Using a dynamic laser monitoring technique,the solubility of 3-nitro-1,2,4-triazole-5-one(NTO)was investigated in two different binary systems,namely hydroxylamine nitrate(HAN)-water and boric acid(HB)-water ranging f...Using a dynamic laser monitoring technique,the solubility of 3-nitro-1,2,4-triazole-5-one(NTO)was investigated in two different binary systems,namely hydroxylamine nitrate(HAN)-water and boric acid(HB)-water ranging from 278.15 K to 318.15 K.The solubility in each system was found to be positively correlated with temperature.Furthermore,solubility data were analyzed using four equations:the modified Apelblat equation,Van’t Hoff equation,λh equation and CNIBS/R-K equations,and they provided satisfactory results for both two systems.The average root-mean-square deviation(105RMSD)values for these models were less than 13.93.Calculations utilizing the Van’t Hoff equation and Gibbs equations facilitated the derivation of apparent thermodynamic properties of NTO dissolution in the two systems,including values for Gibbs free energy,enthalpy and entropy.The%ζ_(H)is larger than%ζ_(TS),and all the%ζ_(H)data are≥58.63%,indicating that the enthalpy make a greater contribution than entropy to theΔG_(soln)^(Θ).展开更多
Pharmaceutical pollution is becoming an increasing threat to aquatic environments since inactive compounds do not break down,and the drug products are accumulated in living organisms.The ability of a drug to dissolve ...Pharmaceutical pollution is becoming an increasing threat to aquatic environments since inactive compounds do not break down,and the drug products are accumulated in living organisms.The ability of a drug to dissolve in water(i.e.,LogS)is an important parameter for assessing a drug’s environmental fate,biovailability,and toxicity.LogS is typically measured in a laboratory setting,which can be costly and time-consuming,and does not provide the opportunity to conduct large-scale analyses.This research develops and evaluates machine learning models that can produce LogS estimates and may improve the environmental risk assessments of toxic pharmaceutical pollutants.We used a dataset from the ChEMBL database that contained 8832 molecular compounds.Various data preprocessing and cleaning techniques were applied(i.e.,removing the missing values),we then recorded chemical properties by normalizing and,even,using some feature selection techniques.We evaluated logS with a total of several machine learning and deep learning models,including;linear regression,random forests(RF),support vector machines(SVM),gradient boosting(GBM),and artificial neural networks(ANNs).We assessed model performance using a series of metrics,including root mean square error(RMSE)and mean absolute error(MAE),as well as the coefficient of determination(R^(2)).The findings show that the Least Angle Regression(LAR)model performed the best with an R^(2) value close to 1.0000,confirming high predictive accuracy.The OMP model performed well with good accuracy(R^(2)=0.8727)while remaining computationally cheap,while other models(e.g.,neural networks,random forests)performed well but were too computationally expensive.Finally,to assess the robustness of the results,an error analysis indicated that residuals were evenly distributed around zero,confirming the results from the LAR model.The current research illustrates the potential of AI in anticipating drug solubility,providing support for green pharmaceutical design and environmental risk assessment.Future work should extend predictions to include degradation and toxicity to enhance predictive power and applicability.展开更多
In order to increase the solubility of pyrroloquinoline quinone disodium salt(PQQ-NA_(2))in water,PQQ-NA_(2)ionic salts formed by PQQ-NA_(2)with amine compounds had been developed.Amine compounds specifically refered ...In order to increase the solubility of pyrroloquinoline quinone disodium salt(PQQ-NA_(2))in water,PQQ-NA_(2)ionic salts formed by PQQ-NA_(2)with amine compounds had been developed.Amine compounds specifically refered to aminomethyl propanol,tromethamine,and matrine.The PQQ-NA_(2)ionic salts solubility test result showed an increase as high as 24-fold compared to dissolving PQQ-NA_(2)alone.The antioxidant test indicated that the ionic salts exhibited significant antioxidant property.Two PQQ-NA_(2)gel formulations were prepared containing the ionic salts,and the stability test and PQQ-NA_(2)content test indicated that the formulations were stable and the loss rate of PQQ was below 10%.展开更多
Understanding the solubility of supercritical CO_(2)and its mixtures with other fluids at various temperatures and pressures conditions is critical for their applications,such as extraction processes,material design,a...Understanding the solubility of supercritical CO_(2)and its mixtures with other fluids at various temperatures and pressures conditions is critical for their applications,such as extraction processes,material design,and carbon capture.In the present study,the solubility parameters of supercritical CO_(2),H_(2)O,and their mixtures were calculated by molecular dynamics simulations.The results show that the solubility parameters decrease with increasing temperature and increase with increasing pressure and are linearly proportional to the density.Furthermore,the intermolecular interactions,including the hydrogen bonds,significantly affect the solubility parameter of the CO_(2)-H_(2)O system.展开更多
Li-S batteries are regarded as one of the most promising candidates for next-generation battery systems with high energy density and low cost.However,the dissolution-precipitation reaction mechanism of the sulfur(S)ca...Li-S batteries are regarded as one of the most promising candidates for next-generation battery systems with high energy density and low cost.However,the dissolution-precipitation reaction mechanism of the sulfur(S)cathode enhances the kinetics of the redox processes of the insulating sulfu r,which also arouses the notorious shuttle effect,leading to serious loss of S species and corrosion of Li anode.To get a balance between the shuttle restraining and the kinetic property,a combined strategy of electrolyte regulation and cathode modification is proposed via introducing 1,1,2,2-tetrafluoroethyl-2,2,3,3-tetrafluoroprpyl ether(HFE)instead of 1,2-dimethoxyethane(DME),and SeS_(7)instead of S_8.The introduction of HFE tunes the solvation structure of the LiTFSI and the dissolution of intermediate polysulfides with Se doping(LiPSSes),and optimize the interface stability of the Li anode simultaneously.The minor Se substitution compensates the decrease in kinetic due to the decreased solubility of LiPSs.In this way,the Li-SeS_(7)batteries deliver a reversible capacity of 1062 and 1037 mAh g^(-1)with 2.0 and 5.5 mg SeS_(7)cm^(-2)loading condition,respectively.Besides,an electrolyte-electrode loading model is established to explain the relationship between the optimal electrolyte and cathode loading.It makes more sense to guide the electrolyte design for practical Li-S batteries.展开更多
The cyclic hydrogenation technology in a direct coal liquefaction process relies on the dissolved hydrogen of the solvent or oil participating in the hydrogenation reaction.Thus,a theoretical basis for process optimiz...The cyclic hydrogenation technology in a direct coal liquefaction process relies on the dissolved hydrogen of the solvent or oil participating in the hydrogenation reaction.Thus,a theoretical basis for process optimization and reactor design can be established by analyzing the solubility of hydrogen in liquefaction solvents.Experimental studies of hydrogen solubility in liquefaction solvents are challenging due to harsh reaction conditions and complex solvent compositions.In this study,the composition and content of liquefied solvents were analyzed.As model compounds,hexadecane,toluene,naphthalene,tetrahydronaphthalene,and phenanthrene were chosen to represent the liquefied solvents in chain alkanes and monocyclic,bicyclic,and tricyclic aromatic hydrocarbons.The solubility of hydrogen X(mol/mol)in pure solvent components and mixed solvents(alkanes and aromatics mixed in proportion to the chain alkanes+bicyclic aromatic hydrocarbons,bicyclic saturated aromatic hydrocarbons+bicyclic aromatic hydrocarbons,and bicyclic aromatic hydrocarbons+compounds containing het-eroatoms composed of mixed components)are determined using Aspen simulation at temperature and pressure conditions of 373–523 K and 2–10 MPa.The results demonstrated that at high temperatures and pressures,the solubility of hydrogen in the solvent increases with the increase in temperature and pressure,with the pressure having a greater impact.Further-more,the results revealed that hydrogen is more soluble in straight-chain alkanes than in other solvents,and the solubility of eicosanoids reaches a maximum of 0.296.The hydrogen solubility in aromatic ring compounds decreased gradually with an increase in the aromatic ring number.The influence of chain alkanes on the solubility of hydrogen predominates in a mixture of solvents with different mixing ratios of chain alkanes and aromatic hydrocarbons.The solubility of hydrogen in mixed aromatic solvents is less than that in the corresponding single solvents.Hydrogen is less soluble in solvent compounds containing heteroatoms than in compounds without heteroatoms.展开更多
The equilibrium solubility of Rebaudioside A(Reb A)FormⅡin binary mixtures of methanol/ethanol and ethyl acetate was quantitatively determined within the temperature range of 283.15—328.15 K at ambient pressure.The ...The equilibrium solubility of Rebaudioside A(Reb A)FormⅡin binary mixtures of methanol/ethanol and ethyl acetate was quantitatively determined within the temperature range of 283.15—328.15 K at ambient pressure.The experimental findings indicate a positive correlation between the solubility of Reb A(FormⅡ)and both the temperature and the methanol/ethanol content in the solvent system.To describe the solubility data,six distinct models were employed:the modified Apelblat equation,theλh model,the combined nearly ideal binary solvent/Redlich—Kister(CNIBS/R—K)model,the van't HoffJouyban-Acree(VJA)model,the Apelblat-Jouyban-Acree(AJA)model,and the non-random two-liquid(NRTL)model.The combined nearly ideal binary solvent/Redlich—Kister model exhibited the most precise fit for solubility in methanol+ethyl acetate mixtures,reflected by an average relative deviation(ARD)of 0.0011 and a root mean square deviation(RMSD)of 12×10^(-7).Conversely,for ethanol+ethyl acetate mixtures,the modified Apelblat equation provided a superior correlation(ARD=0.0014,RMSD=4×10^(-7)).Furthermore,thermodynamic parameters associated with the dissolution of Reb A(FormⅡ),including enthalpy,entropy,and the Gibbs energy change,were inferred from the data.The findings underscore that the dissolution process is predominantly endothermic across the solvent systems examined.Notably,the entropy changes appear to have a significant influence on the Gibbs free energy associated with the dissolution of Reb A(FormⅡ),suggesting that entropic factors may play a pivotal role in the studied systems.展开更多
In order to remove hexahydro-1,3,5-trinitro-1,3,5-triazine(RDX),the main impurity,in process of polymorphic transformation of octrahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine(HMX),the solubility ofβ-HMX and RDX in a...In order to remove hexahydro-1,3,5-trinitro-1,3,5-triazine(RDX),the main impurity,in process of polymorphic transformation of octrahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine(HMX),the solubility ofβ-HMX and RDX in acetonitrile(ACN)+water in the temperature range of 288.15-333.15 K and in nitric acid(HNO_(3))+water in the temperature range of 298.15-333.15 K were measured by laser dynamic method.The results showed that the solubility of bothβ-HMX and RDX in binary mixed solvents increased monotonously as the temperature increase at a given solvent composition or with increasing of mole fraction of solvent(ACN and nitric acid).Solubility data were well correlated by the modified Apelblat equation,Jouyban-Acree model,Yaws equation and van't Hoff equation,and the Yaws equation achieved the best fitting results according to the relative error and the mean square error root.Furthermore,the solubility ofβ-HMX and RDX in binary mixed solvent was compared,based on the solubility difference and the solvent's own properties,the best separation degree ofβ-HMX and RDX was found when the mole fraction of nitric acid was 0.22 at room temperature,which provided data support for HMX crystallization in mixed solvent.The solubility differences between RDX andβ-HMX in mixed solvents were explained from the formation of intermolecular and intramolecular hydrogen bonds.展开更多
Hydraulic fracturing is an effective technology for hydrocarbon extraction from unconventional shale and tight gas reservoirs.A potential risk of hydraulic fracturing is the upward migration of stray gas from the deep...Hydraulic fracturing is an effective technology for hydrocarbon extraction from unconventional shale and tight gas reservoirs.A potential risk of hydraulic fracturing is the upward migration of stray gas from the deep subsurface to shallow aquifers.The stray gas can dissolve in groundwater leading to chemical and biological reactions,which could negatively affect groundwater quality and contribute to atmospheric emissions.The knowledge oflight hydrocarbon solubility in the aqueous environment is essential for the numerical modelling offlow and transport in the subsurface.Herein,we compiled a database containing 2129experimental data of methane,ethane,and propane solubility in pure water and various electrolyte solutions over wide ranges of operating temperature and pressure.Two machine learning algorithms,namely regression tree(RT)and boosted regression tree(BRT)tuned with a Bayesian optimization algorithm(BO)were employed to determine the solubility of gases.The predictions were compared with the experimental data as well as four well-established thermodynamic models.Our analysis shows that the BRT-BO is sufficiently accurate,and the predicted values agree well with those obtained from the thermodynamic models.The coefficient of determination(R2)between experimental and predicted values is 0.99 and the mean squared error(MSE)is 9.97×10^(-8).The leverage statistical approach further confirmed the validity of the model developed.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
Studying the relationship between ionic interactions and salt solubility in seawater has implications for seawater desalination and mineral extraction.In this paper,a new method of expressing ion-to-ion interaction is...Studying the relationship between ionic interactions and salt solubility in seawater has implications for seawater desalination and mineral extraction.In this paper,a new method of expressing ion-to-ion interaction is proposed by using molecular dynamics simulation,and the relationship between ion-to-ion interaction and salt solubility in a simulated seawater water-salt system is investigated.By analyzing the variation of distance and contact time between ions in an electrolyte solution,from both spatial and temporal perspectives,new parameters were proposed to describe the interaction between ions:interaction distance(ID),and interaction time ratio(ITR).The best correlation between characteristic time ratio and solubility was found for a molar ratio of salt-to-water of 10:100 with a correlation coefficient of 0.96.For the same salt,a positive correlation was found between CTR and the molar ratio of salt and water.For type 1-1,type 2-1,type 1-2,and type 2-2 salts,the correlation coefficients between CTR and solubility were 0.93,0.96,0.92,and 0.98 for a salt-to-water molar ratio of 10:100,respectively.The solubility of multiple salts was predicted by simulations and compared with experimental values,yielding an average relative deviation of 12.4%.The new ion-interaction parameters offer significant advantages in describing strongly correlated and strongly hydrated electrolyte solutions.展开更多
As a common precursor for supercritical CO_(2)(scCO_(2))deposition techniques,solubility data of organometallic complexes in scCO_(2)is crucial for the preparation of nanocomposites.Recently,metal acetylacetonates hav...As a common precursor for supercritical CO_(2)(scCO_(2))deposition techniques,solubility data of organometallic complexes in scCO_(2)is crucial for the preparation of nanocomposites.Recently,metal acetylacetonates have shown great potential for the preparation of single-atom catalytic materials.In this study,the solubilities of iron(Ⅲ)acetylacetonate(Fe(acac)3)and nickel(Ⅱ)acetylacetonate(Ni(acac)2)were measured at the temperature from 313.15 to 333.15 K and in the pressure range of 9.5–25.2 MPa to accumulate new solubility data.Solubility was measured using a static weight loss method.The semi-empirical models proposed by Chrastil and Sung et al.were used to correlate the solubility data of Fe(acac)3 and Ni(acac)2.The equations obtained can be used to predict the solubility of the same system in the experimental range.展开更多
The successful deployment of thermoelectric materials necessitates the concurrent development of highperformance p-type and n-type pairs situated within an identical matrix.Nevertheless,limiting by the low dopant solu...The successful deployment of thermoelectric materials necessitates the concurrent development of highperformance p-type and n-type pairs situated within an identical matrix.Nevertheless,limiting by the low dopant solubility,the conventional doping often cannot transfer the Fermi level to the opposite carrier type.Here,the solubility limit of donor dopants was enhanced to achieve n-type GeSe by inducing additional cationic vacancies through raising crystal symmetry.Converting the intrinsic p-type nature of GeSe to n-type poses significant challenges,primarily due to the exceedingly low dopant solubility within its native orthorhombic structure.To overcome this,the In_(2)Te_(3)alloying was initially employed to transition GeSe from orthorhombic to rhombohedral structure,simultaneously generating a large number of Ge vacancies.Following this,the introduction of Pb acts to mitigate the excessive Ge vacancies,steering the material toward a weak p-type character.Crucially,the elevated Ge vacancy concentration serves to extend the solubility limit of Bi donor dopant,which not only promotes the formation of cubic phase,but also enables the p-n type transition.As a result,a peak zT of 0.18 at 773 K was attained for the n-type cubic Ge_(0.55)Bi_(0.2)Pb_(0.2)5Se(In_(2)Te_(3))_(0.1),marking an 18-fold enhancement in comparison with its n-type orthorhombic counterpart.This work attests to the efficacy of introducing vacancies through enhancing crystal symmetry as an effective means to expand dopant solubility,thereby offering valuable insights into the achievement of compatible p-and n-type chalcogenides within the same matrix.展开更多
Short Retraction NoticeThis article has been retracted to straighten the academic record. In making this decision the Editorial Board follows COPE's Retraction Guidelines. The aim is to promote the circulation of ...Short Retraction NoticeThis article has been retracted to straighten the academic record. In making this decision the Editorial Board follows COPE's Retraction Guidelines. The aim is to promote the circulation of scientific research by offering an ideal research publication platform with due consideration of internationally accepted standards on publication ethics. The Editorial Board would like to extend its sincere apologies for any inconvenience this retraction may have caused. The full retraction notice in PDF is preceding the original paper, which is marked "RETRACTED".展开更多
Kaempferol(KA),as one of the flavonoids,has extensive pharmacological properties.However,the poor solubility of KA severely limits its clinical application.In our study,the kaempferol phospholipid complex(KA-PC)has be...Kaempferol(KA),as one of the flavonoids,has extensive pharmacological properties.However,the poor solubility of KA severely limits its clinical application.In our study,the kaempferol phospholipid complex(KA-PC)has been prepared by solvent evaporation for the enhancement of the bioavailability of KA.KA-PC was verified by scanning electron microscope characterization methods.Drug loading,solubility and long-term stability were measured.The characterization results showed that KA-PC was formed through the intermolecular interaction between KA and phospholipids.The solubility of KA-PC in water was 189 times higher than that of KA,and the solubility in n-octanol was also significantly improved.Besides,pharmacodynamic studies showed that KA-PC can significantly reduce the level of serum uric acid in mice without causing renal injury.This study expanded the clinical application of KA by preparing KA-PC.展开更多
文摘Using a dynamic laser monitoring technique,the solubility of 3-nitro-1,2,4-triazole-5-one(NTO)was investigated in two different binary systems,namely hydroxylamine nitrate(HAN)-water and boric acid(HB)-water ranging from 278.15 K to 318.15 K.The solubility in each system was found to be positively correlated with temperature.Furthermore,solubility data were analyzed using four equations:the modified Apelblat equation,Van’t Hoff equation,λh equation and CNIBS/R-K equations,and they provided satisfactory results for both two systems.The average root-mean-square deviation(105RMSD)values for these models were less than 13.93.Calculations utilizing the Van’t Hoff equation and Gibbs equations facilitated the derivation of apparent thermodynamic properties of NTO dissolution in the two systems,including values for Gibbs free energy,enthalpy and entropy.The%ζ_(H)is larger than%ζ_(TS),and all the%ζ_(H)data are≥58.63%,indicating that the enthalpy make a greater contribution than entropy to theΔG_(soln)^(Θ).
文摘Pharmaceutical pollution is becoming an increasing threat to aquatic environments since inactive compounds do not break down,and the drug products are accumulated in living organisms.The ability of a drug to dissolve in water(i.e.,LogS)is an important parameter for assessing a drug’s environmental fate,biovailability,and toxicity.LogS is typically measured in a laboratory setting,which can be costly and time-consuming,and does not provide the opportunity to conduct large-scale analyses.This research develops and evaluates machine learning models that can produce LogS estimates and may improve the environmental risk assessments of toxic pharmaceutical pollutants.We used a dataset from the ChEMBL database that contained 8832 molecular compounds.Various data preprocessing and cleaning techniques were applied(i.e.,removing the missing values),we then recorded chemical properties by normalizing and,even,using some feature selection techniques.We evaluated logS with a total of several machine learning and deep learning models,including;linear regression,random forests(RF),support vector machines(SVM),gradient boosting(GBM),and artificial neural networks(ANNs).We assessed model performance using a series of metrics,including root mean square error(RMSE)and mean absolute error(MAE),as well as the coefficient of determination(R^(2)).The findings show that the Least Angle Regression(LAR)model performed the best with an R^(2) value close to 1.0000,confirming high predictive accuracy.The OMP model performed well with good accuracy(R^(2)=0.8727)while remaining computationally cheap,while other models(e.g.,neural networks,random forests)performed well but were too computationally expensive.Finally,to assess the robustness of the results,an error analysis indicated that residuals were evenly distributed around zero,confirming the results from the LAR model.The current research illustrates the potential of AI in anticipating drug solubility,providing support for green pharmaceutical design and environmental risk assessment.Future work should extend predictions to include degradation and toxicity to enhance predictive power and applicability.
文摘In order to increase the solubility of pyrroloquinoline quinone disodium salt(PQQ-NA_(2))in water,PQQ-NA_(2)ionic salts formed by PQQ-NA_(2)with amine compounds had been developed.Amine compounds specifically refered to aminomethyl propanol,tromethamine,and matrine.The PQQ-NA_(2)ionic salts solubility test result showed an increase as high as 24-fold compared to dissolving PQQ-NA_(2)alone.The antioxidant test indicated that the ionic salts exhibited significant antioxidant property.Two PQQ-NA_(2)gel formulations were prepared containing the ionic salts,and the stability test and PQQ-NA_(2)content test indicated that the formulations were stable and the loss rate of PQQ was below 10%.
基金supported by the National Key Research and Development Program of China(Grant No.2019YFE0117200)the National Natural Science Foundation of China(Grant No.41977304).
文摘Understanding the solubility of supercritical CO_(2)and its mixtures with other fluids at various temperatures and pressures conditions is critical for their applications,such as extraction processes,material design,and carbon capture.In the present study,the solubility parameters of supercritical CO_(2),H_(2)O,and their mixtures were calculated by molecular dynamics simulations.The results show that the solubility parameters decrease with increasing temperature and increase with increasing pressure and are linearly proportional to the density.Furthermore,the intermolecular interactions,including the hydrogen bonds,significantly affect the solubility parameter of the CO_(2)-H_(2)O system.
基金supported by the National Natural Science Foundation of China(22075091)the Natural Science Foundation of Hubei Province(Grant No.2021CFA066)。
文摘Li-S batteries are regarded as one of the most promising candidates for next-generation battery systems with high energy density and low cost.However,the dissolution-precipitation reaction mechanism of the sulfur(S)cathode enhances the kinetics of the redox processes of the insulating sulfu r,which also arouses the notorious shuttle effect,leading to serious loss of S species and corrosion of Li anode.To get a balance between the shuttle restraining and the kinetic property,a combined strategy of electrolyte regulation and cathode modification is proposed via introducing 1,1,2,2-tetrafluoroethyl-2,2,3,3-tetrafluoroprpyl ether(HFE)instead of 1,2-dimethoxyethane(DME),and SeS_(7)instead of S_8.The introduction of HFE tunes the solvation structure of the LiTFSI and the dissolution of intermediate polysulfides with Se doping(LiPSSes),and optimize the interface stability of the Li anode simultaneously.The minor Se substitution compensates the decrease in kinetic due to the decreased solubility of LiPSs.In this way,the Li-SeS_(7)batteries deliver a reversible capacity of 1062 and 1037 mAh g^(-1)with 2.0 and 5.5 mg SeS_(7)cm^(-2)loading condition,respectively.Besides,an electrolyte-electrode loading model is established to explain the relationship between the optimal electrolyte and cathode loading.It makes more sense to guide the electrolyte design for practical Li-S batteries.
基金the financial support from the National Key Research and Development Program of China(2022YFB4101302-01)the National Natural Science Foundation of China(22178243)the science and technology innovation project of China Shenhua Coal to Liquid and Chemical Company Limited(MZYHG-22–02).
文摘The cyclic hydrogenation technology in a direct coal liquefaction process relies on the dissolved hydrogen of the solvent or oil participating in the hydrogenation reaction.Thus,a theoretical basis for process optimization and reactor design can be established by analyzing the solubility of hydrogen in liquefaction solvents.Experimental studies of hydrogen solubility in liquefaction solvents are challenging due to harsh reaction conditions and complex solvent compositions.In this study,the composition and content of liquefied solvents were analyzed.As model compounds,hexadecane,toluene,naphthalene,tetrahydronaphthalene,and phenanthrene were chosen to represent the liquefied solvents in chain alkanes and monocyclic,bicyclic,and tricyclic aromatic hydrocarbons.The solubility of hydrogen X(mol/mol)in pure solvent components and mixed solvents(alkanes and aromatics mixed in proportion to the chain alkanes+bicyclic aromatic hydrocarbons,bicyclic saturated aromatic hydrocarbons+bicyclic aromatic hydrocarbons,and bicyclic aromatic hydrocarbons+compounds containing het-eroatoms composed of mixed components)are determined using Aspen simulation at temperature and pressure conditions of 373–523 K and 2–10 MPa.The results demonstrated that at high temperatures and pressures,the solubility of hydrogen in the solvent increases with the increase in temperature and pressure,with the pressure having a greater impact.Further-more,the results revealed that hydrogen is more soluble in straight-chain alkanes than in other solvents,and the solubility of eicosanoids reaches a maximum of 0.296.The hydrogen solubility in aromatic ring compounds decreased gradually with an increase in the aromatic ring number.The influence of chain alkanes on the solubility of hydrogen predominates in a mixture of solvents with different mixing ratios of chain alkanes and aromatic hydrocarbons.The solubility of hydrogen in mixed aromatic solvents is less than that in the corresponding single solvents.Hydrogen is less soluble in solvent compounds containing heteroatoms than in compounds without heteroatoms.
基金supported by the National Key Research and Development Program of China(2021YFC2103800)the National Natural Science Foundation of China(U21A20301)the Research Funds of Institute of Zhejiang University-Quzhou(IZQ2022RCZX004 and IZQ2021RCZX015)。
文摘The equilibrium solubility of Rebaudioside A(Reb A)FormⅡin binary mixtures of methanol/ethanol and ethyl acetate was quantitatively determined within the temperature range of 283.15—328.15 K at ambient pressure.The experimental findings indicate a positive correlation between the solubility of Reb A(FormⅡ)and both the temperature and the methanol/ethanol content in the solvent system.To describe the solubility data,six distinct models were employed:the modified Apelblat equation,theλh model,the combined nearly ideal binary solvent/Redlich—Kister(CNIBS/R—K)model,the van't HoffJouyban-Acree(VJA)model,the Apelblat-Jouyban-Acree(AJA)model,and the non-random two-liquid(NRTL)model.The combined nearly ideal binary solvent/Redlich—Kister model exhibited the most precise fit for solubility in methanol+ethyl acetate mixtures,reflected by an average relative deviation(ARD)of 0.0011 and a root mean square deviation(RMSD)of 12×10^(-7).Conversely,for ethanol+ethyl acetate mixtures,the modified Apelblat equation provided a superior correlation(ARD=0.0014,RMSD=4×10^(-7)).Furthermore,thermodynamic parameters associated with the dissolution of Reb A(FormⅡ),including enthalpy,entropy,and the Gibbs energy change,were inferred from the data.The findings underscore that the dissolution process is predominantly endothermic across the solvent systems examined.Notably,the entropy changes appear to have a significant influence on the Gibbs free energy associated with the dissolution of Reb A(FormⅡ),suggesting that entropic factors may play a pivotal role in the studied systems.
文摘In order to remove hexahydro-1,3,5-trinitro-1,3,5-triazine(RDX),the main impurity,in process of polymorphic transformation of octrahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine(HMX),the solubility ofβ-HMX and RDX in acetonitrile(ACN)+water in the temperature range of 288.15-333.15 K and in nitric acid(HNO_(3))+water in the temperature range of 298.15-333.15 K were measured by laser dynamic method.The results showed that the solubility of bothβ-HMX and RDX in binary mixed solvents increased monotonously as the temperature increase at a given solvent composition or with increasing of mole fraction of solvent(ACN and nitric acid).Solubility data were well correlated by the modified Apelblat equation,Jouyban-Acree model,Yaws equation and van't Hoff equation,and the Yaws equation achieved the best fitting results according to the relative error and the mean square error root.Furthermore,the solubility ofβ-HMX and RDX in binary mixed solvent was compared,based on the solubility difference and the solvent's own properties,the best separation degree ofβ-HMX and RDX was found when the mole fraction of nitric acid was 0.22 at room temperature,which provided data support for HMX crystallization in mixed solvent.The solubility differences between RDX andβ-HMX in mixed solvents were explained from the formation of intermolecular and intramolecular hydrogen bonds.
文摘Hydraulic fracturing is an effective technology for hydrocarbon extraction from unconventional shale and tight gas reservoirs.A potential risk of hydraulic fracturing is the upward migration of stray gas from the deep subsurface to shallow aquifers.The stray gas can dissolve in groundwater leading to chemical and biological reactions,which could negatively affect groundwater quality and contribute to atmospheric emissions.The knowledge oflight hydrocarbon solubility in the aqueous environment is essential for the numerical modelling offlow and transport in the subsurface.Herein,we compiled a database containing 2129experimental data of methane,ethane,and propane solubility in pure water and various electrolyte solutions over wide ranges of operating temperature and pressure.Two machine learning algorithms,namely regression tree(RT)and boosted regression tree(BRT)tuned with a Bayesian optimization algorithm(BO)were employed to determine the solubility of gases.The predictions were compared with the experimental data as well as four well-established thermodynamic models.Our analysis shows that the BRT-BO is sufficiently accurate,and the predicted values agree well with those obtained from the thermodynamic models.The coefficient of determination(R2)between experimental and predicted values is 0.99 and the mean squared error(MSE)is 9.97×10^(-8).The leverage statistical approach further confirmed the validity of the model developed.
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supported by the National Natural Science Foundation of China(No.21776264).
文摘Studying the relationship between ionic interactions and salt solubility in seawater has implications for seawater desalination and mineral extraction.In this paper,a new method of expressing ion-to-ion interaction is proposed by using molecular dynamics simulation,and the relationship between ion-to-ion interaction and salt solubility in a simulated seawater water-salt system is investigated.By analyzing the variation of distance and contact time between ions in an electrolyte solution,from both spatial and temporal perspectives,new parameters were proposed to describe the interaction between ions:interaction distance(ID),and interaction time ratio(ITR).The best correlation between characteristic time ratio and solubility was found for a molar ratio of salt-to-water of 10:100 with a correlation coefficient of 0.96.For the same salt,a positive correlation was found between CTR and the molar ratio of salt and water.For type 1-1,type 2-1,type 1-2,and type 2-2 salts,the correlation coefficients between CTR and solubility were 0.93,0.96,0.92,and 0.98 for a salt-to-water molar ratio of 10:100,respectively.The solubility of multiple salts was predicted by simulations and compared with experimental values,yielding an average relative deviation of 12.4%.The new ion-interaction parameters offer significant advantages in describing strongly correlated and strongly hydrated electrolyte solutions.
基金financial support from the National Key Research and Development Program of China(2020YFA0710202)the National Natural Science Foundation of China(21978043,U1662130)+1 种基金Inner Mongolia University of Technology Scientific Research Initial Funding(DC2300001240)Talent Introduction Support Project of Inner Mongolia(DC2300001426).
文摘As a common precursor for supercritical CO_(2)(scCO_(2))deposition techniques,solubility data of organometallic complexes in scCO_(2)is crucial for the preparation of nanocomposites.Recently,metal acetylacetonates have shown great potential for the preparation of single-atom catalytic materials.In this study,the solubilities of iron(Ⅲ)acetylacetonate(Fe(acac)3)and nickel(Ⅱ)acetylacetonate(Ni(acac)2)were measured at the temperature from 313.15 to 333.15 K and in the pressure range of 9.5–25.2 MPa to accumulate new solubility data.Solubility was measured using a static weight loss method.The semi-empirical models proposed by Chrastil and Sung et al.were used to correlate the solubility data of Fe(acac)3 and Ni(acac)2.The equations obtained can be used to predict the solubility of the same system in the experimental range.
基金financially supported by the National Key R&D Program of China(No.2021YFB1507403)the National Natural Science Foundation of China(No.52071218)+1 种基金Shenzhen Science and Technology Innovation Commission(No.JCYJ20230808105700001)Shenzhen University 2035 Program for Excellent Research(No.00000218)。
文摘The successful deployment of thermoelectric materials necessitates the concurrent development of highperformance p-type and n-type pairs situated within an identical matrix.Nevertheless,limiting by the low dopant solubility,the conventional doping often cannot transfer the Fermi level to the opposite carrier type.Here,the solubility limit of donor dopants was enhanced to achieve n-type GeSe by inducing additional cationic vacancies through raising crystal symmetry.Converting the intrinsic p-type nature of GeSe to n-type poses significant challenges,primarily due to the exceedingly low dopant solubility within its native orthorhombic structure.To overcome this,the In_(2)Te_(3)alloying was initially employed to transition GeSe from orthorhombic to rhombohedral structure,simultaneously generating a large number of Ge vacancies.Following this,the introduction of Pb acts to mitigate the excessive Ge vacancies,steering the material toward a weak p-type character.Crucially,the elevated Ge vacancy concentration serves to extend the solubility limit of Bi donor dopant,which not only promotes the formation of cubic phase,but also enables the p-n type transition.As a result,a peak zT of 0.18 at 773 K was attained for the n-type cubic Ge_(0.55)Bi_(0.2)Pb_(0.2)5Se(In_(2)Te_(3))_(0.1),marking an 18-fold enhancement in comparison with its n-type orthorhombic counterpart.This work attests to the efficacy of introducing vacancies through enhancing crystal symmetry as an effective means to expand dopant solubility,thereby offering valuable insights into the achievement of compatible p-and n-type chalcogenides within the same matrix.
文摘Short Retraction NoticeThis article has been retracted to straighten the academic record. In making this decision the Editorial Board follows COPE's Retraction Guidelines. The aim is to promote the circulation of scientific research by offering an ideal research publication platform with due consideration of internationally accepted standards on publication ethics. The Editorial Board would like to extend its sincere apologies for any inconvenience this retraction may have caused. The full retraction notice in PDF is preceding the original paper, which is marked "RETRACTED".
基金funded by Young and Middle Aged Teachers’Career Development Support Project of Shenyang Pharmaceutical University(ZQN2019005).
文摘Kaempferol(KA),as one of the flavonoids,has extensive pharmacological properties.However,the poor solubility of KA severely limits its clinical application.In our study,the kaempferol phospholipid complex(KA-PC)has been prepared by solvent evaporation for the enhancement of the bioavailability of KA.KA-PC was verified by scanning electron microscope characterization methods.Drug loading,solubility and long-term stability were measured.The characterization results showed that KA-PC was formed through the intermolecular interaction between KA and phospholipids.The solubility of KA-PC in water was 189 times higher than that of KA,and the solubility in n-octanol was also significantly improved.Besides,pharmacodynamic studies showed that KA-PC can significantly reduce the level of serum uric acid in mice without causing renal injury.This study expanded the clinical application of KA by preparing KA-PC.
