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
In this study,copper extraction from low-grade oxide-sulfide ores was investigated using a leaching method combined with response surface methodology(RSM)to optimize operational conditions and assess leaching kinetics...In this study,copper extraction from low-grade oxide-sulfide ores was investigated using a leaching method combined with response surface methodology(RSM)to optimize operational conditions and assess leaching kinetics.Given copper's extensive industrial applications,sustainable recovery from low-grade ores is critical.Five key parameters-acid concentration,leaching time,particle size,temperature,and solids percentage-were identified as major influences on copper recovery.The results revealed that leaching time and solids percentage,along with interactions between temperature-time and temperature-solids percentage,had the most significant effects.Optimal conditions for 80% copper recovery while minimizing iron recovery below 3% included an acid concentration of 1.21 mol L^(-1),a leaching time of 108 min,a particle size of 438μm,a temperature of 45℃,and a solids percentage of 18.2%.Leaching kinetics were analyzed using shrinking core models,with the Dickinson model best describing the process,showing an activation energy of 32.63 kJ mol^(-1),indicative of mixed diffusion and chemical reaction control.The final kinetic model effectively predicted the influence of key parameters.These findings highlight the importance of optimizing process variables and selecting suitable kinetic models to enhance extraction efficiency,reduce costs,and improve sustainability in copper recovery.展开更多
In order to explore the effects of CaO,lignite dust and sawdust on the drying characteristics ofmunicipal sludge at different concentrations,a three-factor three-level regression experiment was carried out based on th...In order to explore the effects of CaO,lignite dust and sawdust on the drying characteristics ofmunicipal sludge at different concentrations,a three-factor three-level regression experiment was carried out based on the results of thermogravimetric experiment and single factor experiment.By fitting three common mathematical models,the Page model with the highest fitting degree was selected to determine the most suitable mathematical model to describe the municipal sludge drying process.In addition,the Box-Behnken design principle in the response surface method was used to analyze the interaction of three factors on the drying characteristics of municipal sludge.The results of the study show that below 100℃is the optimal drying temperature range for municipal sludge.The results of single factor experiments showed that the order of influence of the three factors on sludge drying time was CaO concentration>sawdust concentration>lignite dust concentration.In the single factor experiment,the optimal process parameterswere CaOconcentration 3%,lignite powder concentration 7%,and sawdust concentration 7%.In themulti-factor interaction analysis,the interaction between CaO and sawdust had the most significant effect on the reduction of drying time,and the order of influence was as follows:CaO interaction with sawdust>lignite dust interaction with sawdust>CaO interaction with lignite powder.Further analysis showed that the optimal process ratio was 3%CaO concentration and 3%sawdust concentration.展开更多
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
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
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
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
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
The accumulation and release of deformation energy within the rock mass of a roadway are primary contributors to the occurrence of rock bursts.This study introduces a calculation model for the kinetic energy generated...The accumulation and release of deformation energy within the rock mass of a roadway are primary contributors to the occurrence of rock bursts.This study introduces a calculation model for the kinetic energy generated during roadway excavation,which is based on the fracture and energy states of the rock mass.The relationships among the mining depth,width of the plastic zone,rebound range of the roof and floor,stress concentration factor,and the induced kinetic energy are systematically explored.Furthermore,a rock burst risk evaluation method is proposed.The findings indicate that the energy evolution of the rock mass can be categorized into four stages:energy accumulation due to in-situ stress,energy accumulation resulting from coal compression,energy dissipation through coal plastic deformation,and energy consumption due to coal failure.The energy release from the rock mass is influenced by several factors,including mining depth,stress concentration factor,the width of the plastic zone,and the rebound range of the roof and floor.Within the plastic zone of coal,the energy released per unit volume of coal and the induced kinetic energy exhibit a nonlinear increase with mining depth and stress concentration factor,while they decrease linearly as the width of the plastic zone increases.Similarly,the driving energy per unit volume of the roof and floor shows a nonlinear increase with mining depth and stress concentration factor,a linear increase with the rebound range of the roof and floor,and a linear decrease with the width of the plastic zone.A rock burst risk evaluation method is developed based on the kinetic energy model.Field observations demonstrate that this method aligns with the drilling cuttings rock burst risk assessment method,thereby confirming its validity.展开更多
The volatilization characteristics and kinetic mechanisms of arsenic were investigated in the temperature range of 623−773 K and pressure ranges of 10−10000 Pa.The experimental results reveal that the evaporation rate...The volatilization characteristics and kinetic mechanisms of arsenic were investigated in the temperature range of 623−773 K and pressure ranges of 10−10000 Pa.The experimental results reveal that the evaporation rate increases with increasing temperature and decreasing pressure.Surface reaction control dominates at low pressures(<100 Pa),whereas diffusion control dominates at high pressures(>5000 Pa).The evaporation behavior is successfully described by an Arrhenius-type model for temperature dependence and Logistic model for pressure dependence.Key kinetic parameters,including the critical pressure,maximum evaporation rate and evaporation coefficient,were calculated.The evaporation coefficient varies between 0.010 and 0.223,and the critical pressures vary between 281 and 478 Pa with temperature.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
Eggshells,a by-product of the food industry,represent a significant yet often overlooked waste stream.Given their vast production volume and inherent properties,eggshells have the potential to serve as a sustainable a...Eggshells,a by-product of the food industry,represent a significant yet often overlooked waste stream.Given their vast production volume and inherent properties,eggshells have the potential to serve as a sustainable and environmentally friendly co-fuel.Aiming to explore the co-combustion characteristics and kinetics of pulverized coal blended with eggshells and offer insights into their combined use as a renewable energy source,a systematic investigation was conducted to evaluate the physical and chemical properties of Shangwan bituminous coal,Shouyang anthracite coal,eggshell(ES)and their blends.Additionally,comprehensive experimental analyses were performed at different heating rates applying a non-isothermal thermogravimetric method.The findings revealed that the addition of ES enhanced the combustion efficiency.The combustion characteristics were significantly influenced by the ES content,with an optimal blend ratio identified for maximum combustion efficiency.To represent the thermal degradation experiments,random pore model and volume model were employed.Furthermore,activation energies and pre-exponential factors were determined.The random pore model demonstrated more superior performance compared to the volume model.The activation energies of all the samples ranged between 18.29 and 42.48 kJ/mol,with the lowest value observed for the sample containing 20 mass%ES.展开更多
Recent work analysing magnesium hydrogenation using Reflecting Electron Energy Loss Spectroscopy(REELS)and Density Function Theory(DFT)has indicated interfacial polarisation and interstitial hydrogen clustering influe...Recent work analysing magnesium hydrogenation using Reflecting Electron Energy Loss Spectroscopy(REELS)and Density Function Theory(DFT)has indicated interfacial polarisation and interstitial hydrogen clustering influence the reaction rate.The site availability model has been modified to include interstitial hydrogen clustering within the site availability factor and interface polarisation using interface treatment.The new model,SAM-CV-S,has demonstrated improved modelling of magnesium hydrogenation across wide operating conditions,such as temperatures from 330 to 400℃and pressures up to 40 bar.This wide applicability makes it a robust model that can be used to simulate bed performance in solid-state hydrogen stores.Thus,the site availability factor successfully combines interstitial hydrogen clustering with thermal resistance effects,which are known to strongly influence metal hydride reactor designs at scale.The next phase of the model is to incorporate a predictive hydrogen capacity method into the model.展开更多
The removal of H_(2)S from coke oven gas (COG) is an important issue for the further utilization of COG. Zeolites could be used for industrial desulfurization owing to their high thermal stability and regenerability. ...The removal of H_(2)S from coke oven gas (COG) is an important issue for the further utilization of COG. Zeolites could be used for industrial desulfurization owing to their high thermal stability and regenerability. However, further analysis on the kinetics of deep desulfurization using zeolites is necessary to provide relevant information for industrial design. In this study, the desulfurization breakthrough curves of faujasite (FAU) zeolite in COG were measured using a fixed bed reactor. The adsorption isotherm was investigated using the Langmuir, Freundlich, Temkin, Dubinin-Radushkevich models. The adsorption saturated capacity of H_(2)S was inversely related to the temperature. The results show that the Langmuir model best fits the adsorption isotherm with a lower value of root-mean-square-error (RMSE) and Chi-Square (χ^(2)), and the calculated activation energy is 14.62 kJ·mol^(−1). The adsorption kinetics were investigated using pseudo-first-order (PFO), pseudo-second-order (PSO), Bangham and Weber-Morris models. The Bangham model fitted the kinetic data well, indicating that pore diffusion is an influential factor in the adsorption process. The Weber-Morris model suggests that the adsorption rate was not solely determined by the pore diffusion, but was also influenced by the active site on the FAU zeolite. The adsorption breakthrough curves under different gas flow rates were fitted using the bed depth service time (BDST) model, and it provides an accurate prediction of the breakthrough time with a small relative error. The results of thermodynamic analysis demonstrated the feasibility and spontaneity (ΔG<0) and exothermic (ΔH<0) nature of the adsorption process of the FAU zeolite for H_(2)S under COG.展开更多
The microstructural characteristics of austenite in Ti microalloyed steel during continuous casting significantly influence thethermoplasticity,thereby affecting the quality of the slab.In this work,a prediction model...The microstructural characteristics of austenite in Ti microalloyed steel during continuous casting significantly influence thethermoplasticity,thereby affecting the quality of the slab.In this work,a prediction model for two-stage austenite growth under varyingcooling rates was established by incorporating the effect of second-phase pinning and high-temperature ferrite-austenite phase transform-ation and growth theory.The results indicate that with 0.02wt%Ti,the high-temperature ferrite growth exhibits typical parabolic growthcharacteristics.When the Ti content increases to 0.04wt%,the high-temperature ferrite grain boundary migration rate significantly slowsduring the initial solidification stage.The predicted austenite grain sizes for 0.02wt%Ti microalloyed steel at the center,quarter,and sur-face of the slab are 5592,3529,and 1524μm,respectively.For 0.04wt%Ti microalloyed steel,the austenite grain sizes are 4074,2942,and 1179μm at the same positions.The average error is within 5%.As the Ti content increases from 0.02wt% to 0.04wt%,the austenitegrain refinement at the center is most significant,with an average grain size reduction of 27.14%.展开更多
Process of dynamic recrystallization(DRX)plays a crucial role in altering the microstructure and enhancing the mechanical characteristics of CrNiMoVW steel.However,its initiation mechanism,deformation conditions,and p...Process of dynamic recrystallization(DRX)plays a crucial role in altering the microstructure and enhancing the mechanical characteristics of CrNiMoVW steel.However,its initiation mechanism,deformation conditions,and predictive models remain insufficiently understood,requiring further research to optimize the processing technology.In the present study,hot compression experiments were carried out on 30CrNiMoVW steel under deformation conditions with temperatures ranging from 950 to 1,250℃and strain rates from 0.001 to 1 s~(-1),during which true stress-strain curves were obtained.Based on friction and temperature corrections applied to these curves,a constitutive equation for 30CrNiMoVW steel was established,and its accuracy was verified through fitting analysis.Simultaneously,the study identified limitations in the initial volume fraction model,prompting the development of a modified recrystallization volume fraction model that was validated via correlation analysis between experimental data and model predictions.Furthermore,building upon the modified recrystallization volume fraction model,a novel recrystallization rate model was developed,and three characteristic strain points were determined.These points segmented the rate curve into three stages:a slow initiation stage(0,ε1),a rapid growth stage(1,ε3),and a slow equilibrium stage(e3,0.9).Notably,the value ofε3 was considered the most economical,ensuring the formation of fine and uniform grains during production while optimizing the process,reducing energy consumption and costs,and enhancing overall material performance.Finally,based on the physical constitutive relationships and kinetic models,a multiscale simulation approach combining the finite element method(FEM)and cellular automata(CA)was employed to predict the microstructural evolution of 30CrNiMoVW steel.The simulation results demonstrate that the FEM&CA approach can accurately reproduce the dynamic recrystallization behavior and microstructural evolution observed experimentally.This work provides critical guidance for the development of forging processes for 30CrNiMoVW steel.展开更多
In this context,the present study proposes the use of microwave irradiation to improve the dehydration rate and efficiency of strontium hydroxide octahydrate(Sr(OH)_(2)·8H_(2)O)without introducing contaminants.Th...In this context,the present study proposes the use of microwave irradiation to improve the dehydration rate and efficiency of strontium hydroxide octahydrate(Sr(OH)_(2)·8H_(2)O)without introducing contaminants.This study revealed that the use of microwave irradiation to dehydrate Sr(OH)_(2)·8H_(2)O is feasible and surprisingly efficient.The effects of this approach on important parameters were investigated using response surface methodology(RSM).The results revealed that the microwave dehydration process follows a linear polynomial model.In addition,compared with the heating time and material thickness,the microwave-assisted dehydration of Sr(OH)_(2)·8H_(2)O is sensitive to the microwave power and not to the material mass.The relative dehydration percentage reached 99.99%when heated in a microwave oven at 950Wfor just 3 min.In contrast,a relative dehydration percentage of 94.6%was reached when heated in an electric furnace at 180℃for 120 min.The XRD spectra also revealed that most of the Sr(OH)_(2)·8H_(2)O transformed into Sr(OH)_(2)after dehydration via microwave irradiation,whereas a significant portion of the Sr(OH)_(2)·H_(2)O remained after conventional electric dehydration.The experimental data were fitted and analyzed via the thin-layer drying dynamics model,and the results indicated that the dehydrating behavior of Sr(OH)_(2)·8H_(2)O could be well described by the Page model.展开更多
Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLM...Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLMs.Therefore,in order to better assess the capability of LLMs in the agricultural domain,Agri-Eval was proposed as a benchmark for assessing the knowledge and reasoning ability of LLMs in agriculture.The assessment dataset used in Agri-Eval covered seven major disciplines in the agricultural domain:crop science,horticulture,plant protection,animal husbandry,forest science,aquaculture science,and grass science,and contained a total of 2283 questions.Among domestic general-purpose LLMs,DeepSeek R1 performed best with an accuracy rate of 75.49%.In the realm of international general-purpose LLMs,Gemini 2.0 pro exp 0205 standed out as the top performer,achieving an accuracy rate of 74.28%.As an LLMs in agriculture vertical,Shennong V2.0 outperformed all the LLMs in China,and the answer accuracy rate of agricultural knowledge exceeded that of all the existing general-purpose LLMs.The launch of Agri-Eval helped the LLM developers to comprehensively evaluate the model's capability in the field of agriculture through a variety of tasks and tests to promote the development of the LLMs in the field of agriculture.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Open Access funding enabled and organized by Projekt DEAL.
文摘In this study,copper extraction from low-grade oxide-sulfide ores was investigated using a leaching method combined with response surface methodology(RSM)to optimize operational conditions and assess leaching kinetics.Given copper's extensive industrial applications,sustainable recovery from low-grade ores is critical.Five key parameters-acid concentration,leaching time,particle size,temperature,and solids percentage-were identified as major influences on copper recovery.The results revealed that leaching time and solids percentage,along with interactions between temperature-time and temperature-solids percentage,had the most significant effects.Optimal conditions for 80% copper recovery while minimizing iron recovery below 3% included an acid concentration of 1.21 mol L^(-1),a leaching time of 108 min,a particle size of 438μm,a temperature of 45℃,and a solids percentage of 18.2%.Leaching kinetics were analyzed using shrinking core models,with the Dickinson model best describing the process,showing an activation energy of 32.63 kJ mol^(-1),indicative of mixed diffusion and chemical reaction control.The final kinetic model effectively predicted the influence of key parameters.These findings highlight the importance of optimizing process variables and selecting suitable kinetic models to enhance extraction efficiency,reduce costs,and improve sustainability in copper recovery.
基金the National Natural Science Foundation of China,grant number 52406074the China Postdoctoral Science Foundation under Grant Number 2025T180171+1 种基金the Natural Science Foundation of Guangdong Province(2025A1515011270)the China Southern Power Grid Technology Project(GDKJXM20231415/030100KC23120104).
文摘In order to explore the effects of CaO,lignite dust and sawdust on the drying characteristics ofmunicipal sludge at different concentrations,a three-factor three-level regression experiment was carried out based on the results of thermogravimetric experiment and single factor experiment.By fitting three common mathematical models,the Page model with the highest fitting degree was selected to determine the most suitable mathematical model to describe the municipal sludge drying process.In addition,the Box-Behnken design principle in the response surface method was used to analyze the interaction of three factors on the drying characteristics of municipal sludge.The results of the study show that below 100℃is the optimal drying temperature range for municipal sludge.The results of single factor experiments showed that the order of influence of the three factors on sludge drying time was CaO concentration>sawdust concentration>lignite dust concentration.In the single factor experiment,the optimal process parameterswere CaOconcentration 3%,lignite powder concentration 7%,and sawdust concentration 7%.In themulti-factor interaction analysis,the interaction between CaO and sawdust had the most significant effect on the reduction of drying time,and the order of influence was as follows:CaO interaction with sawdust>lignite dust interaction with sawdust>CaO interaction with lignite powder.Further analysis showed that the optimal process ratio was 3%CaO concentration and 3%sawdust concentration.
基金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 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 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.
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financially supported by the National Natural Science Foundation of China(Nos.52374094 and 52274086)the Climbling Project of Taishan Scholar in Shandong Province(No.tspd20210313)the Shandong Provincial Youth Innovation and Technology Support Program(No.2024KJH069)。
文摘The accumulation and release of deformation energy within the rock mass of a roadway are primary contributors to the occurrence of rock bursts.This study introduces a calculation model for the kinetic energy generated during roadway excavation,which is based on the fracture and energy states of the rock mass.The relationships among the mining depth,width of the plastic zone,rebound range of the roof and floor,stress concentration factor,and the induced kinetic energy are systematically explored.Furthermore,a rock burst risk evaluation method is proposed.The findings indicate that the energy evolution of the rock mass can be categorized into four stages:energy accumulation due to in-situ stress,energy accumulation resulting from coal compression,energy dissipation through coal plastic deformation,and energy consumption due to coal failure.The energy release from the rock mass is influenced by several factors,including mining depth,stress concentration factor,the width of the plastic zone,and the rebound range of the roof and floor.Within the plastic zone of coal,the energy released per unit volume of coal and the induced kinetic energy exhibit a nonlinear increase with mining depth and stress concentration factor,while they decrease linearly as the width of the plastic zone increases.Similarly,the driving energy per unit volume of the roof and floor shows a nonlinear increase with mining depth and stress concentration factor,a linear increase with the rebound range of the roof and floor,and a linear decrease with the width of the plastic zone.A rock burst risk evaluation method is developed based on the kinetic energy model.Field observations demonstrate that this method aligns with the drilling cuttings rock burst risk assessment method,thereby confirming its validity.
基金Yunnan Fundamental Research Project,China(No.202201BE070001-056)。
文摘The volatilization characteristics and kinetic mechanisms of arsenic were investigated in the temperature range of 623−773 K and pressure ranges of 10−10000 Pa.The experimental results reveal that the evaporation rate increases with increasing temperature and decreasing pressure.Surface reaction control dominates at low pressures(<100 Pa),whereas diffusion control dominates at high pressures(>5000 Pa).The evaporation behavior is successfully described by an Arrhenius-type model for temperature dependence and Logistic model for pressure dependence.Key kinetic parameters,including the critical pressure,maximum evaporation rate and evaporation coefficient,were calculated.The evaporation coefficient varies between 0.010 and 0.223,and the critical pressures vary between 281 and 478 Pa with temperature.
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.
基金sponsored by the Major Science and Technology Special Plan“Unveiling and Leading”Project of Shanxi Province(No.202201050201011)Major Science and Technology Projects of Anhui Province(No.202210700037)Special Funding for Science and Technology of China Minmetals Corporation(No.2021ZXD01).
文摘Eggshells,a by-product of the food industry,represent a significant yet often overlooked waste stream.Given their vast production volume and inherent properties,eggshells have the potential to serve as a sustainable and environmentally friendly co-fuel.Aiming to explore the co-combustion characteristics and kinetics of pulverized coal blended with eggshells and offer insights into their combined use as a renewable energy source,a systematic investigation was conducted to evaluate the physical and chemical properties of Shangwan bituminous coal,Shouyang anthracite coal,eggshell(ES)and their blends.Additionally,comprehensive experimental analyses were performed at different heating rates applying a non-isothermal thermogravimetric method.The findings revealed that the addition of ES enhanced the combustion efficiency.The combustion characteristics were significantly influenced by the ES content,with an optimal blend ratio identified for maximum combustion efficiency.To represent the thermal degradation experiments,random pore model and volume model were employed.Furthermore,activation energies and pre-exponential factors were determined.The random pore model demonstrated more superior performance compared to the volume model.The activation energies of all the samples ranged between 18.29 and 42.48 kJ/mol,with the lowest value observed for the sample containing 20 mass%ES.
基金funded through Engineering and Physical Sciences Research Council(EPSRC)[grant numbers EP/W005131/1,EP/V042556/1].
文摘Recent work analysing magnesium hydrogenation using Reflecting Electron Energy Loss Spectroscopy(REELS)and Density Function Theory(DFT)has indicated interfacial polarisation and interstitial hydrogen clustering influence the reaction rate.The site availability model has been modified to include interstitial hydrogen clustering within the site availability factor and interface polarisation using interface treatment.The new model,SAM-CV-S,has demonstrated improved modelling of magnesium hydrogenation across wide operating conditions,such as temperatures from 330 to 400℃and pressures up to 40 bar.This wide applicability makes it a robust model that can be used to simulate bed performance in solid-state hydrogen stores.Thus,the site availability factor successfully combines interstitial hydrogen clustering with thermal resistance effects,which are known to strongly influence metal hydride reactor designs at scale.The next phase of the model is to incorporate a predictive hydrogen capacity method into the model.
基金support of Ningbo Fareast Tech Catalyst Engineering Co.,Ltd,the National Natural Science Foundation of China(22478275)Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering(2022SX-TD014).
文摘The removal of H_(2)S from coke oven gas (COG) is an important issue for the further utilization of COG. Zeolites could be used for industrial desulfurization owing to their high thermal stability and regenerability. However, further analysis on the kinetics of deep desulfurization using zeolites is necessary to provide relevant information for industrial design. In this study, the desulfurization breakthrough curves of faujasite (FAU) zeolite in COG were measured using a fixed bed reactor. The adsorption isotherm was investigated using the Langmuir, Freundlich, Temkin, Dubinin-Radushkevich models. The adsorption saturated capacity of H_(2)S was inversely related to the temperature. The results show that the Langmuir model best fits the adsorption isotherm with a lower value of root-mean-square-error (RMSE) and Chi-Square (χ^(2)), and the calculated activation energy is 14.62 kJ·mol^(−1). The adsorption kinetics were investigated using pseudo-first-order (PFO), pseudo-second-order (PSO), Bangham and Weber-Morris models. The Bangham model fitted the kinetic data well, indicating that pore diffusion is an influential factor in the adsorption process. The Weber-Morris model suggests that the adsorption rate was not solely determined by the pore diffusion, but was also influenced by the active site on the FAU zeolite. The adsorption breakthrough curves under different gas flow rates were fitted using the bed depth service time (BDST) model, and it provides an accurate prediction of the breakthrough time with a small relative error. The results of thermodynamic analysis demonstrated the feasibility and spontaneity (ΔG<0) and exothermic (ΔH<0) nature of the adsorption process of the FAU zeolite for H_(2)S under COG.
基金financially supported by the National Natural Science Foundation of China(No.52474355)the Liaoning Province Science and Technology Plan Joint Program(Key Research and Development Program Project,Nos.2022JH25/10200003 and 2023JH2/101800058)the Fundamental Research Funds for the Central Universities(Nos.N25YJS003 and N25DCG006)。
文摘The microstructural characteristics of austenite in Ti microalloyed steel during continuous casting significantly influence thethermoplasticity,thereby affecting the quality of the slab.In this work,a prediction model for two-stage austenite growth under varyingcooling rates was established by incorporating the effect of second-phase pinning and high-temperature ferrite-austenite phase transform-ation and growth theory.The results indicate that with 0.02wt%Ti,the high-temperature ferrite growth exhibits typical parabolic growthcharacteristics.When the Ti content increases to 0.04wt%,the high-temperature ferrite grain boundary migration rate significantly slowsduring the initial solidification stage.The predicted austenite grain sizes for 0.02wt%Ti microalloyed steel at the center,quarter,and sur-face of the slab are 5592,3529,and 1524μm,respectively.For 0.04wt%Ti microalloyed steel,the austenite grain sizes are 4074,2942,and 1179μm at the same positions.The average error is within 5%.As the Ti content increases from 0.02wt% to 0.04wt%,the austenitegrain refinement at the center is most significant,with an average grain size reduction of 27.14%.
基金supported by the National Natural Science Foundation of China(52071012)the National Natural Science Foundation of China(Grant No.52101119)+5 种基金the Open Foundation of State Key Laboratory for Advanced Metals and Materials(2022-Z01)the Open Research Fund of National Key Laboratory of Advanced Casting Technologies(CAT2023-004)the Key Research and Development Program of Shandong Province(2022JMRH0209)Hebei Province Innovation Capability Enhancement Plan Project(No.244A7607D)the Beijing Municipal Natural Science Foundation(No.2214072)Young Elite Scientist Sponsorship Program by CAST(No.2021QNRC001)。
文摘Process of dynamic recrystallization(DRX)plays a crucial role in altering the microstructure and enhancing the mechanical characteristics of CrNiMoVW steel.However,its initiation mechanism,deformation conditions,and predictive models remain insufficiently understood,requiring further research to optimize the processing technology.In the present study,hot compression experiments were carried out on 30CrNiMoVW steel under deformation conditions with temperatures ranging from 950 to 1,250℃and strain rates from 0.001 to 1 s~(-1),during which true stress-strain curves were obtained.Based on friction and temperature corrections applied to these curves,a constitutive equation for 30CrNiMoVW steel was established,and its accuracy was verified through fitting analysis.Simultaneously,the study identified limitations in the initial volume fraction model,prompting the development of a modified recrystallization volume fraction model that was validated via correlation analysis between experimental data and model predictions.Furthermore,building upon the modified recrystallization volume fraction model,a novel recrystallization rate model was developed,and three characteristic strain points were determined.These points segmented the rate curve into three stages:a slow initiation stage(0,ε1),a rapid growth stage(1,ε3),and a slow equilibrium stage(e3,0.9).Notably,the value ofε3 was considered the most economical,ensuring the formation of fine and uniform grains during production while optimizing the process,reducing energy consumption and costs,and enhancing overall material performance.Finally,based on the physical constitutive relationships and kinetic models,a multiscale simulation approach combining the finite element method(FEM)and cellular automata(CA)was employed to predict the microstructural evolution of 30CrNiMoVW steel.The simulation results demonstrate that the FEM&CA approach can accurately reproduce the dynamic recrystallization behavior and microstructural evolution observed experimentally.This work provides critical guidance for the development of forging processes for 30CrNiMoVW steel.
基金supported by the Research Program of the Science and Technology Department of Guizhou Province(Qiankehe Jichu[2019]1418)the Research Program of Talented Scholars of Guizhou Institute of Technology(XJGC20190965).
文摘In this context,the present study proposes the use of microwave irradiation to improve the dehydration rate and efficiency of strontium hydroxide octahydrate(Sr(OH)_(2)·8H_(2)O)without introducing contaminants.This study revealed that the use of microwave irradiation to dehydrate Sr(OH)_(2)·8H_(2)O is feasible and surprisingly efficient.The effects of this approach on important parameters were investigated using response surface methodology(RSM).The results revealed that the microwave dehydration process follows a linear polynomial model.In addition,compared with the heating time and material thickness,the microwave-assisted dehydration of Sr(OH)_(2)·8H_(2)O is sensitive to the microwave power and not to the material mass.The relative dehydration percentage reached 99.99%when heated in a microwave oven at 950Wfor just 3 min.In contrast,a relative dehydration percentage of 94.6%was reached when heated in an electric furnace at 180℃for 120 min.The XRD spectra also revealed that most of the Sr(OH)_(2)·8H_(2)O transformed into Sr(OH)_(2)after dehydration via microwave irradiation,whereas a significant portion of the Sr(OH)_(2)·H_(2)O remained after conventional electric dehydration.The experimental data were fitted and analyzed via the thin-layer drying dynamics model,and the results indicated that the dehydrating behavior of Sr(OH)_(2)·8H_(2)O could be well described by the Page model.
文摘Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLMs.Therefore,in order to better assess the capability of LLMs in the agricultural domain,Agri-Eval was proposed as a benchmark for assessing the knowledge and reasoning ability of LLMs in agriculture.The assessment dataset used in Agri-Eval covered seven major disciplines in the agricultural domain:crop science,horticulture,plant protection,animal husbandry,forest science,aquaculture science,and grass science,and contained a total of 2283 questions.Among domestic general-purpose LLMs,DeepSeek R1 performed best with an accuracy rate of 75.49%.In the realm of international general-purpose LLMs,Gemini 2.0 pro exp 0205 standed out as the top performer,achieving an accuracy rate of 74.28%.As an LLMs in agriculture vertical,Shennong V2.0 outperformed all the LLMs in China,and the answer accuracy rate of agricultural knowledge exceeded that of all the existing general-purpose LLMs.The launch of Agri-Eval helped the LLM developers to comprehensively evaluate the model's capability in the field of agriculture through a variety of tasks and tests to promote the development of the LLMs in the field of agriculture.
