/L) ratio. The mathematical model used was the shrinking core model, which was modified to accommodate an equilibrium reaction. The experimental results show that the rate of recovery of Li and Co over time was only affected by temperature. The leaching behaviors of Li and Co were found to oppose each other. An increase in temperature resulted in increased recovery of Li but decreased recovery of Co because of the product-favoring endothermic reaction of Li and the reactant-favoring exothermic reaction of Co. The product of Li has a lower entropy value than the reactant as a free-moving ion, whereas the product of Co leaching has a higher entropy value as a stiff crystal complex. Thus, temperature conditioning is a pivotal factor in the leaching of spent LIBs.展开更多
During the multi-stage processing of advanced high-strength steels, the austenite-to-ferrite transformation, generally as a precursor of the formation of other non-equilibrium or metastable structures, has a severe ef...During the multi-stage processing of advanced high-strength steels, the austenite-to-ferrite transformation, generally as a precursor of the formation of other non-equilibrium or metastable structures, has a severe effect on the subsequent phase transformations. Herein, a more flexible kinetic and microstructural predictive modeling for the key austenite-to-ferrite transformation of Fe-C-Mn-Si steels was developed,in combination with the classical nucleation theory, the general mixed-mode growth model based on Gibbs energy balance, the microstructural path method and the kinetic framework for grain boundary nucleation. Adopting a bounded, extended matrix space corresponding to a single ferrite grain, both softimpingement and hard-impingement can be naturally included in the current modeling. Accordingly, this model outputs the ferrite volume fraction, the austenite/ferrite interface area per unit volume, and the average grain size of ferrite, which will serve as the input parameters for modeling the subsequent bainite or martensite transformations. Applying the model, this work successfully predicts the experiment measurement of the isothermal austenite-to-ferrite transformation in Fe-0.17 C-0.91 Mn-1.03 Si(wt%) steel at different temperatures and explains why the final-state average grain size of ferrite has a maximum at the moderate annealing temperature. Effectiveness and advantages of the present model are discussed arising from kinetics and thermodynamics accompanied with nucleation, growth and impingement.展开更多
The static recrystallization behavior of low-alloy steel Q345B during double-pass hot compression deformation tests was investigated in the temperature range of 900-1000 ℃,the true strain range of 0.15-0.25 and the i...The static recrystallization behavior of low-alloy steel Q345B during double-pass hot compression deformation tests was investigated in the temperature range of 900-1000 ℃,the true strain range of 0.15-0.25 and the interpass time range of 0.5-50 s on Gleeble-3500 thermo-simulation machine.The results show that static recrystallization during the interpass time is observed.As the deformation temperature and strain increase,softening caused by static recrystallization is obvious.According to the analysis and calculation of thermo-simulation data,the static recrystallization activation energy was obtained and static recrystallization kinetics model was built.Finally,the error analysis of static recrystallization kinetics model proved that the model had good accuracy.Therefore,this model provides a theoretical basis for static recrystallization（SRX）and will contribute to the development of multipass hot rolling process,in order to control the rolling process more accurately.展开更多
Adsorption is one of the most widely applied techniques for environmental remediation. Its kinetics are of great significance to evaluate the performance of a given adsorbent and gain insight into the underlying mecha...Adsorption is one of the most widely applied techniques for environmental remediation. Its kinetics are of great significance to evaluate the performance of a given adsorbent and gain insight into the underlying mechanisms. There are lots of references available concerning adsorption kinetics, and several mathematic models have been developed to describe adsorption reaction and diffusion processes. However, these models were frequently employed to fit the kinetic data in an unsuitable or improper manner. This is mainly because the boundary conditions of the associated models were, to a considerable extent, ignored for data modeling. Here we reviewed several widely-used adsorption kinetic models and paid more attention to their boundary conditions. We believe that the review is of certain significance and improvement for adsorption kinetic modeling.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.12272018)the National Key Basic Research Project(2022JCJQZD20600).
文摘Kinetic impact is the most practical planetary-defense technique,with momentum-transfer efficiency central to deflection design.We present a Monte Carlo photometric framework that couples ejecta sampling,dynamical evolution,and image synthesis to compare directly with HST,LICIACube,ground-based and Lucy observations of the DART impact.Decomposing ejecta into(1)a highvelocity(~1600 m/s)plume exhibiting Na/K resonance,(2)a low-velocity(~1 m/s)conical component shaped by binary gravity and solar radiation pressure,and(3)meter-scale boulders,we quantify each component’s mass and momentum.Fitting photometric decay curves and morphological evolution yields size-velocity distributions and,via scaling laws,estimates of Dimorphos’bulk density,cratering parameters,and cohesive strength that agree with dynamical constraints.Photometric ejecta modeling therefore provides a robust route to constrain momentum enhancement and target properties,improving predictive capability for kinetic-deflection missions.
文摘This study explores the thin-layer convective solar drying of Marrubium vulgare L.leaves under conditions typical of sun-rich semi-arid climates.Drying experiments were conducted at three inlet-air temperatures(40℃,50℃,60℃)and two air velocities(1.5 and 2.5 m·s^(-1))using an indirect solar dryer with auxiliary temperature control.Moisture-ratio data were fitted with eight widely used thin-layer models and evaluated using correlation coefficient(r),root-mean-square error(RMSE),and Akaike information criterion(AIC).A complementary heattransfer analysis based on Reynolds and Prandtl numbers with appropriate Nusselt correlations was used to relate flow regime to drying performance,and an energy balance quantified the relative contributions of solar and auxiliary heat.The logarithmic model consistently achieved the lowest RMSE/AIC with r>0.99 across all conditions.Higher temperature and air velocity significantly reduced drying time during the decreasing-rate period,with no constantrate stage observed.On average,solar input supplied the large majority of the thermal demand,while the auxiliary heater compensated short irradiance drops to maintain setpoints.These findings provide a reproducible dataset and a modelling benchmark for M.vulgare leaves,and they support energy-aware design of hybrid solar dryers formedicinal plants in sun-rich regions.
基金supported by the grants PID2020-113371RA-C22 and TED2021-130845A-C32,funded by MCIN/AEI/10.13039/501100011033.M.Marín-García,R.González-OlmosC.Gómez-Canela are members of the GESPA group(Grup d’Enginyeria i Simulacióde Processos Ambientals)at IQS-URL,which has been acknowledged as a Consolidated Research Group by the Government of Catalonia(No.2021-SGR-00321)+1 种基金In addition,M.Marín-García has been awarded a public grant for the Investigo Programme,aimed at hiring young job seekers to undertake research and innovation projects under the Recovery,Transformation,and Resilience Plan(PRTR),European Union Next Generation,for the year 2022,through the Government of Catalonia and the Spanish Ministry for Work and Social Economy(No.100045ID16)Ana Belén Cuenca for her support and expertise,which helped to confirm the proposed reaction mechanism involved in the UV photolysis of cloperastine.
文摘The increasing production and release of synthetic organic chemicals,including pharmaceuticals,into our envi-ronment has allowed these substances to accumulate in our surface water systems.Current purification technolo-gies have been unable to eliminate these pollutants,resulting in their ongoing release into aquatic ecosystems.This study focuses on cloperastine(CPS),a cough suppressant and antihistamine medication.The environmental impact of CPS usage has become a concern,mainly due to its increased detection during the COVID-19 pandemic.CPS has been found in wastewater treatment facilities,effluents from senior living residences,river waters,and sewage sludge.However,the photosensitivity of CPS and its photodegradation profile remain largely unknown.This study investigates the photodegradation process of CPS under simulated tertiary treatment conditions using UV photolysis,a method commonly applied in some wastewater treatment plants.Several transformation prod-ucts were identified,evaluating their kinetic profiles using chemometric approaches(i.e.,curve fitting and the hard-soft multivariate curve resolution-alternating least squares(HS-MCR-ALS)algorithm)and calculating the reaction quantum yield.As a result,three different transformation products have been detected and correctly identified.In addition,a comprehensive description of the kinetic pathway involved in the photodegradation process of the CPS drug has been provided,including observed kinetic rate constants.
基金Supported by Innovation Capability Support Program of Shaanxi(2024RS-CXTD-53,2024ZC-KJXX-096)the Key R&D Program of Shaanxi Province(2022QCY-LL-69)Xi’an Science and Technology Project(24GXFW0089)。
文摘Under the backdrop of“Carbon Peak and Carbon Neutrality”(dual carbon)goal in China,the methane-carbon dioxide reforming reaction has attracted considerable attention due to its environmental benefits of converting two greenhouse gases(methane and carbon dioxide)into syngas and its promising industrial applications.Nickel(Ni)-based catalysts,with high catalytic activity,low cost,and abundant resources,are considered ideal candidates for industrial applications.In this article,three reaction kinetic models were briefly introduced,namely the Power-Law(PL)model,the Eley-Rideal(ER)model,and the Langmuir-Hinshelwood-Hougen-Watson(LHHW)model.Based on the LHHW model,the reaction kinetics and mechanisms of different catalytic systems were systematically discussed,including the properties of supports,the doping of noble metals and transition metals,the role of promoters,and the influence of the geometric and electronic structures of Ni on the reaction mechanism.Furthermore,the kinetics of carbon deposition and elimination on various catalysts were analyzed.Based on the reaction rate expressions for carbon elimination,the reasons for the high activity of transition metal iron(Fe)-doped catalysts and core-shell structured catalysts in carbon elimination were explained.Based on the detailed collation and comparative analysis of the reaction mechanisms and kinetic characteristics across diverse Ni-based catalytic systems,a theoretical guidance for the designing of high-performance catalysts was provided in this work.
文摘Hydrocarbon generation kinetics are influenced by complex factors,including temperature,reaction time,pressure,and molecular structure,which render simple modeling approaches inadequate for accurately simulating methane generation.The closed-system pyrolysis experiment,a common method to study hydrocarbon generation,poses challenges for kinetic parameter regression due to limited data points.This limitation necessitates the application of sophisticated data analysis techniques to extract meaningful insights from sparse experimental data.This paper establishes a quantitative relationship between methane production and the thermal process through closed system pyrolysis experiments.A nonlinear regression model using multiple algorithms is established based on this quantitative relationship.Accordingly,a method that can quantitatively invert the methane generation kinetic parameters corresponding to the samples based on the experimental data is provided.Based on this theoretical model,a computer program capable of processing experimental data is designed and implemented.Practical analyses are performed using the method above for three samples:a coal sample from the Yulong,Guizhou;a solid bitumen sample from Guangyuan,Sichuan;and a marlstone sample containing type Ⅰ kerogen from Luquan,Yunnan.The results obtained agree with the qualitative estimates based on hydrocarbon generation kinetic theory using the previous method.Thus,the validity of the new data processing method,the new mathematical model,and the data processing procedures are verified.
基金Yannick Ureel and Maarten Dobbelaere acknowledge financial support from the Fund for Scientific Research Flanders(FWO Flanders)respectively through doctoral fellowship grants(1185822N and 1S45522N)The authors acknowledge funding from the European Research Council under the European Union’s Horizon 2020 research and innovation programme/ERC(818607).
文摘1.Colors of chemical reaction engineering models Kinetic models of chemical reactions are a crucial asset for understanding and optimizing chemical processes[1].These models are critical for reactor design,process optimization,catalyst design,scale-up,and process control,making them indispensable in the chemical industry.Kinetic models predict the change in temperature and concentration of the relevant species,given an actual concentration and temperature.Reaction predictions are made by integrating the kinetic model with a reactor model,which accounts for external constraints,such as flow,inlet concentration。
基金supported by National Natural Science Foundation of China(Basic Science Center Program:61988101)National Natural Science Foundation of China(62394345,62373155,62173147)the Major Science and Technology Project of Xinjiang(No.2022A01006-4).
文摘Industrial ebullated-bed is an important device for promoting the cleaning and upgrading of oil products. The lumped kinetic model is a powerful tool for predicting the product yield of the ebullated-bed residue hydrogenation (EBRH) unit, However, during the long-term operation of the device, there are phenomena such as low frequency of material property analysis leading to limited operating data and diverse operating modes at the same time scale, which poses a huge challenge to building an accurate product yield prediction model. To address these challenges, a data augmentation-based eleven lumped reaction kinetics mechanism model was constructed. This model combines generative adversarial networks, outlier elimination, and L2 norm data filtering to expand the dataset and utilizes kernel principal component analysis-fuzzy C-means for operating condition partitioning. Based on the hydrogenation reaction mechanism, a single and sub operating condition eleven lumped reaction kinetics model of an ebullated-bed residue hydrogenation unit, comprising 55 reaction paths and 110 parameters, was constructed before and after data augmentation. Compared to the single model before data enhancement, the average absolute error of the sub-models under data enhancement division was reduced by 23%. Thus, these findings can help guide the operation and optimization of the production process.
基金supported by National Key Research and Development Program of China (2023YFB3307800)National Natural Science Foundation of China (Key Program: 62136003, 62373155)+1 种基金Major Science and Technology Project of Xinjiang (No. 2022A01006-4)the Fundamental Research Funds for the Central Universities。
文摘Hydrocracking is one of the most important petroleum refining processes that converts heavy oils into gases,naphtha,diesel,and other products through cracking reactions.Multi-objective optimization algorithms can help refining enterprises determine the optimal operating parameters to maximize product quality while ensuring product yield,or to increase product yield while reducing energy consumption.This paper presents a multi-objective optimization scheme for hydrocracking based on an improved SPEA2-PE algorithm,which combines path evolution operator and adaptive step strategy to accelerate the convergence speed and improve the computational accuracy of the algorithm.The reactor model used in this article is simulated based on a twenty-five lumped kinetic model.Through model and test function verification,the proposed optimization scheme exhibits significant advantages in the multiobjective optimization process of hydrocracking.
基金supported by the National Natural Science Foundation of China(Grant No.11974420).
文摘We study the thermodynamic properties of the classical one-dimensional generalized nonlinear Klein-Gordon lattice model(n≥2)by using the cluster variation method with linear response theory.The results of this method are exact in the thermodynamic limit.We present the single-site reduced densityρ^((1))(z),averages such as(z^(2)),<|z^(n)|>,and<(z_(1)-z_(2))^(2)>,the specific heat C_(v),and the static correlation functions.We analyze the scaling behavior of these quantities and obtain the exact scaling powers at the low and high temperatures.Using these results,we gauge the accuracy of the projective truncation approximation for theφ^(4)lattice model.
基金supported by the Fundamental Research Funds for the Central Universities(No.FRF-TP-19-017A3)National Natural Science Foundation of China(No.51874026).
文摘The continuous growth behavior of austenite grain in 20Cr peritectic steel was analyzed by experiment and theoretical modeling.The peculiar casting experiment with different cooling rates was achieved by multigradient operation scheme,and different morphologies in austenite grain were observed at the target location.The increase in austenite grain size with increasing cooling rate was firstly revealed in steels.The anomalous grain growth theoretically results from the mechanism of peritectic transformation transiting from the diffusional to massive type,and the additional energy storage stimulates the grain boundary migration.A new kinetic model to predict the growth behavior of austenite grain during continuous cooling process was developed,and the energy storage induced by massive type peritectic transformation was novelly taken into account.The parameters in the model were fitted by multiphase field modeling and experimental results.The kinetic model was finally verified by austenite grain size in laboratory test as well as the trial data at different locations in continuously cast bloom.The coarsening behavior of austenite grain during continuous casting was predicted based on the simulated temperature history.It is found that the grain coarsening occurs generally in the mold zone at high temperature for 20Cr steel and then almost levels off in the following process.The austenite finish transformation temperature Tγand primary cooling intensity show great influence on the grain coarsening.As Tγdecreases by 1℃,the austenite grain size decreases by 4μm linearly.However,the variation of Tγagainst heat flux is in a nonlinear relationship,suggesting that low cooling rate is much more harmful for austenite grain coarsening in continuous casting.
基金funded by the National Key R&D Program of China(No.2021YFB3702404)the National Natural Science Foundation of China(Nos.52201101 and 52274372)+1 种基金the Major Program Funding of Cisri(No.21T62450ZD)the Fundamental Research Funds for the Central Universities(Nos.FRF-TP-22-013A1 and FRF-TP-22-015A1).
文摘The cold-rolled quenching and partitioning(Q&P)steel with an initial microstructure of deformed ferrite and pearlite was studied.The microstructural evolution under various heating rates of 1.78,50,and 300℃/s was investigated using microstructural characterization and theoretical modeling.At the same time,the characteristics of recrystallization and austenite formation kinetics were decoupled by examining recrystallized ferrite and deformed ferrite as initial conditions.The findings revealed that the austenite formation during continuous heating can be simplified into two stages:(i)the early nucleation-dominated formation stage and(ii)the later grain growth-dominated stage,resulting in the development of a modified two-stage model based on Johnson-Mehl-Avrami-Kolmogorov.Further experiments confirmed that when the austenite volume fraction exceeded approximately 5% at a heating rate of 1.78℃/s,ferrite recrystallization was suppressed.In consequence,a mixed model including recrystallization kinetics was employed to couple the austenite formation occurring in deformed ferrite and recrystallized ferrite,thereby describing the austenite formation kinetics affected by recrystallization.Precise predictions of non-isothermal austenite formation kinetics in cold-rolled Q&P steel were achieved during slow and ultrafast heating processes by integrating the suppression effect into the model for austenite formation.
基金Supported by the Hong Kong Research Grants Council (Project No.GRF16300918)the National Key R&D Program of China(Grant Nos.2016YFA0300603 and 2016YFA0302400)the National Natural Science Foundation of China (Grant No.11774398)。
文摘Kinetic energy(KE) functional is crucial to speed up density functional theory calculation. However, deriving it accurately through traditional physics reasoning is challenging. We develop a generally applicable KE functional estimator for a one-dimensional (1D) extended system using a machine learning method. Our end-to-end solution combines the dimensionality reduction method with the Gaussian process regression, and simple scaling method to adapt to various 1D lattices. In addition to reaching chemical accuracy in KE calculation, our estimator also performs well on KE functional derivative prediction. Integrating this machine learning KE functional into the current orbital free density functional theory scheme is able to provide us with expected ground state electron density.
基金Supported by National Natural Sciences Foundation of China(40373044)the Natural Science Foundation of the Jiangsu Higher Education Institutions of China(05KJD610209)~~
文摘To investigate the growth conditions of white-rot fungus and simulate its metabolism kinetic models, the rules how the factors such as biomass, culture fluid, pH value, glucose consumption and exopolysaccharides generation, etc., changed during the batch culture process of white-rot fungi by using an air-lift fermenter, as well as metabolic kinetics of white-rot fungi were studied. Based on Logistic equation, Luedeking-Piret equation and experimental data, the correlation model parameters of mycelia biomass, glucose consumption and exopolysaccharide generation were obtained and found to be change with time in metabolism process. Detailedly, μm=0.071 8 h-1,α= 0.831 8 g/(g·h), β= 0.002 g/(g·h), b1=0.016 3 g/(g·h) and b2=3.023 3 g/(g·h). Hence the mycelial growth kinetic model, exopolysaccharide generation kinetic model and substrate consumption kinetic model which describe fermentation process of white-rot fungi were established. Meanwhile, the experimental data were verified by this model, and a good fitting result with an average relative error less than 10% between the data obtained from experiments and the model was yielded. The results show that these models can predict the growth and metabolic rules of white-rot fungus, the fermentation process of exopolysaccharides and the kinetic mechanism of white-rot fungus accurately.
基金This work is supported by the National Natu- ral Science Foundation of China （No.51106146 and No.51036007）, China Postdoctoral Science Foundation （No.20100480047 and No.201104326）, Chinese Univer- sities Scientific Fund （No.WK2310000010）, and Chinese Academy of Sciences.
文摘Pyrolysis of benzene at 30 Torr was studied from 1360 K to 1820 K in this work. Synchrotron vacuum ultraviolet photoionization mass spectrometry was employed to detect the pyroly- sis products such as radicals, isomers and polycyclic aromatic hydrocarbons, and measure their mole fraction profiles versus temperature. A low-pressure pyrolysis model of benzene was developed and validated by the experimental results. Rate of production analysis was performed to reveal the major reaction networks in both fuel decomposition and aromatic growth processes. It is concluded that benzene is mainly decomposed via H-abstraction reaction to produce phenyl and partly decomposed via unimolecular decomposition reac- tions to produce propargyl or phenyl. The decomposition process stops at the formation of acetylene and polyyne species like diacetylene and 1,3,5-hexatriyne due to their high thermal stabilities. Besides, the aromatic growth process in the low-pressure pyrolysis of benzene is concluded to initiate from benzene and phenyl, and is controlled by the even carbon growth mechanism due to the inhibited formation of C5 and C7 species which play important roles in the odd carbon growth mechanism.
基金State Key Laboratory of Natural and Biomimetic Drugs 2013 Funded Project "Establishment and Application an Online Natural Medicines System with Efficient Separation,Structural Identification and Activity Detection"
文摘In the present study, we studied the inhibitory effects of chelidonine and rutaecarpin on porcine pancreatic a-amylase （PPA） catalyzed hydrolysis using 2-chloro-4-nitrophenyl-4-O-β-D-galactopyranosylmaltoside （Gal-G2-α-CNP）. We, for the first time, provided kinetic report and detailed inhibitory effects of both compounds on PPA. Lineweaver-Burk plot revealed that the inhibition was a mixed-noncompetitive type, and only one molecule of inhibitor bound to the enzyme or to the enzyme-substrate complex. Kinetic constants calculated from secondary plots were in millimole range. Dissociation constants of enzyme-inhibitor complex （KEI） were 0.9 mM and 3.5 mM, respectively. Moreover, dissociation constants of enzyme-inhibitor-substrate complex （KESI） were 0.04 mM and 0.31 mM, respectively. These data indicated that the inhibition was more inclined to competitive to Gal-G2-α-CNP hydrolysis. Further molecular docking study manifested that hydrogen bonding formed between acarbose and aspartic acid （Asp300）, histidine （His305） and glycine （Gly3-6）, while hydrogen bonding was observed between chelidonine and glutamic acid （Glu233）, lysine （Lys200） and His305. In addition, rutaecarpine had only one hydrogen bond with Lys200. Our data indicated that chelidonine and rutaecarpine were two promising drug candidates, and chelidonine possessed stronger inhibitory effect compared with rutaecarpine.
基金financially supported by the National Science Foundation of China(Nos.51974212 and 52274316)the China Baowu Low Carbon Metallurgy Innovation Foundation(No.BWLCF202116)+1 种基金the Science and Technology Major Project of Wuhan(No.2023020302020572)the Foundation of Key Laboratory for Ferrous Metallurgy and Resources Utilization of Ministry of Education(No.FMRUlab23-04)。
文摘The utilization of iron coke provides a green pathway for low-carbon ironmaking.To uncover the influence mechanism of iron ore on the behavior and kinetics of iron coke gasification,the effect of iron ore on the microstructure of iron coke was investigated.Furthermore,a comparative study of the gasification reactions between iron coke and coke was conducted through non-isothermal thermogravimetric method.The findings indicate that compared to coke,iron coke exhibits an augmentation in micropores and specific surface area,and the micropores further extend and interconnect.This provides more adsorption sites for CO_(2) molecules during the gasification process,resulting in a reduction in the initial gasification temperature of iron coke.Accelerating the heating rate in non-isothermal gasification can enhance the reactivity of iron coke.The metallic iron reduced from iron ore is embedded in the carbon matrix,reducing the orderliness of the carbon structure,which is primarily responsible for the heightened reactivity of the carbon atoms.The kinetic study indicates that the random pore model can effectively represent the gasification process of iron coke due to its rich pore structure.Moreover,as the proportion of iron ore increases,the activation energy for the carbon gasification gradually decreases,from 246.2 kJ/mol for coke to 192.5 kJ/mol for iron coke 15wt%.
基金financially supported by Universitas Gadjah Mada partly through LPDP’s Molina Project fiscal year 2015 and partly by University Grant for Applied Research (PTUPT) 2018the support given by the Department of Earth Resource, Kyushu University for the research facilities provided during joint research in Sakura Science Project under Japan Science and Technology Agency
文摘Lithium and cobalt recovery from spent lithium-ion batteries(LIBs) is a major focus because of their increased production and usage. The conventional method for recycling spent LIBs using inorganic acids produces harmful byproducts. In this work, the leaching agent was substituted with a less expensive and more environmentally friendly alternative—acetic acid—and a mathematical model was developed to describe the kinetics of the recovery process. The variables used were the pH value, temperature, H_2O_2 concentration, and the solid-to-liquid(S/L) ratio. The mathematical model used was the shrinking core model, which was modified to accommodate an equilibrium reaction. The experimental results show that the rate of recovery of Li and Co over time was only affected by temperature. The leaching behaviors of Li and Co were found to oppose each other. An increase in temperature resulted in increased recovery of Li but decreased recovery of Co because of the product-favoring endothermic reaction of Li and the reactant-favoring exothermic reaction of Co. The product of Li has a lower entropy value than the reactant as a free-moving ion, whereas the product of Co leaching has a higher entropy value as a stiff crystal complex. Thus, temperature conditioning is a pivotal factor in the leaching of spent LIBs.
基金financially supported by the National Key R&D Program of China (Nos. 2017YFB0703001 and 2017YFB0305100)the National Natural Science Foundation of China (Nos. 51134011, 51431008, 51790483 and 51801157)+4 种基金the Fundamental Research Funds for the Central Universities (No. 3102017zy064)the Research Fund of the State Key Laboratory of Solidification Processing (Nos. 117-TZ-2015, 159-QP-2016)the Analytical & Testing Center of Northwestern Polytechnical University for Equipment Supportfinancial support from the Top International University Visiting Program for Outstanding Young Scholars of Northwestern Polytechnical Universitythe China Scholarship Council (CSC) Scholarship
文摘During the multi-stage processing of advanced high-strength steels, the austenite-to-ferrite transformation, generally as a precursor of the formation of other non-equilibrium or metastable structures, has a severe effect on the subsequent phase transformations. Herein, a more flexible kinetic and microstructural predictive modeling for the key austenite-to-ferrite transformation of Fe-C-Mn-Si steels was developed,in combination with the classical nucleation theory, the general mixed-mode growth model based on Gibbs energy balance, the microstructural path method and the kinetic framework for grain boundary nucleation. Adopting a bounded, extended matrix space corresponding to a single ferrite grain, both softimpingement and hard-impingement can be naturally included in the current modeling. Accordingly, this model outputs the ferrite volume fraction, the austenite/ferrite interface area per unit volume, and the average grain size of ferrite, which will serve as the input parameters for modeling the subsequent bainite or martensite transformations. Applying the model, this work successfully predicts the experiment measurement of the isothermal austenite-to-ferrite transformation in Fe-0.17 C-0.91 Mn-1.03 Si(wt%) steel at different temperatures and explains why the final-state average grain size of ferrite has a maximum at the moderate annealing temperature. Effectiveness and advantages of the present model are discussed arising from kinetics and thermodynamics accompanied with nucleation, growth and impingement.
基金Item Sponsored by Fok Ying Tung Education Foundation(101048)Natural Science Foundation of Hebei Province of China(E2008000835)
文摘The static recrystallization behavior of low-alloy steel Q345B during double-pass hot compression deformation tests was investigated in the temperature range of 900-1000 ℃,the true strain range of 0.15-0.25 and the interpass time range of 0.5-50 s on Gleeble-3500 thermo-simulation machine.The results show that static recrystallization during the interpass time is observed.As the deformation temperature and strain increase,softening caused by static recrystallization is obvious.According to the analysis and calculation of thermo-simulation data,the static recrystallization activation energy was obtained and static recrystallization kinetics model was built.Finally,the error analysis of static recrystallization kinetics model proved that the model had good accuracy.Therefore,this model provides a theoretical basis for static recrystallization（SRX）and will contribute to the development of multipass hot rolling process,in order to control the rolling process more accurately.
基金supported by the National Natural Science Foundation of China (No. 20504012)the New Century Excellent Talents in University of China (No. NCET-07-0421)
文摘Adsorption is one of the most widely applied techniques for environmental remediation. Its kinetics are of great significance to evaluate the performance of a given adsorbent and gain insight into the underlying mechanisms. There are lots of references available concerning adsorption kinetics, and several mathematic models have been developed to describe adsorption reaction and diffusion processes. However, these models were frequently employed to fit the kinetic data in an unsuitable or improper manner. This is mainly because the boundary conditions of the associated models were, to a considerable extent, ignored for data modeling. Here we reviewed several widely-used adsorption kinetic models and paid more attention to their boundary conditions. We believe that the review is of certain significance and improvement for adsorption kinetic modeling.
