动态凝胶网络中的溶质扩散

从理论和实验两方面研究了凝胶网络中溶质的扩散 .着重于凝胶网络的涨落对扩散的影响 ,以动态链渗流理论建立了凝胶动态网络中溶质扩散的数学模型 .制备了聚异丙基丙烯酰胺(PNIPA)水凝胶 ,用激光光散射法测定了凝胶网络的涨落行为 .用双室膜池法以甲基蓝为溶质测定了凝胶中的扩散 .模型与实验结果定性相符 .     

P(AA-DAC)两性聚电解质水凝胶的合成及性质

以丙烯酸(AA)和丙烯酰氧乙基三甲基氯化铵(DAC)为单体, 采用水溶液聚合法制备了P(AA-DAC)聚电解质水凝胶. 采用红外光谱和核磁共振等方法对其结构进行了表征. 研究了不同组成比的聚电解质水凝胶在去离子水、不同pH值溶液以及不同离子强度盐溶液中的溶胀行为. 研究结果表明, 摩尔比为1∶1的聚电解质水凝胶表现出典型的两性聚电解质凝胶的溶胀行为. 离子强度对其溶胀行为有着显著影响, 在溶液离子强度较高时, 凝胶网络的溶胀主要受溶剂向凝胶内部扩散所控制, 满足Fick型扩散规律n≤0.5, 随着溶液离子强度的增加, 凝胶网络平衡含水量增加, 扩散系数增大.     

先辐射后冻融法制备聚乙烯醇/水溶性壳聚糖/甘油水凝胶的云南白药药物释放性能研究

采用先辐射后冻融的方法制备了一系列聚乙烯醇(PVA)/水溶性壳聚糖/甘油水凝胶,通过浸泡法在水凝胶中载入云南白药,并且研究了溶液pH值、离子强度、冻融次数和PVA浓度对水凝胶溶胀性能和云南白药释放性能的影响.研究发现水凝胶的溶胀度随溶液离子强度的增大而下降,且酸性溶液大于中性溶液.水溶性壳聚糖的加入有利于云南白药载入凝胶,同时使云南白药的释放具有pH和离子强度敏感性.云南白药的释放量在模拟体液中最大,在中性溶液中次之,在水和酸性溶液中最小,与溶胀度变化关系相反.而水凝胶的溶胀度和云南白药释放量均随冻融次数和PVA浓度的增大而下降.分析表明,云南白药在不同介质中的释放量主要取决于药物和溶液中离子的交换能力;在相同介质中,不同凝胶的药物释放量受溶胀度影响明显.凝胶溶胀速率远大于药物释放速率说明后者主要由扩散过程控制.药物释放的pH敏感性表明该水凝胶具备用作云南白药的口服载体的潜力.     

干燥方式对含直链淀粉半互穿网络水凝胶溶胀和降解的影响

以4,4′-二甲基丙烯酰胺基偶氮苯(BMAAB)为交联剂,制备了丙烯酸-丙烯酰胺-甲基丙烯酸酯共聚物和直链淀粉半互穿网络水凝胶.以冷冻干燥和空气干燥两种方式,研究了干凝胶在pH2.2和pH7.4时的溶胀和降解性能.结果表明采用两种干燥方式的凝胶在不同pH的介质中都遵循二级溶胀动力学.凝胶内部水的扩散均为非Fickian机理,即扩散和链松弛协同作用的机理.但经历冷冻干燥的凝胶其扩散机制占优势.在pH=7.4的介质中,冷冻干燥凝胶的平衡溶胀比(SR)显著增大,而在pH=2.2时则无明显变化.扫描电镜(SEM)和降解实验发现,在结肠内容物的作用下,冷冻干燥凝胶在5天内降解率可达35.3%,而空气干燥凝胶的降解率为28.1%,表明冷冻干燥的方式可在一定程度上促进凝胶在结肠环境下的降解.     

聚乙二醇相对分子质量及用量对温敏型PCL-PEG-PCL水凝胶的制备及释药性研究

采用开环聚合法制备PCL-PEG-PCL共聚物,并将其制成温敏性水凝胶,探究了PEG(聚乙二醇)相对分子质量及质量浓度对水凝胶温敏性的影响.水凝胶的相变温度由翻转小瓶法测定.通过FTIR、热分析仪和SEM等技术对其组成及结构进行表征.以疏水性姜黄素(Cur)为模型药物,制备出载Cur PCL-PEG-PCL水凝胶,并研究其体外释药行为.FTIR结果表明:实验制备的共聚物中含有PCL和PEG的链段.热分析结果表明:在25℃~65℃内水凝胶存在相变过程.SEM结果表明:水凝胶剖面具有疏松多孔.体外释药结果表明:PCL-PEG-PCL水凝胶对Cur具有缓释作用,释药机理符合Higuchi骨架溶蚀模型.     

纳米水凝胶合成方法的研究进展

粒径在1～1000nm范围内的纳米水凝胶可用于药物输送、医学诊断、生物传感器和生物物质分离等领域,近年来受到国内外普遍关注。本文从合成纳米水凝胶的原料入手,分别从单体与交联剂聚合和聚合物后交联两个方面综述了纳米水凝胶合成方法的研究进展。通过单体与交联剂聚合合成纳米水凝胶的方法主要有三种:沉淀聚合法、反相乳液聚合法和微模板聚合法。采用聚合物后交联合成纳米水凝胶的方法主要有四种:沉淀/交联法、乳化/交联法、自组装/交联法和微模板成型/交联法。另外,对这些合成方法的优缺点进行了评述,并对生物医用纳米水凝胶合成方法的研究方向提出了一些粗浅的看法。     

基于电沉积法制备海藻酸钙水凝胶的研究进展

海藻酸钙水凝胶具有高度的吸水性、生物相容性和可降解性,在组织工程领域有着十分广泛的应用。海藻酸钠溶液与钙离子的直接反应是目前制备海藻酸钙水凝胶最常用的方法。然而,该方法中的钙离子在溶液中是自由扩散的,不能控制凝胶的结构,限制了海藻酸钙水凝胶的应用。因此,如何制作特定结构的海藻酸钙水凝胶,近年来成为了研究者的研究热点。基于电沉积法制备海藻酸钙水凝胶,可以控制钙离子析出的数量和位置,能够得到任意结构的海藻酸钙水凝胶。本文综述了电沉积法制作海藻酸钙水凝胶的原理,讨论影响电沉积法成胶的因素,对电沉积法的应用与发展进行概述和展望。     

温敏性纤维素/聚N-异丙基丙烯酰胺复合水凝胶的固体核磁共振表征及动力学研究

利用半互穿网络方法将具有温度响应的高分子聚N-异丙基丙烯酰胺(PNIPAM)与天然纤维素复合得到温敏性水凝胶. 通过固体核磁共振的 ¹H, ¹³C CP/MAS(交叉极化/魔角旋转)和QCP(定量交叉极化)等实验手段对复合凝胶的结构进行了定性及定量研究, 并利用固体静态变温核磁共振实验和偶极滤波-自旋扩散实验研究了复合凝胶中PNIPAM分子链段的动力学行为.     

三维生物高分子/氧化石墨烯复合凝胶对阳离子染料吸附的研究

采用一种简便的方法制备了生物高分子调控的氧化石墨烯凝胶用于水污染处理.将生物高分子白蛋白(BSA)、壳聚糖(CS)、及脱氧核糖核酸(DNA)与氧化石墨烯(GO)共混,自组装形成水凝胶,最后冻干得到生物高分子/氧化石墨烯复合凝胶.通过扫描电镜、原子力显微镜、纳米粒度分析仪等分析复合凝胶的组装结构与表面电位.结果表明凝胶呈现内部联通的三维多孔结构,该结构有利于被吸附分子的快速内部扩散.红外光谱证明了生物高分子被成功负载到了凝胶网络中.然后将该复合凝胶用于阳离子染料的吸附,吸附实验表明这类生物高分子/氧化石墨烯复合凝胶对阳离子染料有很好的吸附效果,同时也对阴离子和非离子毒性分子有一定的吸附能力.研究了吸附时间,初始浓度,pH值等对凝胶吸附量的影响,并考察了凝胶的解吸附.最后详细探讨了GO-BSA、GO-CS和GO-DNA凝胶对亚甲基蓝(MB)吸附的动力学和吸附等温式.经吸附动力学拟合,生物高分子/氧化石墨烯复合凝胶吸附MB复合二级动力学模型和Langmuir等温吸附,对MB分子是单分子层吸附,吸附初期为大孔隙扩散,后期为粒子内扩散.     

半互穿海藻酸钠/聚丙烯酰胺凝胶吸附结晶紫动力学/热力学行为和吸/脱附机理

将含有大量—COO-的聚阴离子海藻酸钠(SA)引入聚丙烯酰胺(PAM)凝胶网络中,采用自由基溶液聚合法制备半互穿网络结构的SA/PAM水凝胶.采用扫描电子显微镜(SEM)、X射线光电子能谱(XPS)和傅里叶变换红外光谱(FTIR)分析了SA/PAM水凝胶吸附结晶紫(CV)前后的孔洞形态和化学组成变化,采用多种模型研究了SA/PAM水凝胶对CV分子的吸附动力学和热力学行为,并探讨了脱附效率,提出了吸脱附机理.研究结果表明,SA的引入降低了孔径尺寸,增加了孔洞数量;SA/PAM-10凝胶对CV分子吸附量最大,达到13.5838 mg/g,符合伪一级吸附动力学模型,吸附速率受膜扩散和粒子内扩散过程共同影响;等温吸附过程符合Temkin和D-R模型,属于微孔多层吸附;热力学分析结果表明,吸附过程由熵驱动引起,非化学诱导因素影响所致;采用HCl进行脱附,最大脱附率高达94.18%,加入Na OH可实现SA/PAM水凝胶的可逆吸附;较高的吸附量主要源于SA分子链上的COO-与CV分子的—C N+—存在的静电作用,低pH值时由于—COO-和—NH2质子化导致与CV分子的静电斥力增大,脱附率随之增加.     

用于聚合物溶液扩散系数计算的活度系数模型比较

用40个聚合物溶液体系的实验数据,对三个有代表性的活度系数模型用于计算联系自扩散系数和互扩散系数的热力学因子的精度进行了比较,结果表明三个模型的精度相近,误差一般在20％左右。,因而本工作揭示了聚合物溶注保由自扩散系数计算与扩散系数的一个潜在问题。即由于活度系数模型计算热力学因子误差较大所带来的较大不确定性。     

Kinetic models for the SR1500 and LY556 epoxies under manufacturer’s recommended cure cycles

The kinetic behaviours of two commercial epoxy resin systems subjected to manufacturer’s recommended cure cycles (MRCC) were studied in detail. The two systems were characterized through differential scanning calorimetry (DSC) using both isothermal and dynamic test conditions. The kinetic parameters were determined and two original kinetic models were established for these resin systems subjected to the “real” processing conditions. In this paper the experimental procedure is described, together with its results and the original kinetic models developed.     

Flow injection analysis simulations and diffusion coefficient determination by stochastic and deterministic optimization methods

Stochastic and deterministic simulations of dispersion in cylindrical channels on the Poiseuille flow have been presented. The random walk (stochastic) and the uniform dispersion (deterministic) models have been used for computations of flow injection analysis responses. These methods coupled with the genetic algorithm and the Levenberg–Marquardt optimization methods, respectively, have been applied for determination of diffusion coefficients. The diffusion coefficients of fluorescein sodium, potassium hexacyanoferrate and potassium dichromate have been determined by means of the presented methods and FIA responses that are available in literature. The best-fit results agree with each other and with experimental data thus validating both presented approaches.     

Understanding the effects of diffusion coefficient and exchange current density on the electrochemical model of lithium-ion batteries

The diffusion coefficient and exchange current density are the two dominant parameters that determine the electrochemical characteristics of the electrochemical battery model. Nevertheless, both parameter values are generally adopted from well-known literature or experimental data measured under limited conditions and are sometimes overfitted to match actual electrochemical behaviors without full consideration. Herein, the diffusion coefficients and exchange current densities of a LiNi_0·4Mn_0·3Co_0·3O₂/Li cell are measured and applied to the electrochemical model (based on Newman's model) using four different electrochemical methods: galvanostatic intermittent titration technique (GITT), potentiostatic intermittent titration technique (PITT), electrochemical impedance spectroscopy (EIS), and cyclic voltammetry (CV). Without any fitting, the model adopting the diffusion coefficient and exchange current density measured from PITT and EIS, respectively, simulates the actual voltage–capacity profiles well. Thus, this case study provides a valuable opportunity to understand the advantages and disadvantages of each measurement method in obtaining key experimental parameters for electrochemical battery models.     

Free-solvent model shows osmotic pressure is the dominant factor in limiting flux during protein ultrafiltration

In protein ultrafiltration (UF), the limiting flux phenomenon has been generally considered a consequence of the presence of membrane fouling or the perceived formation of a cake/gel layer that develops at high operating pressures. Subsequently, numerous theoretical models on gel/cake physics have been made to address how these factors can result in limiting flux. In a paradigm shift, the present article reestablishes the significance of osmotic pressure by examining its contribution to limiting flux in the framework of the recently developed free solvent osmotic pressure model. The resulting free-solvent-based flux model (FSB) uses the Kedem–Katchalsky model, film theory and the free solvent representation for osmotic pressure in its development. Single protein tangential-flow diafiltration experiments (30 kDa MWCO CRC membranes) were also conducted using ovalbumin (OVA, 45 kDa), bovine serum albumin (BSA, 69 kDa), and immuno-gamma globulin (IgG, 155 kDa) in moderate NaCl buffered solutions at pH 4.5, 5.4, 7 and 7.4. The membrane was preconditioned to minimize membrane fouling development during the experimental procedure. The pressure was randomly selected and flux and sieving were determined. The experimental results clearly demonstrated that the limiting flux phenomenon is not dominated by membrane fouling and the FSB model theoretically illustrates that osmotic pressure is the primary factor in limiting flux during UF. The FSB model provides excellent agreement with the experimental results while producing realistic protein wall concentrations. In addition, the pH dependence of the limiting flux is shown to correlate to the pH dependency of the specific protein diffusion coefficient.     

Phenol removal from aqueous solution by adsorption and ion exchange mechanisms onto polymeric resins

The removal of phenol from aqueous solution was evaluated by using a nonfunctionalized hyper-cross-linked polymer Macronet MN200 and two ion exchange resins, Dowex XZ (strong anion exchange resin) and AuRIX 100 (weak anion exchange). Equilibrium experimental data were fitted to the Langmuir and Freundlich isotherms at different pHs. The Langmuir model describes successfully the phenol removal onto the three resins. The extent of the phenol adsorption was affected by the pH of the solution; thus, the nonfunctionalized resin reported the maximum loading adsorption under acidic conditions, where the molecular phenol form predominates. In contrast both ion exchange resins reported the maximum removal under alkaline conditions where the phenolate may be removed by a combined effect of both adsorption and ion exchange mechanisms. A theoretical model proposed in the literature was used to fit the experimental data and a double contribution was observed from the parameters obtained by the model. Kinetic experiments under different initial phenol concentrations and under the best pH conditions observed in the equilibrium experiments were performed. Two different models were used to define the controlling mechanism of the overall adsorption process: the homogeneous particle diffusion model and the shell progressive model fit the kinetic experimental data and determined the resin phase mechanism as the rate-limiting diffusion for the phenol removal. Resins charged after the kinetic experiments were further eluted by different methods. Desorption of nonfunctionalized resin was achieved by using the solution (50% v/v) of methanol/water with a recovery close to 90%. In the case of the ion exchange resins the desorption process was performed at different pHs and considering the effect of the competitive ion Cl⁻. The desorption processes were controlled by the ion exchange mechanism for Dowex XZ and AuRIX 100 resins; thus, no significant effect for the addition of Cl⁻ under acidic conditions was observed, while under alkaline conditions the total recovery increased, specially for Dowex XZ resin.     

Chronopotentiometric method for the assessment of ionophore diffusion coefficients in solvent polymeric membranes

A chronopotentiometric method is proposed for the determination of the diffusion coefficients of free ionophores in solvent polymeric membranes. For the pH sensitive chromoionophore ETH 5294, the method was shown to give diffusion coefficients that correlate well with those assessed by both optical and chronoamperometric methods. The limit of applicability of the chronoamperometric and chronopotentiometric methods in terms of membrane composition and experimental parameters has been identified. The chronopotentiometric method was successfully used to determine the diffusion coefficients of eight ionophores and proved to be more robust and more widely applicable than the previously reported chronoamperometric and optical methods. An erratum to this article can be found at     

Filter feature selectors in the development of binary QSAR models

The application of machine learning methods to the construction of quantitative structure–activity relationship models is a complex computational problem in which dimensionality reduction of the representation of the molecular structure plays a fundamental role in predicting a target activity. The feature selection pre-processing approach has been indicated to be effective in dimensionality reduction for building simpler and more understandable models. In this paper, a performance comparative study of 13 state-of-the-art feature selection filter methods is conducted. Structure–activity relationship models are constructed using three widely used classifiers and a diverse collection of datasets. The comparative study utilizes robust statistical tests to compare the algorithms. According to the experimental results, there are substantial differences in performance among the evaluated feature selection methods. The methods that exhibit the best performance are correlation-based feature selection, fast clustering-based feature selection and the set cover method.     

Diffusional Dynamics of Cytochrome cMolecules in the Presence of a Charged Surface

A new Brownian dynamics code was developed that is capable of computing trajectories of several spherical particles in the presence of a charged planar surface. The code takes into account electrostatic, van der Waals, and hydrodynamic interactions. In this work we describe the methods used in the program and show results from calculations for cytochrome cmolecules interacting with a negatively charged lipid bilayer. This system is of particular biological interest since these molecules play a major role as electron carriers, e.g., in photosynthesis. The shape and charge distribution of cytochrome cmolecules can be well approximated as spherical particles with an embedded monopole and dipole and can therefore easily be handled by the program. That level of approximation makes it possible to study large systems with many (up to 100) particles over time scales up to milliseconds, which would be computationally too expensive using detailed atomistic models.