铁氰化钾分光光度法测定药物中维生素B_1含量

在NaOH碱性介质中,维生素B1能将K3[Fe(CN)6]定量还原为K4[Fe(CN)6],根据Fe3+与K4[Fe(CN)6]反应生成可溶性普鲁士蓝的吸光度值,可间接测定出维生素B1的含量。在选定条件下,维生素B1在0.40~15.0mg·L-1范围内与吸光度(A)呈线性关系,相关系数R=0.9989,检出限为0.12mg·L-1,相对标准偏差(RSD)为1.75%(n=6)。表观摩尔吸光系数ε=4.3×104 L·mol-1·cm-1。该方法可用于药物中维生素B1含量的测定。     

固蓝盐B分光光度法测定药物中抗坏血酸

探讨了一种简便的选择性高的药物中抗坏血酸的测定方法。该方法是基于在酸性介质中抗坏血酸和固蓝盐B的反应,产物的最大吸收为420nm.摩尔吸光系数为1.31×10~4L·mol~(-1)·cm~(-1).方法已应用于某些药物中抗坏血酸的测定,结果与碘量法一致,回收率为98.4％～105％,相对标准偏差低于3.7％。     

菲林B近红外分光光度法测定维生素C

在pH 3的三氯乙酸酸性介质中,菲林B可以定量地将还原型维生素C氧化成脱氢型维生素C,利用脱氢型维生素C在920 nm处有最大吸光度,测定其含量,建立了一种测定维生素C的新方法,并研究了影响反应的各种因素。该方法对维生素C的检出限为0.17 mg/L;线性范围为0.5~10 mg/L,对水果中维生素C含量测定的RSD<2.31%;回收率为99.7%~101.1%,比2,4-二硝基苯肼分光光度法测定结果的相对偏差<±1.6%。     

液相色谱法测定多元维生素片中4种水溶性维生素

采用高效液相色谱法测定多元维生素片中盐酸硫胺(B1)、核黄素(B2)、泛酸钙(B5)、盐酸吡哆醇(B6)的含量。重点考察了提取条件对于维生素测定的影响,4种维生素在确定的浓度范围内分别与色谱峰面积呈良好的线性关系,r2≥0.9999,加标回收率为99.2%～101.4%。4种维生素的检出限分别为0.30、0.19、0.45、0.11μg/g(S/N10)。该方法可作为实际测试标准方法使用。     

分光光度法直接测定天然水中微量钼

本文研究了罗丹明B与硫氰酸钼形成红色络合物的问题,提出了分光光度法直接测定天然水中微量钼的新方法,方法灵敏(_600~ε=1.88×10~5)干扰少,相对标准偏差小于7%。检出限为2ppb。     

维生素B1-钼酸铵荧光光度法的研究与应用

1引言 维生素B1是人体维持正常代谢和机能必需的物质.用荧光光度法测定维生素B1的研究较为广泛.但因维生素B1的特殊性质,文献已报道的氧化测定体系,有的操作要求严格、繁琐;有的试剂毒性大,给环境带来污染;有的氧化时间较长,并需在沸水浴中加热.本文研究了钼酸铵与维生素B1的荧光反应,该氧化测定体系操作简便、快速,荧光强度稳定,测定线性范围宽,试剂无毒性.应用该方法测定了药品中的维生素B1,结果令人满意.     

高灵敏度分光光度法测定痕量 Zn(Ⅱ) 的研究

研究了 Zn( ) - SCN-- Rh B- PVA高灵敏度显色反应体系 ,建立了光度法测定矿泉水中痕量 Zn( )的新方法。结果表明 ,在盐酸介质锌 -罗丹明 B络合物的表观摩尔吸光系数为 1 .58× 1 0 6L·mol-1·cm-1,Zn( )的质量浓度在0～ 2 .0 μg/ 50 m L范围内服从比尔定律。本方法已用于测定饮用水中总 Zn     

利血平与玫瑰精B的高灵敏显色反应及分析应用

研究了利血平与玫瑰精B的显色反应,建立了测定利血平的高灵敏分光光度法。在酸性条件下,利血平的水解产物和玫瑰精B形成具有正、负吸收峰的红色离子缔合物,最大正吸收波长位于490 nm,最大负吸收波长位于520 nm,表观摩尔吸光系数(ε)分别为1.20×105L.mol-1.cm-1(正吸收)和1.83×105L.mol-1.cm-1(负吸收),利血平在0～5.0μg/mL范围内遵从比尔定律。若采用正、负峰叠加测定,灵敏度可达3.00×105L.mol-1.cm-1。探讨了适宜的反应条件、主要分析特性及方法的精密度和可靠性。该法可用于市售利血平注射液中利血平含量的测定。     

过氧化氢氧化-荧光分光光度法测定片剂中叶酸含量

1　引　　言作者曾开发出ＫＭｎＯ4 氧化 荧光分析法测定片剂中叶酸 (ＰＧＡ)含量的荧光新体系。该法通过测定ＰＧＡ的氧化产物蝶呤 6 羧酸的荧光强度 ,间接测定了ＰＧＡ的含量。考虑到用Ｈ2 Ｏ2 氧化ＰＧＡ ,分析其氧化产物蝶呤 6 甲醛的结构 ,也是强荧光性物质 ,也有可能用荧光测定法。为此本文详细研究了在ＮａＡｃ ＨＡｃ和ＮＨ4 Ｃｌ ＮＨ3·Ｈ2 Ｏ不同缓冲溶液中Ｈ2 Ｏ2 氧化ＰＧＡ的最佳条件和荧光特性 ,ＰＧＡ的检测限分别为 5 .2 μｇ/Ｌ(ｐＨ 5 .0 )、6.8μｇ/Ｌ (ｐＨ 10 .5 0 ) ,前者最佳ｐＨ范围较宽 ,抗干扰能力也明显强于…     

乙基罗丹明B-锗钼杂多酸-聚乙烯醇超高灵敏显色反应的研究

研究了乙基罗丹明B锗钼杂多酸聚乙烯醇(PVA)显色体系的形成条件,建立了测定痕量锗的超高灵敏分光光度法。由于形成吸附型缔合物,其表观摩尔吸光系数高达5.44×106L·mol-1·cm-1。缔合物组成比为Ge(Ⅳ)∶ERB+=1∶11,最大吸收波长位于584nm。方法已用于人参中痕量锗的测定,获得满意结果。     

A comparative study of laser induced breakdown spectroscopy analysis for element concentrations in aluminum alloy using artificial neural networks and calibration methods

A comparative study of analysis methods (traditional calibration method and artificial neural networks (ANN) prediction method) for laser induced breakdown spectroscopy (LIBS) data of different Al alloy samples was performed. In the calibration method, the intensity of the analyte lines obtained from different samples are plotted against their concentration to form calibration curves for different elements from which the concentrations of unknown elements were deduced by comparing its LIBS signal with the calibration curves. Using ANN, an artificial neural network model is trained with a set of input data of known composition samples. The trained neural network is then used to predict the elemental concentration from the test spectra. The present results reveal that artificial neural networks are capable of predicting values better than traditional method in most cases.     

人工神经网络在纸浆卡伯值光学定量分析中的应用

卡伯值 (硬度 )是纸浆的重要质量指标 ,是制浆过程控制的关键参数 .目前的测量方法包括化学分析法和光学分析法两大类型 ,国内大多数的制浆造纸厂采用离线的传统化学分析法来测定纸浆的卡伯值 ,需要比较长的时间 .而光学分析法因具有实时性好、精度和可靠性高等优点 ,已逐步用于卡伯值的在线测量和控制 .研究 [1] 发现 ,在 460～ 580 nm的可见光谱范围内 ,蒸煮液吸光度的变化可以表征纸浆中木素含量的变化 .本文将可见分光光谱技术应用于蒸煮液中木素含量的在线测量 ,根据蒸煮液在所选波段的吸光度来预测纸浆的卡伯值 ,建立纸浆卡伯值与蒸煮…     

烃类混合气体的神经网络模型检测

八十年代末科学家模仿生物鼻研制一种传感器阵列与计算机模式识别的气体检测系统．传感器阵列相当于生物鼻的嗅觉细胞，计算机模式识别系统相当于嗅泡和大脑「‘］．传感器阵列对气体的响应是一个多维空间的响应模式，这种响应模式经过一定的数学处理后可以实现气体的种类识别或浓度检测［’－‘j．传感器的响应和混合气体浓度之间呈非线性关系，这一特性给定量检测多组分气体混合物造成很大的限制．应用人工神经元网络技术（ANN）可以克服这一缺陷，并使检测气体的选择性大大提高．本工作运用ANN中的反向传播（BP）算法识别由16个不同…     

人工神经网络紫外分光光度法测定息喘灵片多组分体系的研究

介绍了人工神经网络（ＡＮＮ）原理，详细讨论了网络参数的选择及其对预报的影响。将该技术应用于息喘灵片三组分体系的预报测定并取得满意结果。     

Usage of Artificial Neural Network (Back Propagation) in Optimising Salicylic Acid Determination with Ferric(III) Nitrate

Abstract

The use of artificial neural networks (ANN) in optimizing salicylic acid (SA) determination is presented in this paper. A simple and rapid spectrophotometric method for salicylic acid (SA) determination was carried out based on the complexation of salicylic acid–ferric(III) nitrate, SAFe(III). The SA forms a stable purple complex with ferric(III) nitrate at pH 2.45. The useful dynamic linear range is 0.01–0.35 g/L. It has a maximum absorption at 524 nm and the stability is more than 50 hours. The results were used for artificial neural networks (ANNs) training to optimize data. For training and validation purposes, a back‐propagation (BP) artificial neural network (ANN) was used. The results showed that ANN technique was very effective and useful in broadening the limited dynamic linear response range mentioned to an extensive calibration response (0.01–0.70 g/L). It was found that a network with 22 hidden neurons was highly accurate in predicting the determination of SA. This network scores a summation of squared error (SSE) skill and low average predicted error of 0.0078 and 0.00427 g/L, respectively.     

Simultaneous determination of composition of human urinary calculi by use of artificial neural networks

A new chemometric method, which uses artificial neural networks (ANN), is presented for determination of the composition of urinary calculi. The selected constituents were whewellite, weddellite, and uric acid from which approximately 40% of the urinary calculi obtained from Macedonia patients are composed. The results for the synthetic mixtures were better then those obtained by partial least squares (PLS) regression or by the principal component regression (PCR), because neural networks have better prediction capacity. The generalization abilities of the optimized neural networks were checked using the standard addition method on carefully selected real natural samples.     

模式识别用于压电晶体传感器阵列定量检测有机蒸汽混合物

本文应用9个压电晶体组成传感器阵列, 每片晶体上分别涂有不同种类的冠醚衍生物, 用它来定量检测二元及三元有机蒸汽混合物, 在数据处理中比较了两种模式识别方法---偏最小二乘法(PLS)和人工神经网络法(ANN), 实验证明, ANN法在预测准确度上明显优于PLS法, 本文还讨论了解决神经网络训练过拟合现象的方法。     

神经网络方法在血管紧张素转换酶抑制剂定量构效关系建模中的应用

对20个ACEI化合物用量子化学方法进行结构优化并计算出10个参数,用9种不同隐含层节点数的BP神经网络研究了ACEI的定量构效关系,建立了节点为10/6/1的三层BP神经网络模型。结果表明:以量化理论计算所得参数可以构建合理的ACEI定量构效关系模型,神经网络模型M6的r2=0.995,S=0.050,6个验证集化合物的残差平方和为0.002,预测能力明显强于多元线形回归模型,亦优于同类文献报道,可作为ACEI研发领域中预测先导化合物活性的理论工具。     

Energy analysis of a domestic refrigerator system with ANN using LPG/TiO2–lubricant as replacement for R134a

Journal of Thermal Analysis and Calorimetry - This paper experimentally investigated and also modeled using artificial neural networks (ANN) approach the energy analysis of a domestic refrigerator...     

Identification of combustible material with piezoelectric crystal sensor array using pattern-recognition techniques

A promising way of increasing the selectivity and sensitivity of gas sensors is to treat the signals from a number of different gas sensors with pattern recognition (PR) method. A gas sensor array with seven piezoelectric crystals each coated with a different partially selective coating material was constructed to identify four kinds of combustible materials which generate smoke containing different components. The signals from the sensors were analyzed with both conventional multivariate analysis, stepwise discriminant analysis (SDA), and artificial neural networks (ANN) models. The results show that the predictions were even better with ANN models. In our experiment, we have reported a new method for training data selection, 'training set stepwise expending method' to solve the problem that the network can not converge at the beginning of the training. We also discussed how the parameters of neural networks, learning rate eta, momentum term alpha and few bad training data affect the performance of neural networks.