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Two calibration-free LIBS techniques are used for the quantitative analysis of synthetic cement samples: the CF-LIBS based on the Boltzmann plot method and the Monte Carlo (MC) LIBS based on the iterative spectrum fitting. In CF-LIBS, the inverse problem is solved, i.e. the elemental concentrations are determined by the reconstruction of plasma parameters from spectra. The MC-LIBS technique solves the direct problem by finding the highest correlation between the model-generated and experimental spectrum. The accuracy of both calibration-free LIBS methods suffers from factors such as inaccurately determined instrumental function, the deviation of experimental plasma from the mathematical model used, not taking into account the collection geometry and from the uncertainty of spectroscopic data. Therefore, the both calibration-free LIBS approaches are applied to synthetic spectra which perfectly suit the mathematical model of the method. This test yields the accuracy of both the approaches for the ideal case. In addition, the accuracy of both methods is investigated for non-isothermal plasma, because real laser-induced plasma often has high gradients in temperature. Both methods assume an isothermal plasma.
Two calibration-free (CF) LIBS approaches are used for the quantitative analysis of cement samples: the CF-LIBS based on the Boltzmann plot method and the Monte Carlo (MC) LIBS based on the iterative spectrum fitting. In CF-LIBS, the inverse problem is solved, i.e. the elemental concentrations are determined by the reconstruction of plasma parameters from spectra. The MC-LIBS technique solves the direct problem by finding the highest correlation between the model-generated and experimental spectrum. The accuracy of both calibration-free LIBS methods suffers from factors such as inaccurately determined instrumental function, the deviation of experimental plasma from the mathematical model used, not taking into account the collection geometry, and from the uncertainty of spectroscopic data. The both calibration-free LIBS approaches are first applied to synthetic spectra which perfectly suit the mathematical model of the method, i.e. the model of the uniform, isothermal, and stationary plasma. This test yields the accuracy of both the approaches for the ideal case. In addition, the accuracy of both the methods is investigated for non-uniform and non-isothermal plasma, because real laser-induced plasma often has high gradients in temperature and particle number densities. Finally, both calibration-free LIBS approaches are applied to experimental spectra obtained from cement samples. The figures of merits of two approaches are compared when working with both synthetic and experimental spectra.
Spatial Heterodyne Spectroscopy (SHS) is a spectrometric technique that combines both dispersive and interferometric features into a customizable instrument. The Basis of SHS is a Michelson interferometer with its mirrors replaced by diffraction gratings and with no moving parts. The output signal from SHS is the interferogram, which is recorded with a 1D or 2D pixel array detector. The spatial periodicity of the fringes on the interferogram is a function of the wavelength of the diffracted light. Using the Fast Fourier Transform, the original optical spectrum that enters SHS is retrieved. The light that is analyzed by SHS can come from a variety of sources. In our work, we used Raman scattering and Laser-Induced Plasma to perform quantitative and qualitative analyses. Figure 1 compares the performance of the SHS with that of high Resolution echelle and portable low-resolution asymmetrically crossed Czerny-Turner spectrometers (OO in Fig.1). The analyzed light came from the plasma induced on a stainless-steel reference material. The SHS exhibits the resolution comparable to that of the echelle spectrometer used, about 8000. Due to a high throughput of the SHS (theoretically, ~200 times higher than that of grating instruments), the number of spectra needed to be accumulated for comparable signal-to-noise ratios is much smaller than in the case of the echelle and comparable to OO spectrometers.
Examples of Raman SHS applied to several pure liquids are given in Fig. 2. Raman SHS was used in three different settings: (i) for classification of six types of oils, (ii) for univariate/multivariate analysis of binary mixture cyclohexane-isopropanol, and (iii) for multivariate analysis of glycerol solution in water. For the last two settings, chemometric analysis of the spectra yielded linear calibration plots over the range 1-90% of concentrations of isopropanol in cyclohexane, and 0.5-10% of glycerol in water.
The antimicrobial photodynamic approach has been demonstrated as an efficient and sustainable process for the eradication of microbial pathogens. In this work, silica-coated Magnetite nanoparticles (NPs) were used as carriers of glycosylated porphyrins and phthalocyanines. Their subsequent cationization
resulted in the production of stable antimicrobial photosensitizing materials, effective against E. coli. Suspensions of the photocatalysts in water present bimodal size distributions formed by big clusters and small NPs with hydrodynamic diameters between 8 and 38 nm. The presence of small NPs in the suspensions is related to an effective photodynamic inactivation (PDI) of E. coli cells. Glycosylation of the PS showed a positive effect on the PDI performance, which could be related to a higher accumulation of the photocatalyst over the bacterial cell membrane. In addition, these biocidal agents proved to be photostable and their photoactive performance decreased only between 23% and 28% upon 5 PDI cycles, mostly because of the loss of material between cycles, which makes them promising materials for water disinfection purposes.
The primary screening of hybridoma cells is a time-critical and laborious step during the development of monoclonal antibodies. Often critical errors occur in this phase, which supports the notion that the generation of monoclonal antibodies with hybridoma technology is difficult to control and hence a risky venture. We think that it is crucial to improve the screening process to eliminate most of the immanent deficits of the conventional approach. With this new microarray-based procedure, several advances could be achieved: Selectivity for excellent binders, high throughput, reproducible signals, avoidance of misleading avidity (multivalency) effects, and simultaneous performance of competition experiments. The latter can directly be used to select clones of desired cross-reactivity properties. In this paper, a model system with two excellent clones against carbamazepine, two weak clones and blank supernatant has been designed to examine the effectiveness of the new system. The excellent clones could be detected largely independent of the IgG concentration, which is unknown during the clone screening since the determination and subsequent adjustment of the antibody concentration is not possible in most cases. Furthermore, in this approach, the enrichment, isolation, and purification of IgG for characterization is not necessary. Raw cell culture supernatant can be used directly, even when fetal calf serum (FCS) or other complex media had been used. In addition, an improved method for the oriented antibody-immobilization on epoxy-silanized slides is presented. Based on the results of this model system, we conclude that this approach should be preferable to most other protocols leading to many of false positives, causing expensive and lengthy confirmation steps to weed out the poor clones.
Probe 1, which contains an anilinopyridine chromophore and an azaoxa macrocyclic subunit, presented an absorption band centered at 340 nm in acetonitrile. Addition of Fe(III), Cr(III) and Hg(II) induced the growth of a new absorption band at 430 nm (with color change from colorless to yellow), whereas in the presence of Cu(II), Zn(II) and Pb(II), less marked changes were observed. The color changes observed upon addition of Fe(III), Cr(III) and Hg(II) were ascribed to the formation of 1:1 stoichiometry complexes with probe 1. Coordination of Fe(III), Cr(III) and Hg(II) with the pyridine fragment of 1 induced an enhancement of the charge transfer character accompanied with a marked bathochromic shift that was reflected in a color change from colorless to yellow. The strength of the interaction between probe 1 and Fe(III) cation was modulated upon interaction with anions. Of all the anions tested, only cyanide was able to induce the bleaching of the yellow 1·Fe(III) complex solution. This bleaching was ascribed to
the formation of 1·Fe(III)-CN complex that restored, to some extent, the optical features of the free probe allowing the chromogenic sensing of cyanide. Besides, 1·Fe(III) complex was used to detect
cyanide in acetonitrile-water 90:10 v/v mixtures with good recoveries.
Functional nanomaterials (NM) of different size, shape, chemical composition, and surface chemistry are of increasing relevance for many key technologies of the twenty-first century. This includes polymer and silica or silica-coated nanoparticles (NP) with covalently bound surface groups, semiconductor quantum dots (QD), metal and metal oxide NP, and lanthanide-based NP with coordinatively or electrostatically bound ligands, as well as surface-coated nanostructures like micellar encapsulated NP. The surface chemistry can significantly affect the physicochemical properties of NM, their charge, their processability and performance, as well as their impact on human health and the environment. Thus, analytical methods for the characterization of NM surface chemistry regarding chemical identification, quantification, and accessibility of functional groups (FG) and surface ligands bearing such FG are of increasing importance for quality control of NM synthesis up to nanosafety. Here, we provide an overview of analytical methods for FG analysis and quantification with special emphasis on bioanalytically relevant FG broadly utilized for the covalent attachment of biomolecules like proteins, peptides, and oligonucleotides and address methodand material-related challenges and limitations. Analytical techniques reviewed include electrochemical titration methods, optical assays, nuclear magnetic resonance and vibrational spectroscopy, as well as X-ray based and thermal analysis methods, covering the last 5–10 years. Criteria for method classification and evaluation include the need for a signal-generating label, provision of either the total or derivatizable number of FG, need for expensive instrumentation, and suitability for process and production control during NM synthesis and functionalization.
Working towards a comprehensive understanding of introduction pathways, number, and fate of micro¬plastics in the environment, suitable analytical methods are a precondition. Micro-spectroscopic methods are probably the most widely used techniques. Besides their ability to measure single spectra of a particle or fiber, most modern FTIR- and Raman microscopes are also capable of two-dimensional imaging. This is very appealing to microplastics research because it allows to simultaneously characterize the analytes chemically as well as their size (distribution) and shape.
Two-dimensional imaging on extensive sample areas with FTIR-micros¬copes is facilitated by focal plane array (FPA) detectors resulting in large data sets comprised of up to several million spectra. With numbers too large for manual inspection of each individual spectrum, automated data evaluation is inevitable. Identifying different polymers based on the comparison with known reference spectra (library search) has proven to be a suitable approach. For that purpose, FTIR-spectra of common plastics can be collected to create an individual reference library.
To Supplement this ‘targeted analysis’, looking for known substances via library search, an exploratory approach was tested. Principal component analysis (PCA) proved to be a helpful tool to drastically reduce the size of the data set while maintaining the significant information. Subsequently, cluster analysis was used to find groups of similar spectra. Spectra found in different clusters could be assigned to different polymer types. The variation observed within clusters gives a hint on chemical variability of microplastics of the same polymer found in the sample. Spectra labeled according to the respective cluster/polymer type were used to build a classification model which allowed to quickly predict the polymer type based on the FTIR spectrum. Classification was tested on a second, independent data set and results were compared to the spectral library search procedure.
A particle roughness analysis tool, based on electron microscopy (EM) images. The influence of various parameters on the calculated roughness was also investigated: the setting of the proper threshold, accelerating voltage, etc. The samples were gradually tilted to extend imaging information of more than only one projection. Furthermore, the measurement uncertainty of the profile roughness of particles associated to various orientations was estimated.