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In this paper the concept of a compact high-resolution spectrometer based on the combination of dispersive and interferometric elements is presented. Dispersive elements are used to spectrally resolve the light in one direction with coarse resolution (Delta lambda < 0.5 nm), while perpendicular to that direction an etalon provides high spectral resolution (Delta lambda < 50 pm). This concept for two-dimensional spectroscopy has been implemented for the wavelength range lambda = 350-650 nm. Appropriate algorithms for reconstructing spectra from the two-dimensional raw data and for wavelength calibration were established in an analysis software. Potential applications for this new spectrometer are Raman and laser-induced breakdown spectroscopy (LIBS). Resolutions down to 28 pm (routinely 54 pm) could be realized for these applications.
A promising replacement for the radioactive sources commonly encountered in ion mobility spectrometers is a miniaturized, energy-efficient photoionization source that produce the reactant ions via soft X-radiation (2.8 keV). In order to successfully apply the photoionization source, it is imperative to know the spectrum of reactant ions and the subsequent ionization reactions leading to the detection of analytes. To that end, an ionization chamber based on the photoionization source that reproduces the ionization processes in the ion mobility spectrometer and facilitates efficient transfer of the product ions into a mass spectrometer was developed. Photoionization of pure gasses and gas mixtures containing air, N-2, CO2 and N2O and the dopant CH2Cl2 is discussed. The main product ions of photoionization are identified and compared with the spectrum of reactant ions formed by radioactive and corona discharge sources on the basis of literature data. The results suggest that photoionization by soft X-radiation in the negative mode is more selective than the other sources. In air, adduct ions of O-2 - with H2O and CO2 were exclusively detected. Traces of CO2 impact the formation of adduct ions of O-2 - and Cl -(upon addition of dopant) and are capable of suppressing them almost completely at high CO2 concentrations. Additionally, the ionization products of four alkyl nitrates (ethylene glycol dinitrate, nitroglycerin, erythritol tetranitrate and pentaerythritol tetranitrate) formed by atmospheric pressure chemical ionization induced by X-ray photoionization in different gasses (air, N-2 and N2O) and dopants (CH2Cl2, C2H5Br and CH3I) are investigated. The experimental studies are complemented by density functional theory calculations of the most important adduct ions of the alkyl nitrates (M) used for their spectrometric identification. In addition to the adduct ions [M + NO3](-) and [M + Cl](-), adduct ions such as [M + N2O2](-), [M + Br](-) and [M+ I](-) were detected, and their gas-phase structures and energetics are investigated by density functional theory calculations. Copyright (C) 2016 John Wiley & Sons, Ltd.
The lack of soil data, which are relevant, reliable, affordable, immediately available, and sufficiently detailed, is still a significant challenge in precision agriculture. A promising technology for the spatial assessment of the distribution of chemical elements within fields, without sample preparation is laser-induced breakdown spectroscopy (LIBS). Its advantages are contrasted by a strong matrix dependence of the LIBS signal which necessitates careful data evaluation. In this work, different calibration approaches for soil LIBS data are presented. The data were obtained from 139 soil samples collected on two neighboring agricultural fields in a quaternary landscape of northeast Germany with very variable soils. Reference analysis was carried out by inductively coupled plasma optical emission spectroscopy after wet digestion. The major nutrients Ca and Mg and the minor nutrient Fe were investigated. Three calibration strategies were compared. The first method was based on univariate calibration by standard addition using just one soil sample and applying the derived calibration model to the LIBS data of both fields. The second univariate model derived the calibration from the reference analytics of all samples from one field. The prediction is validated by LIBS data of the second field. The third method is a multivariate calibration approach based on partial least squares regression (PLSR). The LIBS spectra of the first field are used for training. Validation was carried out by 20-fold cross-validation using the LIBS data of the first field and independently on the second field data. The second univariate method yielded better calibration and prediction results compared to the first method, since matrix effects were better accounted for. PLSR did not strongly improve the prediction in comparison to the second univariate method.
The lack of soil data, which are relevant, reliable, affordable, immediately available, and sufficiently detailed, is still a significant challenge in precision agriculture. A promising technology for the spatial assessment of the distribution of chemical elements within fields, without sample preparation is laser-induced breakdown spectroscopy (LIBS). Its advantages are contrasted by a strong matrix dependence of the LIBS signal which necessitates careful data evaluation. In this work, different calibration approaches for soil LIBS data are presented. The data were obtained from 139 soil samples collected on two neighboring agricultural fields in a quaternary landscape of northeast Germany with very variable soils. Reference analysis was carried out by inductively coupled plasma optical emission spectroscopy after wet digestion. The major nutrients Ca and Mg and the minor nutrient Fe were investigated. Three calibration strategies were compared. The first method was based on univariate calibration by standard addition using just one soil sample and applying the derived calibration model to the LIBS data of both fields. The second univariate model derived the calibration from the reference analytics of all samples from one field. The prediction is validated by LIBS data of the second field. The third method is a multivariate calibration approach based on partial least squares regression (PLSR). The LIBS spectra of the first field are used for training. Validation was carried out by 20-fold cross-validation using the LIBS data of the first field and independently on the second field data. The second univariate method yielded better calibration and prediction results compared to the first method, since matrix effects were better accounted for. PLSR did not strongly improve the prediction in comparison to the second univariate method.
The detection of hydrogen sulfide (H2S) by 2 + 1 resonance-enhanced multi-photon ionization (REMPI) and the application of H2S as a laser dopant for the detection of polar compounds in laser ion mobility (IM) spectrometry at atmospheric pressure were investigated. Underlying ionization mechanisms were elucidated by additional studies employing a drift cell interfaced to a time-of-flight mass spectrometer. Depending on the pressure, the primary ions H2S+, HS+, S+, and secondary ions, such as H3S+, were observed. The 2 + 1 REMPI spectrum of H2S near lambda = 302.5 nm was recorded at atmospheric pressure. Furthermore, the limit of detection and the linear range were established. In the second part of the work, H2S was investigated as an H2O analogous laser dopant for the ionization of polar substances by proton transfer. H2S exhibits a proton affinity (PA) similar to that of H2O, but a significantly lower ionization energy facilitating laser ionization. Ion-molecule reactions (IMR) of H3S+ with a variety of polar substances with PA between 754.6 and 841.6 kJ/mol were investigated. Representatives of different compound classes, including alcohols, ketones, esters, and nitroaromatics were analyzed. The IM spectra resulting from IMR of H3S+ and H3O+ with these substances are similar in structure, i.e., protonated monomer and dimer ion peaks are found depending on the analyte concentration.
In the present work, the density distribution of rhodamine 6G ions (R6G) in the gas phase and the droplets of an electrospray plume was studied by spatial and spectral imaging. The intention is to contribute to the fundamental understanding of the release mechanism of gaseous R6G in the electrospray ionization (ESI) process. Furthermore, the influence of ESI-parameters on the release efficiency of R6G, e. g. solvent flow, R6G and salt concentration were examined via direct fluorescence imaging of R6G. A solvent-shift of the fluorescence maximum,lambda(max) = 555 nm in methanolic solution and lambda(max) = 505 nm in gas phase, allows the discrimination between solvated and gaseous R6G. Two experimental setups were used for our measurements. In the first experiment, the R6G fluorescence and the light scattered from the spray plume were imaged in two spatial dimensions using a tunable wavelength filter. The second experiment was designed for obtaining 1-dimensional spatially resolved emission spectra of the spray. Here, the intensity distribution of solvated and gaseous R6G as well as scattered light (lambda = 355 nm) were measured simultaneously.
The results show the distribution of gaseous R6G in the plane, orthogonal to the ESI capillary, decreasing slightly towards the spray center and showing maxima at the cone margins. The distribution of gaseous R6G confirms the preferred release of gaseous ions from nano-droplets, indicating the ion evaporation model (IEM) to be the dominating release mechanism. Up to now, only a few fluorescence spectra of ionic compounds in the gas phase were published because the measurement of emission spectra of mass-selected ions in an ion trap is experimentally challenging. The fluorescence spectrum of gaseous lucigenin at atmospheric pressure is reported for the first time. This spectrum of lucigenin in the gas phase exhibits a blue shift of about Delta lambda = 10 nm in comparison to the corresponding spectrum in methanol.
Infrared matrix-assisted laser dispersion and ionization (IR-MALDI) in combination with ion mobility (IM) spectrometry enables the direct analysis of biomolecules in aqueous solution. The release of ions directly from an aqueous solution is based on a phase explosion, induced by the absorption of an IR laser pulse, which disperses the liquid as vapor, nano-and micro-droplets. The ionization process is characterized initially by a broad spatial distribution of the ions, which is a result of complex fluid dynamics and desolvation kinetics. These processes have a profound effect on the shape and width of the peaks in the IM spectra. In this work, the transport of ions by the phase explosion-induced shockwave could be studied independently from the transport by the electric field. The shockwave-induced mean velocities of the ions at different time scales were determined through IM spectrometry and shadowgraphy. The results show a deceleration of the ions from 118 m.s(-1) at a distance of 400 mu m from the liquid surface to 7.1 m.s(-1) at a distance of 10 mm, which is caused by a pile-up effect. Furthermore, the desolvation kinetics were investigated and a first-order desolvation constant of 325 +/- 50 s(-1) was obtained. In the second part, the IR-MALDI-IM spectrometer is used as an HPLC detector for the two-dimensional separation of a pesticide mixture.
The novel combination of infrared matrix-assisted laser dispersion and ionization (IR-MALDI) with ion mobility (IM) spectrometry makes it possible to investigate biomolecules in their natural environment, liquid water. As an alternative to an ESI source, the IR-MALDI source was implemented in an in-house-developed ion mobility (IM) spectrometer. The release of ions directly from an aqueous solution is based on a phase explosion, induced by the absorption of an IR laser pulse (lambda = 2.94 mu m, 6 ns pulse width), which disperses the liquid as nano- and micro-droplets. The prerequisites for the application of IR-MALDI-IM spectrometry as an analytical method are narrow analyte ion signal peaks for a high spectrometer resolution. This can only be achieved by improving the desolvation of ions. One way to full desolvation is to give the cluster ions sufficient time to desolvate. Two methods for achieving this are studied: the implementation of an additional drift tube, as in ESI-IM-spectrometry, and the delayed extraction of the ions. As a result of this optimization procedure, limits of detection between 5 nM and 2.5 mu M as well as linear dynamic ranges of 2-3 orders of magnitude were obtained for a number of substances. The ability of this method to analyze simple mixtures is illustrated by the separation of two different surfactant mixtures.
Laser-induced breakdown spectroscopy (LIBS) analysers are becoming increasingly common for material classification purposes. However, to achieve good classification accuracy, mostly noncompact units are used based on their stability and reproducibility. In addition, computational algorithms that require significant hardware resources are commonly applied. For performing measurement campaigns in hard-to-access environments, such as mining sites, there is a need for compact, portable, or even handheld devices capable of reaching high measurement accuracy. The optics and hardware of small (i.e., handheld) devices are limited by space and power consumption and require a compromise of the achievable spectral quality. As long as the size of such a device is a major constraint, the software is the primary field for improvement. In this study, we propose a novel combination of handheld LIBS with non-negative tensor factorisation to investigate its classification capabilities of copper minerals. The proposed approach is based on the extraction of source spectra for each mineral (with the use of tensor methods) and their labelling based on the percentage contribution within the dataset. These latent spectra are then used in a regression model for validation purposes. The application of such an approach leads to an increase in the classification score by approximately 5% compared to that obtained using commonly used classifiers such as support vector machines, linear discriminant analysis, and the k-nearest neighbours algorithm.
The increasing development of antibiotic resistance in bacteria has been a major problem for years, both in human and veterinary medicine. Prophylactic measures, such as the use of vaccines, are of great importance in reducing the use of antibiotics in livestock. These vaccines are mainly produced based on formaldehyde inactivation. However, the latter damages the recognition elements of the bacterial proteins and thus could reduce the immune response in the animal. An alternative inactivation method developed in this work is based on gentle photodynamic inactivation using carbon nanodots (CNDs) at excitation wavelengths λex > 290 nm. The photodynamic inactivation was characterized on the nonvirulent laboratory strain Escherichia coli K12 using synthesized CNDs. For a gentle inactivation, the CNDs must be absorbed into the cytoplasm of the E. coli cell. Thus, the inactivation through photoinduced formation of reactive oxygen species only takes place inside the bacterium, which means that the outer membrane is neither damaged nor altered. The loading of the CNDs into E. coli was examined using fluorescence microscopy. Complete loading of the bacterial cells could be achieved in less than 10 min. These studies revealed a reversible uptake process allowing the recovery and reuse of the CNDs after irradiation and before the administration of the vaccine. The success of photodynamic inactivation was verified by viability assays on agar. In a homemade flow photoreactor, the fastest successful irradiation of the bacteria could be carried out in 34 s. Therefore, the photodynamic inactivation based on CNDs is very effective. The membrane integrity of the bacteria after irradiation was verified by slide agglutination and atomic force microscopy. The method developed for the laboratory strain E. coli K12 could then be successfully applied to the important avian pathogens Bordetella avium and Ornithobacterium rhinotracheale to aid the development of novel vaccines.