超临界CO2技术制备微孔聚合物中的基本问题

微发泡聚合物材料以环境友好的超临界CO₂为发泡剂, 具有优异的材料性能. 本文对本课题组的研究工作做了归纳总结, 对聚合物微发泡中CO₂的传质、微发泡过程中泡孔结构参数的变化以及多相/多组分聚合物体系的微发泡行为等内容做了针对性的综述. 结合对聚合物微发泡过程理论模拟研究工作的评述, 展望了超临界CO₂微发泡技术未来的发展方向.     

CO2刺激响应聚合物

CO2刺激响应性聚合物是新近发展起来的一类智能型刺激响应聚合物,是指在通入和排出CO2后,聚合物性质能够发生可逆性变化的新型聚合物。由于调控过程中仅仅涉及CO2以及一些惰性气体而不引入其他杂质,因此具有多方面的潜在应用价值。本文调研了这方面的工作,综述了几类CO2刺激响应聚合物的合成及其自组装,并指出了CO2刺激响应聚合物的应用前景和发展方向。     

超临界CO2中的高分子合成研究进展

本文介绍以超临界CO₂流体为介质的高分子合成的研究进展。说明可在超临界二氧化碳中实施氟代单体的自由基溶液聚合、甲基丙烯酸甲酯和苯乙烯的分散聚合、丙烯酸的沉淀聚合、丙烯酰胺的反相乳液聚合以及异丁基乙烯基醚的阳离子聚合等多种聚合反应。这显示出超临界CO₂是一种对环境无污染且价廉的替代溶剂。     

傅立叶变换红外光谱技术在超临界CO2作用聚合物体系中的应用

超临界CO₂（scCO₂）作为一种物理化学性质优良、具有高扩散速率及优良溶解性能的溶剂,在科学研究及工业生产中广受青睐。将scCO₂应用于聚合物体系中,CO₂ 与聚合物间特殊的相互作用有利于CO₂分子在聚合物中的吸附与扩散。同时通过CO₂的吸附及其对聚合物的溶胀和塑化作用,聚合物所处微观化学环境以及整体结构性质会发生一定的变化。由于傅立叶变换红外光谱（FTIR）技术能够有效地考察化学环境变化对分子结构造成的影响,这一表征技术在超临界CO₂作用体系中广为应用。本文主要选取了近年来利用FTIR技术考察scCO₂作用于聚合物体系的一些实例,从CO₂-聚合物相互作用机理,scCO₂对聚合物或生物大分子的加工过程的影响两方面,阐述了利用红外光谱技术在scCO₂作用体系中的应用以及前景。     

超临界CO2流体萃取重金属的研究进展

超临界CO₂ 流体与金属配合技术相结合开辟了重金属萃取的新途径。本文介绍了超临界CO₂流体萃取重金属的研究现状, 总结了影响萃取的因素, 并对未来的发展趋势作了展望。     

基于混沌自适应粒子群人工神经网络的气体在聚合物中的溶解模型

为提高溶解预测模型的效率和关联度, 建立基于混沌理论、自适应粒子群优化(PSO)算法和反向传播(BP)算法的混沌自适应PSO-BP神经网络模型, 并对二氧化碳(CO₂)在聚苯乙烯(PS)和聚丙烯(PP)中、氮气(N₂)在PS中的溶解度进行预测试验. 模型选用压力和温度作为输入参数, 使用试探法确定隐含层结点个数为8, 输出为预测的溶解度. 模型融合混沌理论、自适应PSO和BP算法各自的优势, 提高了训练速度和预测精度. 结果表明, 混沌自适应PSO-BP神经网络有很好的预测能力, 预测值与实验值相当吻合, 通过与传统BP神经网络和PSO-BP神经网络的比较可知, 其预测精度和相关性均明显较优, 预测平均绝对误差(AAD), 标准偏差(SD)和平方相关系数(R²)分别为0.0058, 0.0198和0.9914.     

嵌段聚合物PGMA-b-PDEAEMAx的合成及其CO2诱导解组装行为

以甲基丙烯酸二乙基氨基乙酯为疏水段,聚甲基丙烯酸甘油酯为亲水段,采用可逆加成-断裂转移聚合合成了具有不同嵌段比例的甲基丙烯酸甘油酯-b-甲基丙烯酸二乙氨基乙酯二嵌段聚合物(PGMA-b-PDEAEMAx),其结构经1H NMR和GPC表征。聚合物通过自组装形成球形胶束、线性胶束聚集体和囊泡结构;向聚合物溶液中通入CO2后,其自组装解体。     

超临界CO2中苯乙烯RAFT分散聚合

以末端带有三硫代碳酸酯的聚二甲基硅氧烷(PDMS-TTC)为大分子链转移剂,在超临界CO2中通过苯乙烯的可逆加成-断裂链转移(RAFT)聚合制备了聚二甲基硅氧烷-b-聚苯乙烯(PDMS-b-PS)嵌段共聚物,对聚合反应动力学以及产物的组成、分子量和形貌等进行了表征.由于PDMS链段可溶于超临界CO2而PS链段不溶,因此在超临界CO2中制备PDMS-b-PS嵌段共聚物的过程是以嵌段共聚物自身作为分散稳定剂的RAFT分散聚合,产物为粒径较均一的球形颗粒.     

醇/水混合溶剂中碱性聚合物电解质独特的溶解行为

Self-aggregated quaternary ammonium polysulfone (aQAPS) is a high-performance alkaline polymer electrolyte that has been applied in alkaline polymer electrolyte fuel cells (APEFCs). For a long time, N, N-dimethyl formamide (DMF) has been considered the best solvent to dissolve aQAPS, but the high boiling point of DMF makes it hard to remove from the electrodes, which potentially poisons the electrocatalysts. Our recent experiments have shown that although aQAPS is unable to dissolve in ethanol, n-propanol, or water, it can dissolve in the mixture of these alcohols and water. This peculiar dissolution behavior significantly facilitates the fabrication of the membrane electrode assembly (MEA) for APEFCs, even though it has not been understood. In this work, atomistic molecular dynamics (MD) simulations were employed to study the dissolution behavior of aQAPS in different solvents, including water, methanol, ethanol, n-propanol, DMF, and the mixture of these non-aqueous solvents and water. The conformation of the aQAPS chain in pure solvents agreed well with the dissolution behavior observed in the experiments, even though in the water-containing mixed solvents, the aQAPS chain tended to be in a more contracted state. The simulations further revealed that the water component in the mixed solvents played dual roles. On one hand, the hydrocarbon chain of aQAPS was compressed to a contracted state upon the addition of water, because of the hydrophobic effect. On the other hand, water can drive the dissociation of the counterion (Cl^{–­ ­ ­} ), which led to an enhancement in the solute-solvent interaction energy and thus facilitated the dissolution of aQAPS. In most mixed solvents, the compensation of these two interactions resulted in a general increase in the total solute-solvent interaction energy; therefore, the addition of water was energetically favorable for the dissolution of aQAPS. This study not only furthers our fundamental understanding of the dissolution behavior of polyelectrolytes but also is technologically significant for the development of better APEFCs.     

不同聚合物对纳米SiO2表面改性的研究进展

纳米SiO2由于具有无味、无毒、无污染等特性,因而被广泛用作无机纳米填料。纳米SiO2极易团聚,从而限制了它的广泛应用。但纳米SiO2表面富含大量的硅羟基,可对其进行表面改性。纳米SiO2表面改性的方法较多,主要有表面物理改性和表面化学改性两种,其中表面化学改性中又以聚合物改性的效果最好。本文综述了国内外利用不同的聚合物——亲水性、疏水性和两亲性聚合物对纳米SiO2表面的化学改性,并对其应用进行了分析,展望了其发展前景。     

Solubility of iodopropynyl butylcarbamate in supercritical carbon dioxide

Supercritical carbon dioxide has been considered an appropriate alternative for extraction and purification process of cosmetics, pharmaceuticals, food supplements and natural products. Solubility information of biological compounds is essential for choosing supercritical fluid (SCF) processes. The solubility of iodopropynyl butylcarbamate (IPBC), a fungicide and anti-dandruff agent, was measured in supercritical carbon dioxide with a high pressure apparatus equipped with a variable volume view cell at 313.15, 323.15, and 333.15 K and at pressure between 80 and 35 MPa. The experimental data were correlated well with Peng–Robinson equation of state (PR EOS) and quasi-chemical nonrandom lattice fluid model.     

Evaluation of attraction terms in equations of state on the prediction of solubility of some biomolecules in supercritical carbon dioxide

In the present work,effect of theattr action terms of four recently modified Peng-Robinson(MPR)equations of state on the prediction of solubility of caffeine,cholesterol,uracil and erythromycin was studied.The attraction terms of two of these equations are linear relative to the acentric factor and for the other two are exponential.It is found that the later show less deviation.Also interaction parameters for the studied systems are obtained and the percentage of average absolute relative deviation(%AARD)in each calculation is displayed.     

Measurement and correlation of solubility of artemisinin in supercritical carbon dioxide

Artemisinin is an effective antimalarial drug isolated from the herbal medicine Artemisia annua L. Supercritical fluid extraction is an environment-friendly method for the extraction of artemisinin. In this work, the solubility of artemisinin in supercritical carbon dioxide was determined by static method at three temperatures of 313 K, 323 K, 333 K and pressures from 11 to 31 MPa. The range of experimental solubility data was from 0.498 × 10⁻³ to 2.915 × 10⁻³ mol/mol under the above-mentioned conditions. Two density-based models (Chrastil and Mendez–Santiago–Teja models) were selected to correlate the experimental data of this work, and the average absolute relative deviation (AARD) was 8.32% and 8.33%, respectively. The correlation results showed good agreement with the experimental data.     

Measurement and correlation of solubility of anthraquinone dyestuffs in supercritical carbon dioxide

Solubility data of 1,4-diaminoanthraquinone (C.I. Disperse Violet 1) and 1,4-bis(ethylamino)anthraquinone (C.I. Solvent Blue 59) in supercritical carbon dioxide (sc-CO₂) have been measured at the temperatures of (323.15, 353.15, and 383.15) K and over the pressure range from (12.5 to 25.0) MPa by a flow-type apparatus. The solubility of two anthraquinone dyestuffs was obtained over the mole fraction ranges of (1.3 to 26.1) · 10⁻⁷ for 1,4-diaminoanthraquinone (C.I. Disperse Violet 1) and (1.1 to 148.5) · 10⁻⁷ for 1,4-bis(ethylamino)anthraquinone (C.I. Solvent Blue 59). The experimental results have been correlated with the empirical equations of Mendez-Santiago–Teja and Kumar–Johnston expressed in terms of the density of sc-CO₂, and also analyzed thermodynamically by the regular solution model with the Flory–Huggins theory and the Peng–Robinson equation of state modified by Stryjek and Vera (PRSV-EOS) with the conventional mixing rules. Good agreement between the experimental and calculated solubilities of the dyestuffs was obtained.     

A comparison between neural network method and semi empirical equations to predict the solubility of different compounds in supercritical carbon dioxide

Accuracy of seven semi empirical equations for the estimation of solubility of 30 different compounds in supercritical carbon dioxide has been compared with a new neural network method. To base this comparison on a fair basis, a unique set of experimental data was used for both optimization of semi empirical equations’ parameters and training, validation and testing of neural network. Results showed that neural network method with an average relative deviation of about 5.3% was more accurate than the best semi empirical equation with an average relative deviation of about 15.96% for same compounds. It was also found that the average relative deviation of semi empirical equations varies sharply among different compounds, while this quantity is less dependent on material type for neural network method.     

Solubility of thiophene in carbon dioxide and carbon dioxide + 1-propanol mixtures at temperatures from 313 to 363 K

Solubility measurements of sulfur compounds in supercritical fluids are required in order to determine the feasibility of supercritical extraction for removing them from gasoline and diesel fuel. In this work, solubility of thiophene in CO₂ and in CO₂ + 1-propanol mixtures were measured from 313 to 363 K using an apparatus based on the static–analytical method. Vapor–liquid equilibria (VLE) data of binary mixtures were fitted to the Peng–Robinson equation of state (EoS) with classical mixing rules. The binary interaction parameters (k_ij) obtained were used to predict the VLE data of ternary systems. The calculated values given by this simple model agree well to the experimental data.     

Measurement and modeling of metoclopramide hydrochloride (anti-emetic drug) solubility in supercritical carbon dioxide

Knowledge of drug solubility data in supercritical carbon dioxide (SC-CO₂) is a fundamental step in producing nano and microparticles through supercritical fluid technology. In this work, for the first time, the solubility of metoclopramide hydrochloride (MCP) in SC-CO₂ was measured in pressure and temperature range of 12 to 27 MPa and 308 to 338 K, respectively. The results represented a range mole fractions of 0.15 × 10^-5 to 5.56 × 10^-5. To expand the application of the obtained data, six semi-empirical models and three models based on the Peng-Robinson equation of state (PR + VDW, PR + WS + Wilson and PR + MHV1 + COSMOSAC) with different mixing rules and various ways to describe intermolecular interactions were investigated. Furthermore, total enthalpy, sublimation enthalpy and solvation enthalpy relevant to MCP solvating in SC-CO₂ were estimated.     

Measurement and correlation of solubility of benzamide in supercritical carbon dioxide with and without cosolvent

The experimental equilibrium solubility of benzamide in supercritical carbon dioxide was measured at temperatures between 308 K and 328 K and for pressures from 11.0 MPa to 21.0 MPa using a dynamic flow method. The effects of three cosolvents - ethanol, acetone and ethylene glycol, were investigated at a cosolvent molar concentration of 3.5%. The results showed that the solubility was enhanced by the presence of the three cosolvents, and ethanol exhibited the highest cosolvent effect. The solubility data in the absence and presence of cosolvents were correlated by two density-based models. The calculated results showed satisfactory agreement with the experimental data.     

Novel density-based model for the correlation of solid drugs solubility in supercritical carbon dioxide

A novel density-based model derived by a simple modification of the Jouyban et al. model has been proposed to correlate the solubility of solid drugs in supercritical carbon dioxide. The six-parameter model expresses the solubility only as a function of the solvent density and the equilibrium temperature. This model is in contrast to the Jouyban et al. (J. Superiority. Fluids 24 (2002) 19) model, which gives the solubility as a function of the solvent density and the equilibrium temperature and pressure. The performance of the model has been tested on a database of 100 drugs that account for 2891 experimental data points collected from the literature. The comparison in terms of the mean absolute relative deviation for each solid drug and for the entire database between the proposed model and models that have been suggested to be mostly more accurate demonstrates that the proposed model has the best global correlation performance, exhibiting an overall average absolute relative deviation of 8.13%.