Recovering the iron(Fe)and phosphorus(P)contained in steelmaking slags not only reduces the environmental burden caused by the accumulated slag,but also is the way to develop a circular economy and achieve sustainable...Recovering the iron(Fe)and phosphorus(P)contained in steelmaking slags not only reduces the environmental burden caused by the accumulated slag,but also is the way to develop a circular economy and achieve sustainable development in the steel industry.We had pre-viously found the possibility of recovering Fe and P resources,i.e.,magnetite(Fe_(3)O_(4)) and calcium phosphate(Ca_(10)P_(6)O_(25)),contained in steel-making slags by adjusting oxygen partial pressure and adding modifier B_(2)O_(3).As a fundamental study for efficiently recovering Fe and P from steelmaking slag,in this study,the crystallization behavior of the CaO-SiO_(2)-FeO-P_(2)O_(5)-B_(2)O_(3) melt has been observed in situ,using a confocal scanning laser microscope(CLSM).The kinetics of nucleation and growth of Fe-and P-rich phases have been calculated using a classical crys-tallization kinetic theory.During cooling,a Fe_(3)O_(4) phase with faceted morphology was observed as the 1st precipitated phase in the isothermal interval of 1300-1150℃,while Ca_(10)P_(6)O_(25),with rod-shaped morphology,was found to be the 2nd phase to precipitate in the interval of 1150-1000℃.The crystallization abilities of Fe_(3)O_(4) and Ca_(10)P_(6)O_(25) phases in the CaO-SiO_(2)-FeO-P_(2)O_(5)-B_(2)O_(3) melt were quantified with the in-dex of(T_(U)−T_(I))/T_(I)(where T_(I) represents the peak temperature of the nucleation rate and TU stands for that of growth rate),and the crystalliza-tion ability of Fe_(3)O_(4) was found to be larger than that of Ca_(10)P_(6)O_(25) phase.The range of crystallization temperature for Fe_(3)O_(4) and Ca_(10)P_(6)O_(25) phases was optimized subsequently.The Fe_(3)O_(4) and Ca_(10)P_(6)O_(25) phases are the potential sources for ferrous feedstock and phosphate fertilizer,respectively.展开更多
Diesel molecular compositional model has important application for diesel quality prediction,blending,and molecular-level process model development.In this paper,different types of diesel molecular compositional and b...Diesel molecular compositional model has important application for diesel quality prediction,blending,and molecular-level process model development.In this paper,different types of diesel molecular compositional and blending models were constructed based on the SU-BEM framework.More than 1500 representative molecules were selected to form the molecular structure library.The probability density functions(PDFs)combination was determined by experimental data and experience.A quadratic optimization strategy combining genetic algorithm with local optimization algorithm was adopted to improve the accuracy of the compositional model.The model results show good agreement with the experimental data.The diesel blending model was constructed at the molecular-level based on the above diesel compositional models.The properties of the blending model accord with the experimental regulations.It is proved that the compositional models and blending model constructed have high accuracy and strong prediction capability,and are applicable to the industrial process.展开更多
In this work,a molecular-level kinetic model was built to simulate the vacuum residue(VR)coking process in a semi-batch laboratory-scale reaction kettle.A series of reaction rules for heavy oil coking were summarized ...In this work,a molecular-level kinetic model was built to simulate the vacuum residue(VR)coking process in a semi-batch laboratory-scale reaction kettle.A series of reaction rules for heavy oil coking were summarized and formulated based on the free radical reaction mechanism.Then,a large-scale molecularlevel reaction network was automatically generated by applying the reaction rules on the vacuum residue molecules.In order to accurately describe the physical change of each molecule in the reactor,we coupled the molecular-level kinetic model with a vapor–liquid phase separation model.The vapor–liquid phase separation model adopted the Peng-Robinson equation of state to calculate vapor–liquid equilibrium.A separation efficiency coefficient was introduced to represent the mass transfer during the phase separation.We used six sets of experimental data under various reaction conditions to regress the model parameters.The tuned model showed that there was an excellent agreement between the calculated values and experimental data.Moreover,we investigated the effect of reaction temperature and reaction time on the product yields.After a comprehensive evaluation of the reaction temperature and reaction time,the optimal reaction condition for the vacuum residue coking was also obtained.展开更多
基金supported by Jiangsu University(No.19JDG011)the Project of the National Natural Science Foundation of China(Nos.51874272,52111540265)the Open Foundation of State Key Laboratory of Mineral Processing(No.BGRIMM-KJSKL-2022-23).
文摘Recovering the iron(Fe)and phosphorus(P)contained in steelmaking slags not only reduces the environmental burden caused by the accumulated slag,but also is the way to develop a circular economy and achieve sustainable development in the steel industry.We had pre-viously found the possibility of recovering Fe and P resources,i.e.,magnetite(Fe_(3)O_(4)) and calcium phosphate(Ca_(10)P_(6)O_(25)),contained in steel-making slags by adjusting oxygen partial pressure and adding modifier B_(2)O_(3).As a fundamental study for efficiently recovering Fe and P from steelmaking slag,in this study,the crystallization behavior of the CaO-SiO_(2)-FeO-P_(2)O_(5)-B_(2)O_(3) melt has been observed in situ,using a confocal scanning laser microscope(CLSM).The kinetics of nucleation and growth of Fe-and P-rich phases have been calculated using a classical crys-tallization kinetic theory.During cooling,a Fe_(3)O_(4) phase with faceted morphology was observed as the 1st precipitated phase in the isothermal interval of 1300-1150℃,while Ca_(10)P_(6)O_(25),with rod-shaped morphology,was found to be the 2nd phase to precipitate in the interval of 1150-1000℃.The crystallization abilities of Fe_(3)O_(4) and Ca_(10)P_(6)O_(25) phases in the CaO-SiO_(2)-FeO-P_(2)O_(5)-B_(2)O_(3) melt were quantified with the in-dex of(T_(U)−T_(I))/T_(I)(where T_(I) represents the peak temperature of the nucleation rate and TU stands for that of growth rate),and the crystalliza-tion ability of Fe_(3)O_(4) was found to be larger than that of Ca_(10)P_(6)O_(25) phase.The range of crystallization temperature for Fe_(3)O_(4) and Ca_(10)P_(6)O_(25) phases was optimized subsequently.The Fe_(3)O_(4) and Ca_(10)P_(6)O_(25) phases are the potential sources for ferrous feedstock and phosphate fertilizer,respectively.
基金supported by the SINOPEC R&D Program(grant number 119014-1)
文摘Diesel molecular compositional model has important application for diesel quality prediction,blending,and molecular-level process model development.In this paper,different types of diesel molecular compositional and blending models were constructed based on the SU-BEM framework.More than 1500 representative molecules were selected to form the molecular structure library.The probability density functions(PDFs)combination was determined by experimental data and experience.A quadratic optimization strategy combining genetic algorithm with local optimization algorithm was adopted to improve the accuracy of the compositional model.The model results show good agreement with the experimental data.The diesel blending model was constructed at the molecular-level based on the above diesel compositional models.The properties of the blending model accord with the experimental regulations.It is proved that the compositional models and blending model constructed have high accuracy and strong prediction capability,and are applicable to the industrial process.
基金supported by the National Natural Science Foun-dation of China(22021004 and U19B2002).
文摘In this work,a molecular-level kinetic model was built to simulate the vacuum residue(VR)coking process in a semi-batch laboratory-scale reaction kettle.A series of reaction rules for heavy oil coking were summarized and formulated based on the free radical reaction mechanism.Then,a large-scale molecularlevel reaction network was automatically generated by applying the reaction rules on the vacuum residue molecules.In order to accurately describe the physical change of each molecule in the reactor,we coupled the molecular-level kinetic model with a vapor–liquid phase separation model.The vapor–liquid phase separation model adopted the Peng-Robinson equation of state to calculate vapor–liquid equilibrium.A separation efficiency coefficient was introduced to represent the mass transfer during the phase separation.We used six sets of experimental data under various reaction conditions to regress the model parameters.The tuned model showed that there was an excellent agreement between the calculated values and experimental data.Moreover,we investigated the effect of reaction temperature and reaction time on the product yields.After a comprehensive evaluation of the reaction temperature and reaction time,the optimal reaction condition for the vacuum residue coking was also obtained.
