黄藤素溶解度的测定与关联

在黄藤素的提取分离过程中,其在不同溶剂中的溶解度数据对其结晶纯化有重要的指导意义。本文以UV法测定了298.12-313．12K时黄藤素在纯水、甲醇、乙醇、三氯甲烷等不同溶剂中的溶解度数据,为黄藤素的结晶纯化提供了基础的热力学数据。试验结果表明,黄藤素在四种溶剂中的溶解度均随温度的升高而增加。对试验结果采用Apelblat方程进行拟合,其溶解度关联值与试验值比较稳合。     

氯化铷在有机溶剂中的溶解度

铷作为稀有碱金属常与钾共存,氯化铷在不同溶剂中的溶解度是对铷化合物结晶提纯的理论依据,因此,探究氯化铷在不同溶剂中的溶解规律对于实现铷钾分离具有指导意义。实验分别测定了常压条件下氯化铷在甲酸、冰乙酸、正丙醇和乙二醇中303.15—343.15 K条件下的溶解度。结果表明:氯化铷在上述4种有机溶剂中的溶解度均随温度的升高而增大,其中温度对氯化铷在甲酸中的溶解度影响最为明显;在4种溶剂中溶解度的排序为:甲酸乙二醇冰乙酸正丙醇,甲酸比较适合用于氯化铷的重结晶。同时对实验数据进行了拟合,实验数据与理论计算结果吻合,所得拟合方程可为氯化铷重结晶工艺路线的制定提供理论依据。     

甲钴胺溶解度的测定和关联

在甲钴胺的结晶分离纯化过程中,溶解度数据至关重要。本文采用静态法测定了273～335K范围内甲钴胺在溶剂——纯水、乙醇及丙酮：水=8：1的混合溶剂中的溶解度数据,为结晶方案的确定和结晶工艺条件的优化提供了基础的热力学数据。实验结果表明,甲钴胺在纯溶剂水或乙醇中的溶解度随着温度的升高而增加;此外,甲钴胺在丙酮：水=8：1混合溶剂中几乎不溶解。采用Apelblat模型和经验多项式方程关联测定结果,其溶解度关联值和实验值比较吻合。这为采用溶析结晶法分离甲钴胺提供了理论基础。     

N-（2,6-二甲苯基）-2-（1-哌嗪基）乙酰胺纯化工艺研究

N-（2,6-二甲苯基）-2-（1-哌嗪基）乙酰胺合成过程中,会同时有产品及哌嗪双取代副产物生成,通过研究两者在常规溶剂中的溶解度,利用溶解度差异,选用乙醇对产品进行纯化,革除了原有不适于工业化规模生产的乙醚重结晶纯化工艺。     

重结晶提纯碳酸二苯酯的溶剂选择

为了寻找重结晶法提纯碳酸二苯酯(DPC)的适宜溶剂,文章对DPC重结晶溶剂的选择及影响DPC纯度的因素进行了研究。结果表明:乙醇是重结晶纯化DPC的适宜溶剂,DPC在乙醇中溶解度在5—15℃的区间内变化缓慢,重结晶中止温度在15℃左右,DPC的收率高于89.0%。乙醇和DPC比率(质量比)采用8∶5为重结晶DPC时的适宜比率。通过对重结晶溶剂的进一步研究,发现采用水-乙醇的混合溶剂作为重结晶溶剂时,可以明显提高DPC的收率。水的质量分数在25.0%—35.0%范围内时,DPC的收率大于93.0%,纯度高于99.6%。其纯度符合合成聚碳酸酯的要求。     

关于麦芽酚生产中几种溶剂回收工艺的改进

麦芽酚广泛应用于日化、饮料、医药、烟、酒等精细化工领域.其合成过程为:先进行格氏试剂的合成:卤代烷及Mg在苯、四氢呋喃溶剂存在下进行反应,然后与糠醛加成,再经水解得到糠基醇中间体,将制得的糠基醇在甲醇和水为溶剂的条件下用氯气氧化,最后在酸性介质中加热水解,得到麦芽酚粗产品,将制得的粗产品在乙醇等溶剂中进行结晶和重结晶,晶体干燥后包装.     

丙交酯交替溶剂重结晶纯化法及其对聚合的影响

研究了交替溶剂重结晶丙交酯的纯化方法.首先优化了重结晶时间:在乙酸乙酯体系中,每百克溶剂中溶解丙交酯45 ~75 g,重结晶最佳时间为3~5 h;在乙醇体系中,每百克溶剂中溶解丙交酯30 ~45 g,重结晶最佳时间为1 ~3 h,结果表明,通过控制重结晶时间可达到最佳重结晶效果.以聚合效果比较了以上两种溶剂重结晶的结果,结果表明,乙醇体系重结晶率可高出乙酸乙酯体系约10%,但其纯化的丙交酯经聚合获得的产物分子量却远远低于乙酸乙酯体系.为此,采用交替溶剂重结晶法,即先使用乙醇重结晶丙交酯以获得高结晶率,再以乙酸乙酯重结晶则可在高得率的条件下获得高分子量聚丙交酯.用该法纯化得到的丙交酯经聚合后,产物的分子量可达43×104.     

纯度标准物质HMX的制备及均匀性检验

以工业特级品HMX为基体,研究了HMX的纯化工艺,制备出军用纯度标准物质HMX.考察了用不同溶剂重结晶对HMX纯度的影响,选择用两种重结晶方法、分三步操作纯化HMX:首先用二甲基亚砜作溶剂,80℃溶解HMX,趁热过滤除去无机杂质和机械杂质后,用溶剂-非溶剂沉淀技术使HMX结晶析出;第二步以乙腈为溶剂重结晶纯化HMX,HMX的纯度达到99.60%以上;最后用MOS级无水乙醇煮洗,进一步去除有机杂质和溶剂残留.液相色谱分析、X射线粉末衍射分析和均匀性研究结果表明,所制备的纯度标准物质HMX纯度不小于99.70%,晶型为β型并且均匀性良好.     

β-蒿甲醚在五种有机溶剂中溶解度的测定与关联

采用重量法测量了288.35～322.75 K温度范围内β-蒿甲醚在正丙醇、异丙醇、丙酮、乙酸乙酯及N, N-二甲基甲酰胺中的溶解度.结果表明β-蒿甲醚在五种有机溶剂中的溶解度均随温度的升高而增大,但在不同的溶剂中溶解度及其温度敏感性存在一定差异,在N,N-二甲基甲酰胺、乙酸乙酯和丙酮中的溶解度相对较大,而在正丙醇和异丙醇中的溶解度相对较小但对温度比较敏感.采用经验方程和理想溶液模型对实验数据进行了关联,计算值与实验值吻合良好.上述结果可为蒿甲醚结晶过程溶剂选择提供基础数据.     

环氧树脂固化剂2—甲基咪唑的纯化

本文用重结晶法对环氧树脂固化剂２－甲基咪唑进行纯化，重点讨论了纯化过程中溶剂选择和溶剂用量确定两个问题，并对产物质量进行了标定。     

MEASUREMENT AND CORRELATION OF TAXOL SOLUBILITY IN METHANOL,ETHANOL AND METHANOL-WATER SYSTEMS

Taxol is a unique antitumor drug that appears to exert its activity as a result of interference with microtubular structure and function. The Taxol solubility of in methanol, ethanol and methanol-water was measured by the equilibrium method in this paper. The data obtained were correlated by the regress equation and ANN model. The results showed that the both were in excellent agreement with the experimental data and the ANN model was more convenient than the regress equation.     

UNIFICATION OF FRUIT WATER SORPTION ISOTHERMS USING ARTIFICIAL NEURAL NETWORKS

The chemical composition, water activity, temperature and equilibrium moisture content (EMC) for 10 selected fruits were determined. Two methods of water sorption modeling, the GAB equation and the artificial neural network (ANN) method, were compared for their ability to predict water sorption behavior. Unlike the GAB equation, which uses only physical data for modeling, the ANN method uses both physical and chemical compositional data to make predictions. The ANN was superior, in most cases, to that of the GAB equation, in predicting EMC. This superiority was due to the availability of the additional chemical compositional information. The ANN method could predict EMC with a mean relative error of 9.85% and a standard error (S_x) of 1.59% EMC. The correlation coefficient (r²) of the relationship between the actual and predicted values of equilibrium moisture content obtained by the ANN was 0.9938. The ANN model was able to show a temperature dependent crossing of water sorption isotherms, due to the dissolution of sugar crystals in the fruit. The ANN was also able to predict the extent of crossing, depending upon differences in the individual fruit chemical composition.     

基于纯二次模型的单基发射药贮存寿命预测

利用MATLAB软件分别得到不同地区库存单基发射药贮存寿命与温湿度关系的拟合曲线,发现拟合曲线符合二次模型.利用环境特征相对典型地区的温湿度数据,建立了纯二次回归模型,得到贮存寿命与温湿度的回归方程.回归方程的剩余标准差和残差极小,表明拟合效果非常好,能够较准确预测不同温湿度条件下单基发射药的安全贮存寿命.     

UNIFICATION OF FRUIT WATER SORPTION ISOTHERMS USING ARTIFICIAL NEURAL NETWORKS

The chemical composition, water activity, temperature and equilibrium moisture content (EMC) for 10 selected fruits were determined. Two methods of water sorption modeling, the GAB equation and the artificial neural network (ANN) method, were compared for their ability to predict water sorption behavior. Unlike the GAB equation, which uses only physical data for modeling, the ANN method uses both physical and chemical compositional data to make predictions. The ANN was superior, in most cases, to that of the GAB equation, in predicting EMC. This superiority was due to the availability of the additional chemical compositional information. The ANN method could predict EMC with a mean relative error of 9.85% and a standard error (S _x ) of 1.59% EMC. The correlation coefficient (r ²) of the relationship between the actual and predicted values of equilibrium moisture content obtained by the ANN was 0.9938. The ANN model was able to show a temperature dependent crossing of water sorption isotherms, due to the dissolution of sugar crystals in the fruit. The ANN was also able to predict the extent of crossing, depending upon differences in the individual fruit chemical composition.     

2,4-二氯苯酚在水中溶解度的测定及关联

在pH值为6.2或9.3条件下,采用综合法测定了2,4-二氯苯酚在水中的固液平衡数据,分别用经验方程、W ilson方程、固液平衡λH方程对实验数据进行了拟合处理。结果说明,在pH值为9.3条件下,2,4-二氯苯酚的水溶解度增大;W ilson方程、λH方程模型均能很好地关联2,4-二氯苯酚的水溶解度数据,pH=9.3时平均相对误差分别为3.00%,1.17%,其中λH方程拟合效果更好。     

An Artificial Neural Network Model for Prediction of Drying Rates

Drying rate data were generated for training of an ANN model using a liquid diffusion model for potato slices of different thicknesses using air at different velocities, humidities and temperatures. Moisture content and temperature dependence of the liquid diffusivity as well as the heat of wetting for bound moisture were included in the diffusion model making it a highly nonlinear system. An ANN model was developed for rapid prediction of the drying rates using the Page equation fitted to the drying rate curves. The ANN model is verified to provide accurate interpolation of the drying rates and times within the ranges of parameters investigated.     

咖啡因在水和乙醇中的溶解度及其关联

The solubility of caffeine in water and ethanol at 0—50 ℃ was measured using the laser method. The results were regressed with an empirical equation and simplified EOS correlation. A 2 - 2 - 1 backpropagation (BP) artificial neural network (ANN) model was selected from many other models. The prediction of interpolation and extrapolation of the data was made with trained 2 - 2 - 1 BP ANN model. The result was satisfactory.     

An Artificial Neural Network Model for Prediction of Drying Rates

Abstract

Drying rate data were generated for training of an ANN model using a liquid diffusion model for potato slices of different thicknesses using air at different velocities, humidities and temperatures. Moisture content and temperature dependence of the liquid diffusivity as well as the heat of wetting for bound moisture were included in the diffusion model making it a highly nonlinear system. An ANN model was developed for rapid prediction of the drying rates using the Page equation fitted to the drying rate curves. The ANN model is verified to provide accurate interpolation of the drying rates and times within the ranges of parameters investigated.     

苊冷却结晶动力学的间歇动态法研究

通过添加晶种的间歇冷却结晶实验研究了苊在乙醇中的结晶动力学。由苊晶体的粒数密度数据,通过矩量变换法按粒度无关生长模型求解粒数衡算方程,采用多元线性最小二乘法回归动力学数据,得到苊在乙醇中晶体生长及成核速率方程。对动力学方程的理论分析表明:搅拌速率对二次成核影响显著,随搅拌速率增加,晶体的成核速率明显增加。同时适宜的过饱和度及较低的悬浮密度,有利于苊晶体生长。该研究为苊冷却结晶特性的辨识、粒度分布的控制及工业放大提供了重要的理论指导。     

基于神经网络-遗传算法优化生物柴油制备工艺

根据生物柴油制备的实验数据,用人工神经网络(ANN)的反向传播(BP)算法建立了生物柴油转化率神经网络预测模型,提出了适宜的人工神经网络拓扑结构,讨论了BP算法中学习速率、动量系数及过拟合现象对网络的影响。实验数据检验表明,ANN方法能准确地关联生物柴油制备工艺条件与转化率的关系,转化率预测平均相对误差为1.917%,复相关系数R为0.9996;该神经网络预测模型用遗传算法优化,得到了最佳生物柴油制备条件。