Refine
Document Type
- Journal article (3)
Language
- English (3)
Has full text
- yes (3)
Is part of the Bibliography
- yes (3)
Institute
- Life Sciences (3)
Publisher
- American Chemical Society (1)
- MDPI (1)
- Wiley (1)
Commercially available homogenized cow- and plant-based milks were investigated by optical spectroscopy in the range of 400–1360 nm. Absorbance spectra, the effective scattering coefficient μs′, and the spectral absorption coefficient μa were recorded for 23 milk varieties and analyzed by multivariate data analysis. Cow- and plant-based milks were compared and discriminated using principal component analysis combined with a quadratic discriminant analysis. Furthermore, it was possible to discriminate the origin of plant-based milk by μa and the fat content in cow-based milk by μs′. Partial least squares regression models were developed to determine the fat content in cow-based milk. The model for μs′ proved to be the most efficient for this task with R2 = 0.98 and RMSEP = 0.19 g/100 mL for the external validation. Thus, optical spectroscopy together with multivariate data analysis is suitable for routine laboratory analysis or quality monitoring in the dairy production.
In this study a biobased polyurethane (PU) thermoset is investigated due to its turbidity. In contrary to the expectations, the turbidity increases with a higher amount of a low molecular weight crosslinker. Morphological aspects are investigated with SEM imaging and measurement of the effective scattering coefficient μ’s. FTIR spectroscopy is applied to study the influence of the chemical structure. This is combined with multivariate data analysis to identify the relevant peaks. SEM images show spherical precipitations with increasing turbidity and a simultaneous increase in the μ’s values. FTIR analysis shows a significant amount of unreacted isocyanate‐(NCO)groups and a low level of hydrogen bonding. No formation of typical hard and soft segments is detectable. Therefore, it can be concluded that the increase in polarity differences with increasing crosslinker amount disabled the mixture of the polyol and isocyanate components, resulting in the precipitation of the isocyanate. At the same time, the low molecular weight crosslinker (~200 g mol−1) can react with the NCO quickly, reducing the mobility of the polymer chain, with remaining, non‐reacted isocyanate. A proof for the correlation of the differences in the FTIR and the μ’s values was found by a regression analysis with an R2 of 0.94.
Metalworking fluids (MWFs) are widely used to cool and lubricate metal workpieces during processing to reduce heat and friction. Extending a MWF’s service life is of importance from both economical and ecological points of view. Knowledge about the effects of processing conditions on the aging behavior and reliable analytical procedures are required to properly characterize the aging phenomena. While so far no quantitative estimations of ageing effects on MWFs have been described in the literature other than univariate ones based on single parameter measurements, in the present study we present a simple spectroscopy-based set-up for the simultaneous monitoring of three quality parameters of MWF and a mathematical model relating them to the most influential process factors relevant during use. For this purpose, the effects of MWF concentration, pH and nitrite concentration on the droplet size during aging were investigated by means of a response surface modelling approach. Systematically varied model MWF fluids were characterized using simultaneous measurements of absorption coefficients µa and effective scattering coefficients µ’s. Droplet size was determined via dynamic light scattering (DLS) measurements. Droplet size showed non-linear dependence on MWF concentration and pH, but the nitrite concentration had no significant effect. pH and MWF concentration showed a strong synergistic effect, which indicates that MWF aging is a rather complex process. The observed effects were similar for the DLS and the µ’s values, which shows the comparability of the methodologies. The correlations of the methods were R2c = 0.928 and R2P = 0.927, as calculated by a partial least squares regression (PLS-R) model. Furthermore, using µa, it was possible to generate a predictive PLS-R model for MWF concentration (R2c = 0.890, R2P = 0.924). Simultaneous determination of the pH based on the µ’s is possible with good accuracy (R²c = 0.803, R²P = 0.732). With prior knowledge of the MWF concentration using the µa-PLS-R model, the predictive capability of the µ’s-PLS-R model for pH was refined (10 wt%: R²c = 0.998, R²p = 0.997). This highlights the relevance of the combined measurement of µa and µ’s. Recognizing the synergistic nature of the effects of MWF concentration and pH on the droplet size is an important prerequisite for extending the service life of an MWF in the metalworking industry. The presented method can be applied as an in-process analytical tool that allows one to compensate for ageing effects during use of the MWF by taking appropriate corrective measures, such as pH correction or adjustment of concentration.