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When size matters - near infrared reflection spectroscopy of nanostructured materials

机译:当尺寸很重要时-纳米结构材料的近红外反射光谱

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This article evaluates the applicability of near infrared (NIR) reflection spectroscopy for the physico-chemical and morphological characterisation of matter on a scale smaller than 1 micrometre (normally between 1 and 100 nanometres). The investigated materials comprise porous and non-porous silica particles, carbon based materials such as C{sub}60 fullerenes, nano-crystalline diamond (NCD) and dendrimers, all of them having diameters and/or pore sizes in the nanometre range, respectively. In case of the silica packings and differently derivatised C{sub}60 fullerenes, absorbance signals could be clearly assigned to corresponding surface modifications. Identification or classification of the material can be achieved successfully by principal component analysis. Nano crystalline diamond surfaces, whether H- or O-terminated, could be differentiated by a computed partial least squares (PLS) regression model with around 80% precision. Generations 0-7 of poly(amidoamine) (PAMAM) dendrimers with functionalised surface amine groups are characterised in respect of particle diameter and molecular weight. The established PLS models showed a standard error of prediction of only 0.43 nm and 12.30 kDa, respectively. NIR spectroscopy has developed as a flexible analytical method that can be utilized for fast, reliable and highly reproducible screening of matter even in the nanometer range.
机译:本文评估了近红外(NIR)反射光谱在小于1微米(通常在1到100纳米)范围内对物质的物理化学和形态表征的适用性。被研究的材料包括多孔和无孔二氧化硅颗粒,碳基材料(例如C {sub} 60富勒烯,纳米晶体金刚石(NCD)和树枝状聚合物),它们的直径和/或孔径分别在纳米范围内。在二氧化硅填料和衍生化不同的C {sub} 60富勒烯的情况下,可以将吸光度信号明确分配给相应的表面改性。通过主成分分析可以成功实现材料的识别或分类。纳米晶金刚石表面,无论是H端还是O端,都可以通过计算的偏最小二乘(PLS)回归模型进行区分,精度约为80%。具有官能化的表面胺基的聚(酰胺基胺)(PAMAM)树状聚合物的第0-7代在粒径和分子量方面表征。建立的PLS模型显示的预测标准误差分别仅为0.43 nm和12.30 kDa。近红外光谱技术已经发展成为一种灵活的分析方法,即使在纳米范围内,也可用于快速,可靠和高度可重复的物质筛查。

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