近红外漫反射分析技术在测定共聚聚丙烯中乙烯含量的应用

文章探讨了利用近红外漫反射分析技术快速判断共聚聚丙烯中的乙烯含量的应用。用近红外漫反射法收集了样品近红外光谱图。利用中红外方法测定共聚聚丙烯样品的乙烯含量。利用偏最小二乘法线性回归法建立了聚丙烯中聚乙烯含量的近红外光谱预测模型。将近红外法测定结果与中红外方法测定结果进行了比较,对光谱测量的重复性进行了考察。结果表明,利用近红外光谱法与中红外方法的测定结果无显著差异,近红外法具有准确,快速,操作简便和低成本等特点。     

基于近红外光谱的茶叶中粗纤维快速测定方法研究

近红外光谱技术由于其操作简单、无需前处理、不破坏样品、无需化学试剂等特点受到人们的青睐,在众多领域得到研究和应用。本文就利用近红外光谱技术快速检测茶叶中粗纤维含量的方法进行研究,首先确定了茶叶样品粉碎时的最佳颗粒度和采集样品近红外光谱时的最佳装样厚度,选用135个茶叶样品作为试验对象,结合国标方法(GB/T 8310-2013)测定样品的粗纤维含量值,利用偏最小二乘方法建立了茶叶中粗纤维含量快速测定的近红外模型,并对60个未参加建模的茶叶样品进行了预测,将模型预测结果与国标方法结果进行成对结果 t检验,统计分析结果证明近红外方法与国标方法不存在显著差异,证明了近红外光谱法在茶叶中粗纤维快速检测中应用的可行性。     

近红外技术在聚丙烯物性测试中的应用研究

介绍了近红外光谱技术在快速测定聚丙烯物性参数中的应用,通过分析化学值的性质,采用漫反射方式和偏最小二乘法（PLS）,建立了聚丙烯粉料的等规指数、熔融指数、乙烯基含量等定量分析数学校正模型并对预测效果进行了检验。近红外光谱技术具有操作简单、快速、重复性好,不污染和破坏样品等优点。     

乙烯裂解原料在线近红外光谱分析模型的建立与评价

利用近红外光谱分析技术和相关的标准分析方法分别对乙烯裂解原料PONA值进行测定,得出样品的一系列近红外光谱图和基础数据,用合适的化学计量方法建立近红外光谱图与基础数据的数学对应关系,即近红外光谱分析模型。在建立模型的基础上,采用SEC和SEP参数评价在线近红外分析仪分析结果的准确度。     

核磁共振仪在聚丙烯测定中的应用

常规的测定聚丙烯二甲苯可溶物及等规的分析方法,分析过程复杂、分析时间长、接触有毒有害的试剂较多。本文采用核磁共振仪分析聚丙烯的二甲苯可溶物及等规,样品用量少、分析速度快、操作简单并不需要接触有毒有害溶剂等优点,在聚丙烯装置中间控制样品分析时值得推广应用。     

抗冲共聚聚丙烯的组成及其结晶行为

采用二甲苯可溶物分析仪和分析型升温淋洗分级仪表征了两种二甲苯可溶物含量相近、二甲苯可溶物中乙烯含量不同的抗冲共聚聚丙烯(IPC)。利用溶解沉淀法分离出两种IPC试样的室温可溶物,得到了两个室温不溶物。采用非等温结晶和等温结晶方法研究了两种IPC原样及室温不溶物的结晶行为。采用小角X射线散射方法研究了两种IPC原样及室温不溶物的片晶厚度和长周期。结果表明:在二甲苯可溶物含量相近的前提下,二甲苯可溶物对不溶物结晶行为的影响与二甲苯可溶物中的乙烯含量有关。在二甲苯可溶物中乙烯含量较低的试样中,不溶物的结晶受可溶物的影响更明显。     

核磁共振技术在聚丙烯中二甲苯可溶物含量测定中的研究

神华包头煤化工有限责任公司在聚丙烯生产中间产品控制分析中,用核磁谱仪取代GB/T 24282-2009测定聚丙烯粉料中二甲苯可溶物含量。结果表明此方法不仅提高分析的时效性,准确性,而且使分析过程更加环保,在化工生产中值得广泛推广应用。对于使用该方法测定二甲苯可溶物含量时的不确定度因素从几个方面进行了考虑,为方法的应用提供借鉴。     

近红外漫反射分析技术在测定低密度聚乙烯密度的应用

利用近红外漫反射分析技术快速判断低密度聚乙烯密度。用漫反射法收集低密度聚乙烯样品的近红外光谱图。利用梯度柱法测定样品密度。用偏最小二乘线性回归法建立预测模型。对两种方法的结果进行比较并考察光谱测量的重复性。结果表明,近红外光谱法与梯度柱法的测定结果无显著差异。     

近红外光谱用于火箭煤油馏程测定的研究

利用近红外光谱法及标准方法对60个火箭煤油样品的馏程进行测定,采用偏最小二乘法建立模型,初馏点与10%馏程的相关系数分别达到0.9299、0.9584。用该模型对10个未知样品进行测定,近红外光谱法预测结果与实测结果相关性很好,其准确度和再现性均符合标准分析方法的要求,表明近红外光谱分析技术代替传统标准方法快速测定火箭煤油馏程是可行的。     

近红外光谱法测定汽油中的芳烃含量

研究了采用近红外光谱测定汽油中芳烃含量的方法,通过汽油单体分析法获得汽油中芳烃的基础数据。在1000～2000nm波长范围内,应用傅立叶变换近红外光谱仪,交互检验偏最小二乘法对使用的近红外光谱数据进行优化,所得校正模型对训练集样品预测的相对平均误差为0.42%,相关系数为0.9696。对未知样品将近红外预测结果与GC的测定结果进行比较,相对平均误差为0.45%。作为一种快速分析技术,近红外光谱测定汽油中芳烃含量是简便可靠的方法。     

近红外光谱技术在酚醛预浸布中的应用

为了对预浸布进行快速检测,采用近红外漫反射的方法对高硅氧/酚醛预浸布,碳/酚醛预浸布中的树脂含量、可溶树脂含量和挥发份含量进行在线监测,三项指标同时显示.通过偏最小二乘方法分别建立标准模型,用模型的评价指标评价,分析未知样品.用近红外方法在1 min之内同时分析出结果,没有破坏性.用近红外的测定结果和标准方法的测定结果相比,两者不存在显著性差异.近红外光谱的方法可以应用在酚醛预浸料生产线上.     

近红外光谱技术的定性和定量分析

近红外光谱(NIR)分析技术具有简便、快捷、低成本、无污染以及不破坏样品等优点,是近年来发展最为迅速的实用分析技术之一.从近红外光谱的原理、特点以及定性分析和定量分析应用方面进行了论述,阐述光谱解析在近红外光谱定性和定量研究中的重要作用.     

Measuring the residence time distribution in a twin screw extruder with the use of NIR‐spectroscopy

The mean residence time (MRT) and the residence time distribution (RTD) of polypropylene in a twin‐screw extruder was determined directly in‐line with the help of near infrared (NIR) spectroscopy and the use of an UV‐absorber as tracer. Different experiment alignments such as screw speed, mass throughput, back pressure as well as tracer content and their influence on MRT and RTD have been investigated. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2014 , 131, 39919.     

The use of near infrared reflectance spectroscopy in the control of flour protein content

Near infrared reflectance spectroscopy (NIR) is a rapid (50s) and non-destructive method of analysis of a wide variety of solid, semi-solid and liquid samples. Since no sample preparation is required for many sample types, particularly powders, NIR is an ideal technique for process control. The use of NIR to monitor the protein content of flour in order to optimise the milling conditions and the composition of the grist is described. Control of the blending of flours or supplementation with wheat gluten to achieve a composite flour of a given protein content is proposed.     

13C-NMR和近红外光谱研究PP序列结构

利用核磁共振碳谱和近红餐光谱法研究了聚丙烯（PP）微观序列结构，建立了精确测定PP立构规整度的近红外数学模型，该方法简便、快速、准确、重复性好，两者之间的相关性很好，尤其适用于工业生产的中间控制分析。     

Near Infrared Spectroscopy for On-line Monitoring of Alkali- Free Cloth/Phenolic Resin Prepreg During Manufacture

A NIR method was developed for the on-line monitoring of alkali-free cloth/phenolic resin prepreg during its manufacturing process. First, the sizing content of the alkali-free cloth was analyzed, and then the resin, soluble resin and volatiles content of the prepreg was analyzed simultaneously using the FT-NIR spectrometer. Partial least square (PLS) regression was used to develop the calibration models, which for the sizing content was preprocessed by 1stDER +MSC, for the volatile content by 1stDER +VN, for the soluble resin content by 1stDER +MSC and for the resin content by the VN spectral data preprocessing method. RMSEP of the prediction model for the sizing content was 0.732 %, for the resin content it was 0.605, for the soluble resin content it was 0.101 and for volatiles content it was 0.127. The results of the paired t-test revealed that there was no significant difference between the NIR method and the standard method. The NIR spectroscopy method could be used to predict the resin, soluble resin and the volatiles content of the prepreg simultaneously, as well as sizing content of alkali-free cloth. The processing parameters of the prepreg during manufacture could be adjusted quickly with the help of the NIR analysis results. The results indicated that the NIR spectroscopy method was sufficiently accurate and effective for the on-line monitoring of alkali-free cloth/phenolic resin prepreg.     

Quantitative analysis of palm carotene using fourier transform infrared and near infrared spectroscopy

β-Carotene content is usually determined by using ultraviolet (UV)-visible spectrophotometry at 446 nm. In this study, two spectroscopic techniques, namely, Fourier transform infrared (FTIR) and near infrared (NIR) spectroscopy, have been investigated and compared to UV-visible spectrophotometry to measure the β-carotene content of crude palm oil (CPO). Calibration curves ranging from 200 to 800 ppm were prepared by extracting β-carotene from original CPO using open-column chromatography. Separate partial least squares calibration models were developed for predicting β-carotene based on the spectral region from 976 to 926 cm⁻¹ for FTIR spectroscopy and 546 to 819 nm for NIR spectroscopy. The correlation coefficient (R ²) and standard error of calibration obtained were 0.972 and 25.2 for FTIR and 0.952 and 23.6 for NIR techniques, respectively. The validation set gave R ² of 0.951 with standard error of performance (SEP) of 25.78 for FTIR technique and R ² of 0.979 with SEP of 19.96 for NIR technique. The overall reproducibility and accuracy did not give comparable results to that of spectrophotometric method; however, the standard deviation of prediction was still within ±5% β-carotene content over the range tested. Because of their rapidness and simplicity, both FTIR and NIR techniques provide alternative means of measuring β-carotene content in CPO. In addition, these two spectroscopic techniques are environmentally friendly since no solvent is involved.     

Estimating the content of free fatty acids in high‐oleic sunflower seeds by near‐infrared spectroscopy

The content of free fatty acids (FFA) in vegetable oils represents an important quality factor in oil crops. The objective of the investigation was to develop a near‐infrared (NIR) calibration for estimating the FFA content in high‐oleic sunflower seeds. A sample set of different varieties from the harvest of 2004 as well as of 2005 from two locations in Germany was used; additionally seeds from 2003 were stored under unsuitable conditions to obtain samples utilised for calibration with an extended FFA range. A direct titration method for FFA determination was developed and adjusted to the official AOCS method. The modified method is sufficiently reliable, much faster than the AOCS method and therefore suitable for use in the calibration of NIR spectrometers. The developed NIR spectroscopy (NIRS) calibration was calculated with a modified partial least square algorithm, standard normal variate and detrend scatter correction and the 2^nd derivative of the spectra of ground sunflower seeds. The standard error of prediction of the validated calibration was 0.20, and the multiple coefficient of determination (RSQ_val) reached 0.94. The obtained results demonstrated clearly the efficiency and how cost effective the NIRS method is for the estimation of FFA content in sunflower seeds.     

近红外光谱技术在中草药口服液在线质量监控中的模型建立和模型转移

应用近红外光谱技术在线监测工业产品质量时,会出现环境条件变化或仪器的部件如探头或光纤更换的情况,使原模型不再具有原来的预测效果,但是完全从头开始采集数据重新建立新模型工作量大,造成原来宝贵的模型和数据的浪费。为了解决这一矛盾,本文以一种中草药口服液中多糖含量、可溶性固形物含量及pH 为研究对象,利用近红外光谱技术对其进行实时在线检测,研究了主从机分辨率不同的光谱之间的模型转移。模型转移过程利用已建模完成并成功上线应用的模型为原模型,在不能获取原主仪器和从仪器一一对应的标准标样的条件下,找到虚拟标样建立转移矩阵。以直接标准化法结合主成分分析降维作为模型转移方法,以质量指标化学参考值与预测值间的相对误差为指标筛选最佳模型。模型转移结果显示,多糖模型预测值与化学参考值间的相对误差可控制在10%以内,可溶性固形物相对误差在5%以内,pH 相对误差在3%以内。在线生产使用表明,转移的模型同原模型一样可有效应用于在线、快速对质量指标做出准确的预测。结果表明,本文提出的采用虚拟标样的模型转移方法对于无法获得主从机一一对应的标准标样的情况下的模型转移,是一个可行的有效方法。