The CO_(2)solubilities(including CO_(2)Henry’s constant)in physical-and chemical-based ILs/DESs and the COSMO-RS models describing these properties were comprehensively collected and summarized.The summarized results...The CO_(2)solubilities(including CO_(2)Henry’s constant)in physical-and chemical-based ILs/DESs and the COSMO-RS models describing these properties were comprehensively collected and summarized.The summarized results indicate that chemical-based ILs/DESs are superior to physical-based ILs/DESs for CO_(2)capture,especially those ILs have functionalized cation and anion,and superbase DESs;some of the superbase DESs have higher CO_(2)solubilities than those of ILs;the best physical-and chemical-based ILs,as well as physical-and chemicalbased DESs are[BMIM][BF4](4.20 mol kg^(-1)),[DETAH][Im](11.91 mol kg^(-1)),[L-Arg]-Gly 1:6(4.92 mol kg^(-1))and TBD-EG 1:4(12.90 mol kg^(-1)),respectively.Besides the original COSMO-RS mainly providing qualitative predictions,six corrected COSMO-RS models have been proposed to improve the prediction performance based on the experimental data,but only one model is with universal parameters.The newly determined experimental results were further used to verify the perditions of original and corrected COSMO-RS models.The comparison indicates that the original COSMO-RS qualitatively predicts CO_(2)solubility for some but not all ILs/DESs,while the quantitative prediction is incapable at all.The original COSMO-RS is capable to predict CO_(2)Henry’s constant qualitatively for both physical-based ILs and DESs,and quantitative prediction is only available for DESs.For the corrected COSMO-RS models,only the model with universal parameters provides quantitative predictions for CO_(2)solubility in physical-based DESs,while other corrected models always show large deviations(>83%)compared with the experimental CO_(2)Henry’s constants.展开更多
The application of carbon dioxide(CO_(2)) in enhanced oil recovery(EOR) has increased significantly, in which CO_(2) solubility in oil is a key parameter in predicting CO_(2) flooding performance. Hydrocarbons are the...The application of carbon dioxide(CO_(2)) in enhanced oil recovery(EOR) has increased significantly, in which CO_(2) solubility in oil is a key parameter in predicting CO_(2) flooding performance. Hydrocarbons are the major constituents of oil, thus the focus of this work lies in investigating the solubility of CO_(2) in hydrocarbons. However, current experimental measurements are time-consuming, and equations of state can be computationally complex. To address these challenges, we developed an artificial intelligence-based model to predict the solubility of CO_(2) in hydrocarbons under varying conditions of temperature, pressure, molecular weight, and density. Using experimental data from previous studies,we trained and predicted the solubility using four machine learning models: support vector regression(SVR), extreme gradient boosting(XGBoost), random forest(RF), and multilayer perceptron(MLP).Among four models, the XGBoost model has the best predictive performance, with an R^(2) of 0.9838.Additionally, sensitivity analysis and evaluation of the relative impacts of each input parameter indicate that the prediction of CO_(2) solubility in hydrocarbons is most sensitive to pressure. Furthermore, our trained model was compared with existing models, demonstrating higher accuracy and applicability of our model. The developed machine learning-based model provides a more efficient and accurate approach for predicting CO_(2) solubility in hydrocarbons, which may contribute to the advancement of CO_(2)-related applications in the petroleum industry.展开更多
This work presents the development of molecular-based mathematical model for the prediction of CO_(2) solubility in deep eutectic solvents(DESs).First,a comprehensive database containing 1011 CO_(2) solubility data in...This work presents the development of molecular-based mathematical model for the prediction of CO_(2) solubility in deep eutectic solvents(DESs).First,a comprehensive database containing 1011 CO_(2) solubility data in various DESs at different temperatures and pressures is established,and the COSMO-RS-derived descriptors of involved hydrogen bond acceptors and hydrogen bond donors of DESs are calculated.Afterwards,the efficiency of the input variables,i.e.,temperature,pressure,COSMO-RS-derived descriptors of HBA and HBD as well as their molar ratio,is explored by a qualitative analysis of CO_(2) solubility in DESs using a simple multiple linear regression model.A machine learning method namely random forest is then employed to develop more accurate nonlinear quantitative structure-property relationship(QSPR)model.Combining the QSPR validation and comparisons with literature-reported models(i.e.,COSMO-RS model,traditional thermodynamic models and equations of state methods),the developed QSPR model with COSMO-RS-derived parameters as molecular descriptors is suggested to be able to give reliable predictions of CO_(2) solubility in DESs and could be used as a useful tool in selecting DESs for CO_(2) capture processes.展开更多
Herein,the synthesis and characterization methods of natural deep eutectic solvents based on monoterpenoids have been presented.Low viscous fluids with suitable physicochemical properties are produced.The materials ar...Herein,the synthesis and characterization methods of natural deep eutectic solvents based on monoterpenoids have been presented.Low viscous fluids with suitable physicochemical properties are produced.The materials are non-toxic,biodegradable,and cost-effective.Thus,they can be used to develop sustainable solvents for various processes and can find their applications in various fields.A theoretical study based on quantum chemistry and classical molecular dynamics is used for the nanoscopic characterization of structure,dynamics,and hydrogen bonding.The reported results help analyze the properties of this new family of solvents.The required information for developing structure–property relationships for proper solvent design to form a sustainable chemistry framework is obtained.展开更多
Is it possible to improve CO_(2)solubility in potassium carbonate(K_(2)CO_(3))-based transition temperature mixtures(TTMs)?To assess this possibility,a ternary transition-temperature mixture(TTTM)was prepared by using...Is it possible to improve CO_(2)solubility in potassium carbonate(K_(2)CO_(3))-based transition temperature mixtures(TTMs)?To assess this possibility,a ternary transition-temperature mixture(TTTM)was prepared by using a hindered amine,2-amino-2-methyl-1,3-propanediol(AMPD).Fourier transform infrared spectroscopy(FT-IR)was employed to detect the functional groups including hydroxyl,amine,carbonate ion,and aliphatic functional groups in the prepared solvents.From thermogravimetric analysis(TGA),it was found that the addition of AMPD to the binary mixture can increase the thermal stability of TTTM.The viscosity findings showed that TTTM has a higher viscosity than TTM while their difference was decreased by increasing temperature.In addition,Eyring’s absolute rate theory was used to compute the activation parameters(∆G^(*),∆H^(*),and ∆S^(*)).The CO_(2)solubility in liquids was measured at a temperature of 303.15 K and pressures up to 1.8 MPa.The results disclosed that the CO_(2)solubility of TTTM was improved by the addition of AMPD.At the pressure of about 1.8 MPa,the CO_(2)mole fractions of TTM and TTTM were 0.1697 and 0.2022,respectively.To confirm the experimental data,density functional theory(DFT)was employed.From the DFT analysis,it was found that the TTTM+CO_(2)system has higher interaction energy(|∆E|)than the TTM+CO_(2)system indicating the higher CO_(2)affinity of the former system.This study might help scientists to better understand and to improve CO_(2)solubility in these types of solvents by choosing a suitable amine as HBD and finding the best combination of HBA and HBD.展开更多
To determine the solubility of CO_(2)in n-dodecane at T=303.15-353.15 K,P≤11.00 MPa,an integrated fused silica capillary and in-situ Raman spectroscopy system was built.The Raman peak intensity ratio(I_(CO_(2))/IC-H)...To determine the solubility of CO_(2)in n-dodecane at T=303.15-353.15 K,P≤11.00 MPa,an integrated fused silica capillary and in-situ Raman spectroscopy system was built.The Raman peak intensity ratio(I_(CO_(2))/IC-H)between the upper band of CO_(2)Fermi diad(I_(CO_(2)))and the C-H stretching band of n-dodecane(IC-H)was employed to determine the solubility of CO_(2)in n-dodecane based on the calibrated correlation equation between the known CO_(2)molality in n-dodecane and the I_(CO_(2))/IC-Hratio with R^(2)=0.9998.The results indicated that the solubility of CO_(2)decreased with increasing temperature and increased with increasing pressure.The maximum CO_(2)molality(30.7314 mol/kg)was obtained at 303.15 K and7.00 MPa.Finally,a solubility prediction model(lnS=(P-A)/B)based on the relationship with temperature(T in K)and pressure(P in MPa)was developed,where S is CO_(2)molality,A=-8×10^(-6)T^(2)+0.0354T-8.1605,and B=0.0405T-10.756.The results indicated that the solubilities of CO_(2)derived from this model were in good agreement with the experimental data.展开更多
基金financially supported by Carl Tryggers Stiftelse foundation(No.18:175)the financial support from the Swedish Energy Agency(P47500-1)+5 种基金K.C.Wang Education Foundation(No.GJTD-201804)the financial support from the National Natural Science Foundation of China(No.21890764)the financial supports from the National Natural Science Foundation of China(No.21838010)the financial support from the National Natural Science Foundation of China(No.21776276)the National Natural Science Foundation of China(21701024)the Foundation for Distinguished Young Talents in Higher Education of Fujian Province(GY-Z17067)
文摘The CO_(2)solubilities(including CO_(2)Henry’s constant)in physical-and chemical-based ILs/DESs and the COSMO-RS models describing these properties were comprehensively collected and summarized.The summarized results indicate that chemical-based ILs/DESs are superior to physical-based ILs/DESs for CO_(2)capture,especially those ILs have functionalized cation and anion,and superbase DESs;some of the superbase DESs have higher CO_(2)solubilities than those of ILs;the best physical-and chemical-based ILs,as well as physical-and chemicalbased DESs are[BMIM][BF4](4.20 mol kg^(-1)),[DETAH][Im](11.91 mol kg^(-1)),[L-Arg]-Gly 1:6(4.92 mol kg^(-1))and TBD-EG 1:4(12.90 mol kg^(-1)),respectively.Besides the original COSMO-RS mainly providing qualitative predictions,six corrected COSMO-RS models have been proposed to improve the prediction performance based on the experimental data,but only one model is with universal parameters.The newly determined experimental results were further used to verify the perditions of original and corrected COSMO-RS models.The comparison indicates that the original COSMO-RS qualitatively predicts CO_(2)solubility for some but not all ILs/DESs,while the quantitative prediction is incapable at all.The original COSMO-RS is capable to predict CO_(2)Henry’s constant qualitatively for both physical-based ILs and DESs,and quantitative prediction is only available for DESs.For the corrected COSMO-RS models,only the model with universal parameters provides quantitative predictions for CO_(2)solubility in physical-based DESs,while other corrected models always show large deviations(>83%)compared with the experimental CO_(2)Henry’s constants.
基金supported by the Fundamental Research Funds for the National Major Science and Technology Projects of China (No. 2017ZX05009-005)。
文摘The application of carbon dioxide(CO_(2)) in enhanced oil recovery(EOR) has increased significantly, in which CO_(2) solubility in oil is a key parameter in predicting CO_(2) flooding performance. Hydrocarbons are the major constituents of oil, thus the focus of this work lies in investigating the solubility of CO_(2) in hydrocarbons. However, current experimental measurements are time-consuming, and equations of state can be computationally complex. To address these challenges, we developed an artificial intelligence-based model to predict the solubility of CO_(2) in hydrocarbons under varying conditions of temperature, pressure, molecular weight, and density. Using experimental data from previous studies,we trained and predicted the solubility using four machine learning models: support vector regression(SVR), extreme gradient boosting(XGBoost), random forest(RF), and multilayer perceptron(MLP).Among four models, the XGBoost model has the best predictive performance, with an R^(2) of 0.9838.Additionally, sensitivity analysis and evaluation of the relative impacts of each input parameter indicate that the prediction of CO_(2) solubility in hydrocarbons is most sensitive to pressure. Furthermore, our trained model was compared with existing models, demonstrating higher accuracy and applicability of our model. The developed machine learning-based model provides a more efficient and accurate approach for predicting CO_(2) solubility in hydrocarbons, which may contribute to the advancement of CO_(2)-related applications in the petroleum industry.
基金support from National Natural Science Foundation of China(21861132019,21776074)is greatly acknowledged.
文摘This work presents the development of molecular-based mathematical model for the prediction of CO_(2) solubility in deep eutectic solvents(DESs).First,a comprehensive database containing 1011 CO_(2) solubility data in various DESs at different temperatures and pressures is established,and the COSMO-RS-derived descriptors of involved hydrogen bond acceptors and hydrogen bond donors of DESs are calculated.Afterwards,the efficiency of the input variables,i.e.,temperature,pressure,COSMO-RS-derived descriptors of HBA and HBD as well as their molar ratio,is explored by a qualitative analysis of CO_(2) solubility in DESs using a simple multiple linear regression model.A machine learning method namely random forest is then employed to develop more accurate nonlinear quantitative structure-property relationship(QSPR)model.Combining the QSPR validation and comparisons with literature-reported models(i.e.,COSMO-RS model,traditional thermodynamic models and equations of state methods),the developed QSPR model with COSMO-RS-derived parameters as molecular descriptors is suggested to be able to give reliable predictions of CO_(2) solubility in DESs and could be used as a useful tool in selecting DESs for CO_(2) capture processes.
基金funded by the Junta de Castilla y Leon(Spain,project NANOCOMP-BU058P20)the Ministerio de Ciencia,Innovación y Universidades(Spain,project RTI2018–101987-B-I00)。
文摘Herein,the synthesis and characterization methods of natural deep eutectic solvents based on monoterpenoids have been presented.Low viscous fluids with suitable physicochemical properties are produced.The materials are non-toxic,biodegradable,and cost-effective.Thus,they can be used to develop sustainable solvents for various processes and can find their applications in various fields.A theoretical study based on quantum chemistry and classical molecular dynamics is used for the nanoscopic characterization of structure,dynamics,and hydrogen bonding.The reported results help analyze the properties of this new family of solvents.The required information for developing structure–property relationships for proper solvent design to form a sustainable chemistry framework is obtained.
基金support of National Key Research and Development Program of China(Grant No.2019YFC1904602)the Key SCI-Tech Innovation 2025 Program of Ningbo,China(Grant No.2018B10025).
文摘Is it possible to improve CO_(2)solubility in potassium carbonate(K_(2)CO_(3))-based transition temperature mixtures(TTMs)?To assess this possibility,a ternary transition-temperature mixture(TTTM)was prepared by using a hindered amine,2-amino-2-methyl-1,3-propanediol(AMPD).Fourier transform infrared spectroscopy(FT-IR)was employed to detect the functional groups including hydroxyl,amine,carbonate ion,and aliphatic functional groups in the prepared solvents.From thermogravimetric analysis(TGA),it was found that the addition of AMPD to the binary mixture can increase the thermal stability of TTTM.The viscosity findings showed that TTTM has a higher viscosity than TTM while their difference was decreased by increasing temperature.In addition,Eyring’s absolute rate theory was used to compute the activation parameters(∆G^(*),∆H^(*),and ∆S^(*)).The CO_(2)solubility in liquids was measured at a temperature of 303.15 K and pressures up to 1.8 MPa.The results disclosed that the CO_(2)solubility of TTTM was improved by the addition of AMPD.At the pressure of about 1.8 MPa,the CO_(2)mole fractions of TTM and TTTM were 0.1697 and 0.2022,respectively.To confirm the experimental data,density functional theory(DFT)was employed.From the DFT analysis,it was found that the TTTM+CO_(2)system has higher interaction energy(|∆E|)than the TTM+CO_(2)system indicating the higher CO_(2)affinity of the former system.This study might help scientists to better understand and to improve CO_(2)solubility in these types of solvents by choosing a suitable amine as HBD and finding the best combination of HBA and HBD.
基金supported by the National Key Research and Development Program of China(2019YFE0117200)the Natural Science Foundation of China(41977304)
文摘To determine the solubility of CO_(2)in n-dodecane at T=303.15-353.15 K,P≤11.00 MPa,an integrated fused silica capillary and in-situ Raman spectroscopy system was built.The Raman peak intensity ratio(I_(CO_(2))/IC-H)between the upper band of CO_(2)Fermi diad(I_(CO_(2)))and the C-H stretching band of n-dodecane(IC-H)was employed to determine the solubility of CO_(2)in n-dodecane based on the calibrated correlation equation between the known CO_(2)molality in n-dodecane and the I_(CO_(2))/IC-Hratio with R^(2)=0.9998.The results indicated that the solubility of CO_(2)decreased with increasing temperature and increased with increasing pressure.The maximum CO_(2)molality(30.7314 mol/kg)was obtained at 303.15 K and7.00 MPa.Finally,a solubility prediction model(lnS=(P-A)/B)based on the relationship with temperature(T in K)and pressure(P in MPa)was developed,where S is CO_(2)molality,A=-8×10^(-6)T^(2)+0.0354T-8.1605,and B=0.0405T-10.756.The results indicated that the solubilities of CO_(2)derived from this model were in good agreement with the experimental data.
