Summary of main observation and conclusion CO2 flooding accounts for a considerable proportion in gas flooding.Using CO2 as a gas displacement agent is benefit for enhanced oil recovery(EOR),and the alleviation of the...Summary of main observation and conclusion CO2 flooding accounts for a considerable proportion in gas flooding.Using CO2 as a gas displacement agent is benefit for enhanced oil recovery(EOR),and the alleviation of the greenhouse effect by the permanent storage of CO2 in the crust.Minimum miscibility pressure(MMP)of CO2-oil is a key factor affecting EOR,which determines the yield and economic benefit of crude oil recovery.Therefore,it is of great importance to use fast,accurate and cheap prediction methods for MMP estimation.In the present study,to evaluate the reliability of four recently developed prediction models based on machine learning(i.e.,neural network analysis(NNA),genetic function approximation(GFA),multiple linear regression(MLR),partial least squares(PLS)),136 sets of data are selected for calculation via outlier analysis from 147 sets of data.Afterwards,we compared the four models with existing prediction models from the literature.The analysis of correlation coefficients and multiple error functions shows that the four models can solve the MMP prediction problem well,and the model using intelligent algorithm has a higher prediction accuracy than the simple linear model.Besides,intelligent methods based on similarity algorithm have little difference from each other.Finally,a sensitivity analysis was conducted.展开更多
The broad class of explosives includes nitro aromatics as well as challenging aliphatic nitro-organics whose detection is important from counter-terrorism and national security perspectives.Here we report a turn-on fl...The broad class of explosives includes nitro aromatics as well as challenging aliphatic nitro-organics whose detection is important from counter-terrorism and national security perspectives.Here we report a turn-on fluorescent sensor array based on aggregation-induced emission(AIE)fluorophores as receptors.To achieve a good sensing system with fast response,good sensitivity and low detection limit,three receptors with abundant chemical diversities for target analytes were synthesized.The turn-on response of the individual receptor showed highly variable and cross-reactive analyte-dependent changes in fluorescence.The excellent ability to identify a variety of explosives,especially the challenging aliphatic nitro-organics(2,3-dimethyl-2,3-dinitrobutane(DMNB),1,3,5-trinitro-1,3,5-triazinane(RDX),cyclotetramethylene tetranitramine(HMX)and entaerythritol tetranitrate(PETN)),was demonstrated in qualitative and quantitative analyses with 100%accuracy.The fluorescence signal amplification in the presence of explosives allows for application of these receptors in a sensor microarray suitable for high-throughput screening.These results suggested that the cross-reactive sensor array based on AIE fluorophores could find a wide range of applications for sensing various analytes or complex mixtures.展开更多
Main observation and conclusion In this paper,a series of ReaxFF molecular dynamic simulations were performed to study the oxidation of chemical passivated silicon(100)surface,which was terminated with different n-alk...Main observation and conclusion In this paper,a series of ReaxFF molecular dynamic simulations were performed to study the oxidation of chemical passivated silicon(100)surface,which was terminated with different n-alkyl chains.The simulated results showed that the oxidant species diffuse into Si substrate through peroxy-like structures during the oxidation process.During the oxidation process,the Si-alkyl(Si-C)covalent bond was stable and there is no occurrence of decomposition of the n-alkyl chains.In addition,the existence of n-alkyl monolayers on silicon surface did not change the initial reaction pathway of the oxidation process.The simulations indicated that the chemical passivation mechanism includes two parts,one is about the Si-C covalent bond occupying the active site of the reaction on Si(100)surface,and the other is about the oxygen penetrating Si-alkyl layers.The simulations also indicated that the chemical passivation of Si-alkyl is better for longer alkyl chains,which is consistent with the experimental observation.Our results have investigated the oxidation of chemical passivated silicon(100)surface at the atom level,which is helpful to comprehend the manufacture of semiconductor devices like metal-oxide-semiconductor(MOS)devices in the experiments.展开更多
基金supported by“Qilu Young Talent Scholar”program (11190088963032)of Shandong Universitythe Carbon Neutrality Research Institute Funds (CNIF20230101 and CNIF20230202)the Wynca Group for its“Chem is Try”Innovation Fund (11190047102082)under“Xin’An Cup”program。
基金This work was supported by the National Natural Science Foundation of China(No.21573130).
文摘Summary of main observation and conclusion CO2 flooding accounts for a considerable proportion in gas flooding.Using CO2 as a gas displacement agent is benefit for enhanced oil recovery(EOR),and the alleviation of the greenhouse effect by the permanent storage of CO2 in the crust.Minimum miscibility pressure(MMP)of CO2-oil is a key factor affecting EOR,which determines the yield and economic benefit of crude oil recovery.Therefore,it is of great importance to use fast,accurate and cheap prediction methods for MMP estimation.In the present study,to evaluate the reliability of four recently developed prediction models based on machine learning(i.e.,neural network analysis(NNA),genetic function approximation(GFA),multiple linear regression(MLR),partial least squares(PLS)),136 sets of data are selected for calculation via outlier analysis from 147 sets of data.Afterwards,we compared the four models with existing prediction models from the literature.The analysis of correlation coefficients and multiple error functions shows that the four models can solve the MMP prediction problem well,and the model using intelligent algorithm has a higher prediction accuracy than the simple linear model.Besides,intelligent methods based on similarity algorithm have little difference from each other.Finally,a sensitivity analysis was conducted.
基金the National Natural Science Foundation of China(50873051,205333050)National High Technology Research and Development Program of China(2007AA03Z307)Transregional Project(TRR61)
文摘The broad class of explosives includes nitro aromatics as well as challenging aliphatic nitro-organics whose detection is important from counter-terrorism and national security perspectives.Here we report a turn-on fluorescent sensor array based on aggregation-induced emission(AIE)fluorophores as receptors.To achieve a good sensing system with fast response,good sensitivity and low detection limit,three receptors with abundant chemical diversities for target analytes were synthesized.The turn-on response of the individual receptor showed highly variable and cross-reactive analyte-dependent changes in fluorescence.The excellent ability to identify a variety of explosives,especially the challenging aliphatic nitro-organics(2,3-dimethyl-2,3-dinitrobutane(DMNB),1,3,5-trinitro-1,3,5-triazinane(RDX),cyclotetramethylene tetranitramine(HMX)and entaerythritol tetranitrate(PETN)),was demonstrated in qualitative and quantitative analyses with 100%accuracy.The fluorescence signal amplification in the presence of explosives allows for application of these receptors in a sensor microarray suitable for high-throughput screening.These results suggested that the cross-reactive sensor array based on AIE fluorophores could find a wide range of applications for sensing various analytes or complex mixtures.
基金The authors are grateful for funding from the Youth Innovation Group of Shandong University(No.2020QNQT018).
文摘Main observation and conclusion In this paper,a series of ReaxFF molecular dynamic simulations were performed to study the oxidation of chemical passivated silicon(100)surface,which was terminated with different n-alkyl chains.The simulated results showed that the oxidant species diffuse into Si substrate through peroxy-like structures during the oxidation process.During the oxidation process,the Si-alkyl(Si-C)covalent bond was stable and there is no occurrence of decomposition of the n-alkyl chains.In addition,the existence of n-alkyl monolayers on silicon surface did not change the initial reaction pathway of the oxidation process.The simulations indicated that the chemical passivation mechanism includes two parts,one is about the Si-C covalent bond occupying the active site of the reaction on Si(100)surface,and the other is about the oxygen penetrating Si-alkyl layers.The simulations also indicated that the chemical passivation of Si-alkyl is better for longer alkyl chains,which is consistent with the experimental observation.Our results have investigated the oxidation of chemical passivated silicon(100)surface at the atom level,which is helpful to comprehend the manufacture of semiconductor devices like metal-oxide-semiconductor(MOS)devices in the experiments.
