Near Infrared Spectroscopy, Cluster and Multivariate Analysis—Characterisation of Silica Materials for Liquid Chromatography

Abstract

Near infrared (NIR) refl ectance spectroscopy is a well established method within the analytical chemistry and a wide range of applications, for example in the fi eld of food and pharmaceutical products, is covered. In the era of material science and nano technology, we brought together, in this feasibility study, silica chemistry with NIR. NIR, in the fi bre-optics mode, is used for morphological studies. It enables differentiation between silica materials in a three-dimensional factor-plot depending on their functionalisation and physical properties such as particle diameter and pore diameter with Q-values of 0.95 and 0.99. The well established, common reference methods for the determination of surface area and porosity are the so called Brunnauer Emmett Teller method and size-exclusion chromatography. Both methods are time-consuming and require a lot of experience. The recently elaborated NIR method offers a physicochemical quantitative description at the nano-scale level of particle size, specifi c surface area, pore diameter, pore porosity, pore volume and total porosity with high linearity of R 2 > 0.97 for calibration and r 2 > 0.98 for validation and a bias of < 2.48 × 10-14. Compared to the reference method, which enables the determination of the individual parameters with a relative standard deviation between 6 and 28%, the NIR method shows RSD% between only 0.010 and 13.7%, which means a fundamental improvevement in precision. The measurement takes only a few seconds so high sample throughput is guaranteed. The suitability of the newly established method in material science is demonstrated, as an example, on the silica stationary phases for liquid chromatography.

Fast, noninvasive and simultaneous near‐infrared spectroscopic characterisation of physicochemical stationary phases' properties: From silica particles towards monoliths

“…Differences in pore structure can be visualised by SEM. Figure 1 shows electron micrographs of nonporous, 60, 300 and 1000 silica particles [43]. Spectra are recorded in the wavenumber range from 4500 to 9996 cm -1 following the Kubelka -Munk function (f(R) = (1 -R) 2 /2R; R = I/I 0 ) [44].…”

Infrared Spectroscopy: A Novel Tool for the Physicochemical Characterization of Particulate, Monolithic and Coated Stationary Phases

“…As a selected example the 2D-cluster depicted in Fig. 2 allows the classification of pure silica, silica-C18 and aminosilica [18]. The sensitivity to differentiate between different particle sizes at consistent porosity and the sensitivity to differentiate between different porosities at consistent particle size were verified successfully in a detailed study described in [19].…”

“…A quantitative approach enables the determination of surface coverage [20] as well as particle size, specific surface area and pore structure simultaneously [18,19]. Particle size is routinely determined by electron microscopy, light scattering or the Coulter-Counter (CC) method.…”

Quantitative Determination of Fluorine Content in Blends of Polylactide (PLA)–Talc Using Near Infrared Spectroscopy

“…This quality index qualifies the calibrations using a number between 0 (useless) and 1 (ideal). When achieving a Q-value greater than 0.50, the calibration will give reliable results [28]. Outlier detection was performed by the software based on Mahalanobis distance criterion [29].…”