Nanodiamond (ND)-based polyamide (PA) 66 nanocomposite studied with infrared (IR) microscopy and time-domain nuclear magnetic resonance (TD-NMR) combined with two-trace two-dimensional (2T2D) correlation analysis.

Nanodiamond/polyamide (ND/PA) nanocomposite was examined with infrared (IR) microscopy and time-domain nuclear magnetic resonance (TD-NMR) to elucidate in detail the interphase between amino functionalized ND (ND-NH2) and PA 66. An IR image of the ND/PA nanocomposite suggested the uniform nanoscale distribution of the ND-NH2 particles thanks to the spherical shape and accessible external surface of ND terminated with reactive amino groups. On the other hand, a substantial level of change was observed in T2 decay curves when the ND-NH2 particles were incorporated in the PA 66. The fine features of the thermally induced changes in the decay curves were readily analyzed with the two-trace two-dimensional (2T2D) correlation method. The variation in the asynchronous correlation intensity indicated that the changes observed in the mechanical properties of the ND/NH2 may be attributed to the development of crosslinking between tie chains in the amorphous region via the interaction between the ND-NH2 and PA 66. Accordingly, such firm links have a substantial effect in preventing the displacement of the amorphous domain, which eventually increases the Young's modulus but reduces the ductility of the PA.

Two-trace two-dimensional (2T2D) correlation applied to a number of spectra beyond a simple pair.

The application of two-trace two-dimensional (2T2D) correlation analysis to a number of spectra consisting of more than a simple pair is explored, especially when such spectra are randomly collected without knowing the sampling order. Calculation and interpretation of 2T2D correlation spectra are briefly reviewed, and a systematic procedure to identify the set of characteristic bands, which are mutually asynchronous and least overlapped with each other, is described. 2T2D correlation is applied to individual spectra by selecting a representative reference spectrum, such as the average of the whole dataset. A slice of an asynchronous 2T2D spectrum at a characteristic band is devoid of the spectral contribution from the species represented by the band. Since 2T2D analysis may be applied to the whole set of spectra, and each 2T2D asynchronous spectrum yields a set of slices for different characteristic bands, it is possible to generate a series of 2T2D slices obtained at a given characteristic band. By applying the generalized 2D correlation or a successive 2T2D analysis to such slices, one can obtain excellent estimates of the pure component spectra of the mixture, which are comparable to the results from other curve resolution techniques.

Estimating more than two pure component spectra from only two mixture spectra using two-dimensional correlation.

A procedure is described to estimate the pure component spectra of mixtures from only a pair of available spectra even when there are more than two component species present in the system. In contrast, traditional multivariate curve resolution (MCR) technique cannot be used for such a case. The method relies on the use of two-trace two-dimensional (2T2D) correlation spectroscopy. Asynchronous 2T2D spectrum is used to identify the characteristic bands most strongly associated with the individual mixture component species. Correlation coefficients derived from the synchronous 2T2D spectrum are used to obtain a set of correlative filtering functions to distribute the spectral intensity of the average spectrum among the estimates of the pure component spectra. Efficacy of the method was demonstrated using a pair of ATR IR spectra obtained for two solution mixtures containing three main ingredients with very similar compositions. Relatively congested and overlapped spectral region was used first for the demonstration, and reasonable resolution was accomplished yielding a set of the estimates of pure component spectra with most of the expected pertinent features included. The analysis was then extended to a broader spectral region containing well-isolated spectral signatures of individual components for positive validation. While traditional MCR technique seems to perform better with a large number of spectra, this technique can be effectively used in conjunction with MCR to improve its stability and performance, especially under some challenging conditions.

Rapid and Accurate Approach for Honeybee Pollen Analysis Using ED-XRF and FTIR Spectroscopy.

Since honeybee pollen is considered a "perfectly complete food" and is characterized by many beneficial properties (anti-inflammatory, antioxidant, anti-bacterial, etc.), it has begun to be used for therapeutic purposes. Consequently, there is a high need to develop methods for controlling its composition. A thorough bee pollen analysis can be very informative regarding its safety for consumption, the variability of its composition, its biogeographical origin, or harvest date. Therefore, in this study, two reliable and non-destructive spectroscopy methods, i.e., ED-XRF and ATR-FTIR, are proposed as a fast approach to characterize bee pollen. The collected samples were derived from apiaries located in west-central Poland. Additionally, some commercially available samples were analyzed. The applied methodology was optimized and combined with sophisticated chemometric tools. Data derived from IR analyses were also subjected to two-dimensional correlation spectroscopy. The developed ED-XRF method allowed the reliable quantification of eight macro- and micro-nutrients, while organic components were characterized by IR spectroscopy. Principal component analysis, cluster analysis, and obtained synchronous and asynchronous maps allowed the study of component changes occurring dependently on the date and location of harvest. The proposed approach proved to be an excellent tool to monitor the variability of the inorganic and organic content of bee pollen.

Detection of adulterants in dietary supplements with Ginkgo biloba extract by attenuated total reflectance Fourier transform infrared spectroscopy and multivariate methods PLS-DA and PCA.

The infrared spectroscopy with attenuated total reflectance (ATR) sampling coupled with chemometric methods has been applied to non-destructive detection of adulterants in dietary supplements containing Ginkgo biloba extract. The sample set comprised the spectra of six drugs and sixteen dietary supplements with ginkgo leaf extract. Spectral data (900-1800 cm-1) were analyzed using multivariate partial least squares regression combined with a discriminant analysis (PLS-DA). The second derivative of spectra followed by mean centering was used as pre-processing method. Three models were constructed and validated for detection of potential adulterants: kaempferol, quercetin, and rutin. The iPLS-DA classification models achieved about 87.5%, 93,7%, and 87,5% of correct classification for adulteration with kaempferol, quercetin and rutin, respectively. The results obtained from classification models were verified by chromatographic fingerprints of unhydrolyzed sample extracts. Two-trace two-dimensional asynchronous correlation maps were constructed from pairs of spectra (each dietary supplement spectrum vs. averaged spectrum of drugs) and then analyzed by multiway PCA which revealed good discrimination between samples.