盐酸帕罗西汀杂质亚甲基双盐酸帕罗西汀的合成研究

目的:通过研究亚甲基双盐酸帕罗西汀产生的工艺条件,获得更稳定的盐酸帕罗西汀合成工艺。方法:以N-甲基帕罗西汀为原料,经取代反应、水解反应与缩合反应合成亚甲基双盐酸帕罗西汀,并对亚甲基双盐酸帕罗西汀的合成工艺条件与反应机理进行考察。结果:目标产物为亚甲基双盐酸帕罗西汀,并经HPLC与~1H NMR结构确证。结论:为制备盐酸帕罗西汀提供更加稳定的工艺条件。     

人工神经网络在半水盐酸帕罗西汀溶解度预测中的应用

溶解度的测定与预测对于多晶型体的晶体生长和结晶过程中的多晶型控制至关重要.利用激光监视装置,首次测得了半水盐酸帕罗西汀在不同溶剂体系中的溶解度,共计308组数据;采用多参数人工神经网络模型,随机选取308组数据中的184组数据进行人工神经网络的训练,考察了不同隐含层节点数对神经网络训练效果的影响,得到了优化后的人工神经网络模型,利用剩余的124组数据对优化后的模型进行检测,平均预测误差小于0.7％.预测结果表明,优化后的人工神经网络模型可以胜任半水盐酸帕罗西汀溶解度预测的任务.     

盐酸帕罗西汀有关物质检测方法的研究进展

盐酸帕罗西汀是选择性5-HT再摄取抑制剂,属第三代抗抑郁类新型药。主要用于治疗抑郁症、强迫症、惊恐障碍或者社交恐惧症等精神类疾病。本文对盐酸帕罗西汀有关物质的分析方法进行了综述。近年来,盐酸帕罗西汀有关物质检测常用到的方法有高效液相色谱法(HPLC)、液质联用技术(LC-MS)。随着盐酸帕罗西汀有关物质分析方法的不断完善,为其质量控制和临床应用也提供了一定的参考价值。     

3种晶型抗氧剂1010的表征

利用示差扫描量热分析(DSC)、红外光谱(IR)、粉末X射线衍射(XRD)对3种晶型抗氧剂1010进行了表征，对δ－晶型的晶体结构进行了进一步研究，指标化了该晶体的粉末X射线衍射峰，其晶体结构为四方晶系，体心点阵结构，晶胞参数为a＝1.9789nm、c＝0.8847nm，晶胞体积为V＝3.4645nm     

提高盐酸小檗碱溶解度的研究

采用不同溶剂对盐酸小檗碱进行重结晶,考察温度、时间对盐酸小檗碱重结晶的影响,得到提高盐酸小檗碱溶解度的最佳重结晶方法,通过粉末X衍射法对不同溶剂产生的盐酸小檗碱晶型进行分析,发现通过改变盐酸小檗碱的晶型可以提高其溶解度。     

β-蒿甲醚的多晶型、晶体结构解析与晶习研究

考察了不同结晶方式及条件对蒿甲醚晶型的影响,通过X射线单晶衍射和X射线粉末衍射表征,结合分子动力学模拟,利用直接空间解析方法,对所确定的β-蒿甲醚两种多晶型进行了结构分析。通过热分析考察了两种晶型的热稳定性,采用BFDH模型和AE模型,对β-蒿甲醚A晶型的理论晶习进行了模拟预测。结果表明,β-蒿甲醚两种多晶型的晶胞结构分别为单斜晶系、P21空间群和三斜晶系、P-1空间群,温度会导致β-蒿甲醚多晶型之间的可逆转变,通过模拟获得的A晶型理论晶习与实际生长情况相近。     

依鲁替尼4种晶型的制备、表征与稳定性研究

制备了依鲁替尼的4种晶型（晶型A、晶型B、晶型C和假多晶型苯甲醚溶剂化物）,采用粉末X-射线衍射分析、红外光谱分析、热分析技术对依鲁替尼4种晶型进行了固相表征,并通过混悬实验筛选出稳定晶型。结果表明,依鲁替尼4种晶型的理化性质存在明显差异,无溶剂晶型间的稳定性关系为：晶型A > 晶型C > 晶型B,晶型A为热力学稳定晶型。     

分子蒸馏技术提纯帕罗西汀碱

应用刮膜式分子蒸馏装置对帕罗西汀的提纯进行了研究。考察了多种分离工艺参数对帕罗西汀质量分数、纯度和馏出率的影响。得到了分子蒸馏技术提纯帕罗西汀的最适宜工艺条件:进料速度60 mL/h,进料温度80℃,蒸发温度163℃,蒸发压力0.1 Pa。通过对该生产过程技术经济的初步分析,以年产1000 kg帕罗西汀计算,可产生利润约7000万元。     

NAC修饰的CdS测定盐酸帕罗西汀片剂含量的研究

以N-乙酰半胱氨酸(NAC)为修饰剂,简便,无毒,快速合成了CdS量子点,并基于盐酸帕罗西汀对该量子点的荧光猝灭作用,建立了盐酸帕罗西汀片剂的含量测定方法。结果显示,在pH=7.22,Tris-HCl缓冲液浓度为0.06 mol/L,量子点浓度为0.35 mmol/L,反应25 min的最佳条件下,该系统荧光强度变化值与盐酸帕罗西汀在(0.0033~0.1810 mg/m L)范围内线性关系良好,ΔF=682.06C+19.115为线性回归方程,检测限为0.32μg/m L。结果满意。     

环氧虫啶多晶型的制备和表征

[目的]制备环氧虫啶的多晶型,并对其进行表征。[方法]采用旋蒸法成功制备环氧虫啶晶型B,通过粉末X射线衍射、差示扫描量热、热重分析、红外光谱、单晶X射线衍射和扫描电镜等对其进行表征,并对其溶解度、粉末粒度和堆密度进行了测试。[结果]晶型B为环氧虫啶与硝基甲烷以1∶1摩尔比的硝基甲烷溶剂化物,在25℃水中溶解度为1616.19 mg/L,平均粒度D_0.5为10.650μm,堆积密度为0.289 g/cm³,均比原药晶型A有所提高。[结论]通过制备晶型B,可以提高环氧虫啶的溶解度、粉末粒度和堆积密度,方便其制剂加工。     

环己烷甲酸晶体结构及生长动力学

通过熔融结晶得到高质量环己烷甲酸单晶,并首次报道采用X射线单晶衍射解析所得CCA单晶结构。环己烷甲酸晶体为单斜晶系,空间群为P2₁/c,晶胞参数为a=1.19113 nm,b=1.07421 nm,c=1.10733 nm,β=94.72°,同时利用Material Studio软件预测其晶习。利用DSC测定不同降温速率下的出晶温度与诱导期。通过热台显微镜对环己烷甲酸晶体生长进行了在线观测,对不同温度下的生长速率进行了研究,发现主要显露晶面的生长速率与过冷度为指数关系。     

计算机模拟溶剂对对苯二酚晶习的影响

针对苯二酚的单晶结构,采用BFDH和AE模型对对苯二酚的理论晶习进行了模拟,然后利用分子动力学模拟计算了对苯二酚各晶面在水溶液中与水分子的相互作用能,并利用修正的AE模型对水溶液可能出现的晶习进行了模拟计算,计算结果与实际晶习一致。     

间苯二甲酸连续多级结晶的数学模拟

以粒数衡算为基础,对间苯二甲酸精制的多级连续蒸发结晶流程建模。通过对模型预测和实测最终产品的比较,确定了间苯二甲酸在水中的结晶动力学参数,并利用所建模型和得到的结晶动力学方程分析了各种操作参数对结晶产品粒度分布的影响,提出了改善结晶产品的粒度分布的条件并实际应用于工业生产。     

1,4-二硝基咪唑的制备与晶体结构

以咪唑作为原料,经两步反应,得到1,4-二硝基咪唑,并于室温下培养出单晶。通过X射线单晶结构分析法测定其晶体结构。结果表明,晶体属于正交晶系,空间群为P212121,晶体学参数为：a=5.832 3（13）nm,b=9.562（2）nm,c=10.302（2）nm,V=574.5（2）nm3,Z=4,DC=1.828 g/cm3,F（000）=320。     

Kinetic modeling and optimization of the operating condition of MTO process on SAPO-34 catalyst

In this paper, a new kinetic model for methanol to olefin process (MTO) over SAPO-34 catalyst was developed based on data obtained from a micro catalytic reactor using appropriate reaction network. The reaction rate equation has been introduced with consideration of reaction mechanism and the parameters were optimized on the experimental data by genetic algorithm. Comparing the experimental and predicted data showed that the predicted values from the presented model are well fitted to the experimental data. Using this kinetic model, the effect of most important operating conditions such as temperature, pressure, inlet water to methanol molar ratio and methanol space–time on the product distribution, has been examined. Finally, the optimal operating conditions for maximum production of the ethylene and the propylene were introduced.     

2,4,6-三硝基间二甲苯晶体的实验研究

合成了2,4,6-三硝基间二甲苯并培养出其晶体,用X射线单晶衍射,1HNMR,MS和傅里叶变换红外光谱进行了表征.该晶体为正交晶系,属Pbcn空间群,晶胞参数为a=5.749(2)×10-10 m,b=15.043(3)×10-10 m,c=11.415(2)×10-10 m, α=β=γ=90°, V=987.20(3)×10-30 m3, Z=4,Dc=1.623 g/cm3(理论密度),最终R因子为R1=0.0359, wR2=0.1006,所有数据的R因子为R1=0.0459, wR2=0.1045.依靠相邻分子中硝基氧之间的弱相相互作用,2,4,6-三硝基间二甲苯分子连接形成二维平面结构.对该晶体进行了DSC和TG-DTG热分析,根据热分析结果提出该物质经过一步失重过程完全分解.     

Modelling of Mechanical Properties of Nanoparticle Filled Polyethylene

A continuum-mechanics approach has been applied to model the mechanical properties of high density polyethylene (HDPE) filled with differently coated SiO₂ nanoparticles. The tensile yield stress has been predicted with a finite-element model (FE-model) taking into account the microstructural features, for example, matrix, filler content, and the interphase formed around the filler. A good agreement between the experimental and modelled data has been found. Additionally, the FE-model has been compared with a semi-empirical model and an analytical model with similar input parameters to predict the composite property. It was found that all models are congruent with respect to solution space.     

Modelling of Mechanical Properties of Nanoparticle-Filled Polyethylene

A continuum-mechanics approach has been applied to model the mechanical properties of high density polyethylene (HDPE) filled with differently coated SiO₂ nanoparticles. The tensile yield stress has been predicted with a finite-element model (FE-model) taking into account the microstructural features, e.g. matrix, filler content and the interphase formed around the filler. A good agreement between the experimental and modelled data has been found. Additionally, the FE-model has been compared with a semi-empirical model and an analytical model with similar input parameters to predict the composite property. It was found that all models are congruent with respect to solution space.     

Neural network simulation for non-MSMPR crystallization

A neural network model has been developed for the simulation of steady state industrial crystallizers where, in general, the crystal size distribution cannot be described by simple mass and energy balances, i.e. they are non-MSMPR crystallizers. The model is based on fundamental equations of steady state suspension crystallization. The parameters in the nucleation rate have been chosen for the simulation of different chemicals. The particle size distribution of the product is expressed by the Rosin–Rammler equation. Different operating modes and deviations in crystal size distribution caused by the suspension being imperfectly mixed are presented by different values of modified Rosin–Rammler number. The ranges of variables in the neural network have been chosen based on data for industrial crystallizers. The dominant size of particle, and the productivity of the crystallizer can be predicted with input information. Thus, this neural network can be used for most chemicals and for different kinds of operating conditions. The results predicted with the neural network have been verified by solving the fundamental equations and by comparison with experimental data.     

Molecular Dynamic Simulation in Titanium Dioxide Polymorphs: Rutile, Brookite, and Anatase

Molecular dynamic (MD) simulations with a quantum correction were performed on the titanium dioxide polymorphs. Interatomic potential functions of our new model are composed of Coulomb, short-range repulsion, van der Waals, and Morse interactions. The energy parameters were empirically determined to reproduce the fundamental properties of rutile crystal. The optimized crystal structure of TiO₂, rutile, was in very good agreement with experimental data in the literature. For brookite and anatase, our MD simulations reproduced well the crystal structures and several physical properties, including volume thermal expansivity and bulk modulus. The present MD simulations with a new interatomic potential function and parameters successfully predicted the crystal structures of the titanium dioxide polymorphs.