Switchgrass-and pine wood-derived biochars produced by fast pyrolysis were characterized to estimate the degree of thermochemical transformation and to assess their potential use as a soil amendment and to sequester carbon. The feedstocks were pyrolyzed to biochars in an auger reactor at 450, 600, and 800 °C with a residence time of 30 s. Ash contents of switchgrass and pine wood biochars varied from 13 to 22% and from 1.3 to 5.2%, respectively. Nutrients, such as N, P, K, S, Mg, and Ca, in switchgrass biochars ranged from 0.16 to 1.77%. Under combustion conditions, switchgrass chars were decomposed at lower temperatures than pine wood biochars because of the structural differences between the two feedstocks. Principal component analysis of the Fourier transform infrared (FTIR) spectra allowed for the discrimination of all biochars by significant contributions of cellulose-derived functionality at low pyrolysis temperatures, while the same analysis of the Raman spectra presented apparent separation of all biochars by two broad bands at 1587 and 1350 cm À1 . These two broad peaks were deconvoluted into pseudo-subpeaks, which revealed that the number of aromatic rings linearly increased with the pyrolysis temperature. Cross-linkages between aromatic rings were also found to increase with thermal treatment, and switchgrass biochars contained a higher number of aromatic rings and cross-linkages than pine wood biochars, which was consistent with turbostratic carbon crystallites in the X-ray diffraction (XRD) pattern.

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A novel approach for the direct detection of oxidizing agents in aqueous solution is presented using diamond-like carbon (DLC) protected waveguides in combination with attenuated total reflectance (ATR) mid-infrared spectroscopy. Pulsed laser deposition was applied to produce high-quality DLC thin films on ZnSe ATR crystals with thicknesses of a few 100 nm. Scanning electron microscopy and X-ray photoelectron spectroscopy has been used to investigate the surface properties of the DLC films including the sp(3)/sp(2) hybridization ratio of the carbon bonds. Beside excellent adhesion of the DLC coatings to ZnSe crystals, these films show high chemical stability against strongly oxidizing agents. IR microscopy was utilized to compare differences in the chemical surface modification of bare and protected ATR waveguides when exposed to hydrogen peroxide, peracetic acid, and peroxydisulfuric acid. The feasibility of DLC protected waveguides for real-time concentration monitoring of these oxidizing agents was demonstrated by measuring calibration sets in a concentration range of 0.2-10%. Additionally, principal component regression has been applied to analyze multicomponent mixtures of hydrogen peroxide, acetic acid, and peracetic acid in aqueous solution. Due to high chemical stability and accurate monitoring capabilities, DLC protected waveguides represent a novel approach for directly detecting oxidizing agents in aqueous solution with promising potential for industrial process analysis.

Hyperspectral imaging sensors are continuously enhanced by increasing spatial and spectral resolution. However, the 'curse of dimensionality' comes into effect, as the amount of acquired data increases in third order (two spatial, one spectral dimension). On top of that, the computational expense of many chemometric data evaluation techniques such as principal component analysis (PCA) rises also in third order with the data amount. Thus the need for computer memory is increased in third and the demand for computational power up to ninth order. One immediate consequence of massively increased computation times is a decreased time resolution of hyperspectral imagers, which is especially detrimental in online applications. Archiving humongous amounts of data becomes another burden. Thus it is anticipated that increased computation resources alone will not be able to facilitate fast online evaluation of hyperspectral data cubes or even to handle the acquired data. In this study, 3D wavelet transforms are used for compression of hyperspectral data cubes prior to chemometric data evaluation and/or data storage. Five different wavelet types of the Daubechies family are compared with respect to their ability to preserve relevant information in compressed data cubes. Because only relevant information has to be considered, shorter computation time and less storage space are required. By means of experimental hyperspectral data cubes it is demonstrated that additional computation expense for the 3D wavelet transform is largely overcompensated by reduced calculations necessitated by smaller data cubes. In the presented examples, computation time for a PCA could be decreased by one order of magnitude; storage space could be reduced to < 1% of the original size. It was found that the wavelet type has a major influence on the acceleration factors.

In this study, a novel chemometric algorithm for improved evaluation of analytical data is presented and applied to three spectroscopic data sets obtained by different analytical methods. This so-called secured principal component regression (sPCR) was developed for detecting and correcting uncalibrated spectral features newly emerging in spectra after finalizing the PCR calibration, which may result in major concentration errors. Hence, detection and correction of uncalibrated features is essential. Furthermore, detected uncalibrated features provide qualitative information for sensing and process monitoring applications indicating problems in the process flow. After conventional PCR calibration, sPCR analyzes measurement data in two steps: The first step investigates whether the obtained data set is consistent with the calibration model or not. If spectroscopic features are found that cannot be modeled by the principal components, they are extracted from the measurement spectrum. This corrected spectrum is then evaluated by conventional PCR. In the Experimental Section, sPCR was successfully applied to three data sets obtained by different spectroscopic measurements in order to corroborate general applicability of the proposed concept. For each data set, one of several substances was excluded from the calibration acting in the sPCR assessment as uncalibrated absorber. The test sets consisted of disturbed and undisturbed samples. A total of 109 out of 110 test samples were correctly classified as disturbed or undisturbed by an uncalibrated absorber. It was confirmed that the extracted disturbance spectra are in accordance with the spectra of the uncalibrated analytes. The concentration results obtained with sPCR were found to be equivalent to conventional PCR results in the case of undisturbed samples and more precise for disturbed samples.

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UV derivative spectroscopy is investigated for its potential in online control of various processes. One typical application is emission monitoring of several pollutants such as SO2, NO, NO2, NH3, and aromatic hydrocarbons. The proposed method gains selectivity and sensitivity by using the first and second derivative of the transmission spectrum with respect to wavelength. These derivatives are generated in an optical manner and are compared empirically for the first time with the known numerical derivative spectroscopy and conventional transmission spectroscopy. The generation of the optical derivatives is discussed. For demonstration of the feasibility, laboratory monitoring results are reported. With the use of a sample pathlength of 10 cm with this optical method, detection limits are determined to be 4 ppm, compared to 11 ppm with numerically calculated signals and 20 ppm obtained by using the transmission only. Typically a time resolution of below three minutes is achieved. Emphasis is also laid on the treatment of an observed nonlinearity by means of chemometric calibration and evaluation algorithms such as principal component regression (PCR) and partial least-squares (PLS).

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