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Hydrothermal carbonization (HTC) can be used for converting the biomass into a carbon-rich material, whose application as a fuel requires higher heating value, whereas soil amendment needs stable carbon. This work was focused on the characterization of hydrochars derived from microcrystalline cellulose. The chars were investigated using elemental analysis, Brunauer–Emmett–Teller technique, nuclear magnetic resonance spectroscopy, Raman, Fourier transform infrared, and electron spin resonance spectroscopy. Severity in temperature between 230 and 270 °C with reaction times between 2 and 10 h only affect the carbon content moderately. The results show that aromatization of HTC chars correlates well with temperature, which was further supported by the increase of organic radicals with decreasing g values at higher temperatures. Based on these results, the energetic use of chars favors mild HTC (T < 230 °C and t ≤ 6 h), while the soil amendement favors serve conditions (T ≥ 230 °C, and t > 6 h).
The leaching behavior of scandium (Sc) from bauxite residues can differ significantly when residues of different geological backgrounds are compared. The mineralogy of the source rock and the physicochemical environment during bauxitization affect the association of Sc in the bauxite i.e., how Sc is distributed amongst different mineral phases and whether it is incorporated in and/or adsorbed onto those phases. The Sc association in the bauxite is in turn crucial for the resulting Sc association in the bauxite residue. In this study systematic leaching experiments were performed on three different bauxite residues using a statistical design of experiments approach. The three bauxite residues compared originated from processing of lateritic and karstic bauxites from
Germany, Hungary, and Russia. The recovery of Sc and Fe was determined by ICP-OES measurements. Mineralogical changes were analyzed by X-ray-diffraction and subsequent Rietveld refinement. The effects of various parameters including temperature, acid type, acid concentration, liquid-to-solid ratio and residence time were studied. A response surface model was calculated for the selected case of citric acid leaching of Hungarian bauxite residue. The investigations showed that the type of bauxite residue has a strong influence. The easily leachable fraction of Sc can vary considerably between the types, reaching ~20–25% in German Bauxite residue and ~50% in Russian bauxite residue. Mineralogical investigations revealed that a major part of this fraction was released from secondary phases such as cancrinite and katoite formed during Bayer processing of the bauxite.
The effect of temperature on Sc and Fe recovery is strong especially when citric acid is used. Based on the exponential relationship between temperature and Fe-recovery it was found to be particularly important for the selectivity of Sc over Fe. Optimization of the model for a maximum Sc recovery combined with a minimum Fe
recovery yielded results of ~28% Sc recovery at <2% Fe recovery at a temperature of 60 ◦C, a citric acid normality of 1.8, and a liquid-to-solid ratio of 16 ml/g. Our study has shown that detailed knowledge about the Sc association and distribution in bauxite and bauxite residue is key to an efficient and selective leaching of Sc
from bauxite residues.
Spatial heterodyne spectroscopy (SHS) is used for quantitative analysis and classification of liquid samples. SHS is a version of a Michelson interferometer with no moving parts and with diffraction gratings in place of mirrors. The instrument converts frequency-resolved information into spatially resolved one and records it in the form of interferograms. The back-extraction of spectral information is done by the Fast Fourier transform. A SHS instrument is constructed with the resolving power 5000 and spectral range 522 - 593 nm. Two original technical solutions are used as compared to previous SHS instruments: the use of a high frequency diode pumped solid state (DPSS) laser for excitation of Raman spectra and a microscope-based collection system. Raman spectra are excited at 532 nm at the repetition rate 80 kHz. Raman shifts between 330 cm-1 and 1600 cm-1 are measured. A new application of SHS is demonstrated: for the first time it is used for quantitative Raman analysis to determine concentrations of cyclohexane in isopropanol and glycerol in water. Two calibration strategies are employed: univariate based on the construction of a calibration plot and multivariate based on partial least square regression (PLSR). The detection limits for both cyclohexane in isopropanol and glycerol in water are at a 0.5 mass% level. In addition to the Raman-SHS chemical analysis, classification of industrial oils (biodiesel, poly(1-decene), gasoline, heavy oil IFO380, polybutenes, and lubricant) is performed using their Raman-fluorescence spectra and principal component analysis (PCA). The oils are easily discriminated as they show distinct non-overlapping patterns in the space of principal components.
The transformation of a base-catalyzed, mechano-assisted Knoevenagel condensation of mono-fluorinated benzaldehyde derivatives (p-, m-, o-benzaldehyde) with malonodinitrile was investigated in situ and in real time. Upon milling, the para-substituted product was found to crystallize initially into two different polymorphic forms, depending on the quantity of catalyst used. For low catalyst concentrations, a mechanically metastable phase (monoclinic) was initially formed, converting to the mechanically stable phase (triclinic) upon further grinding. Instead, higher catalyst concentrations crystallize directly as the triclinic product. Inclusion of catalyst in the final product, as evidenced by mass spectrometric analysis, suggests this complex polymorphic pathway may be due to seeding effects. Multivariate analysis for the in situ Raman spectra supports this complex formation pathway, and offers a new approach to monitoring multi-phase reactions during ball milling.
The authenticity of objects and artifacts is often
the focus of forensic analytic chemistry. In document fraud
cases, the most important objective is to determine the
origin of a particular ink. Here, we introduce a new
approach which utilizes the combination of two analytical
methods, namely Raman spectroscopy and laser-induced
breakdown spectroscopy (LIBS). The methods provide
complementary information on both molecular and elemental
composition of samples. The potential of this hyphenation
of spectroscopic methods is demonstrated for ten blue
and black ink samples on white paper. LIBS and Raman
spectra from different inks were fused into a single data
matrix, and the number of different groups of inks was
determined through multivariate analysis, i.e., principal
component analysis, soft independent modelling of class
analogy, partial least-squares discriminant analysis, and
support vector machine. In all cases, the results obtained
with the combined LIBS and Raman spectra were found to
be superior to those obtained with the individual Raman or
LIBS data sets.
Arsenic is a redox-active metalloid whose toxicity and mobility strongly depends on its oxidation state, with arsenite (As(III)) being more toxic and mobile than arsenate (As(V)). Humic substances (HS) are also redox-active and can potentially react with arsenic and change its redox state. In this study we show that semiquinone radicals produced during microbial or chemical reduction of a HS model quinone (AQDS, 9,10-anthraquinone-2,6-disulfonic acid) are strong oxidants. They oxidize arsenite to arsenate, thus decreasing As toxicity and mobility. This reaction depends strongly on pH with more arsenite (up to 67.3%) being oxidized at pH 11 compared to pH 7 (12.6% oxidation) and pH 3 (0.5% oxidation). In addition to As(III) oxidation by semiquinone radicals, hydroquinones that were also produced during quinone reduction reduced As(V) to As(III) at neutral and acidic pH values (less than 12%) but not at alkaline pH. In order to understand redox reactions between arsenite/arsenate and reduced/oxidized HS, we quantified the radical content in reduced quinone solutions and constructed Eh-pH diagrams that explain the observed redox reactions. The results from this study can be used to better predict the fate of arsenic in the environment and potentially explain the occurrence of oxidized As(V) in anoxic environments.
Monitoring chemical reactions is the key to chemical process control. Today, mainly optical online methods are applied, which require excessive calibration effort. NMR spectroscopy has a high potential for direct loop process control while exhibiting short set-up times. Compact NMR instruments make NMR spectroscopy accessible in industrial and harsh environ¬ments for advanced process monitoring and control, as demonstrated within the European Union’s Horizon 2020 project CONSENS.
We present a range of approaches for the automated spectra analysis moving from conventional multivariate statistical approach, (i.e., Partial Least Squares Regression) to physically motivated spectral models (i.e., Indirect Hard Modelling and Quantum Mechanical calculations). By using the benefits of traditional qNMR experiments data analysis models can meet the demands of the PAT community (Process Analytical Technology) regarding low calibration effort/calibration free methods, fast adaptions for new reactants or derivatives and robust automation schemes.
Monitoring specific chemical properties is the key to chemical process control. Today, mainly optical online methods are applied, which require time- and cost-intensive calibration effort. NMR spectroscopy, with its advantage being a direct comparison method without need for calibration, has a high potential for closed-loop process control while exhibiting short set-up times. Compact NMR instruments make NMR spectroscopy accessible in industrial and rough environments for process monitoring and advanced process control strategies.
We present a fully automated data analysis approach which is completely based on physically motivated spectral models as first principles information (Indirect Hard Modelling – IHM) and applied it to a given pharmaceutical lithiation reaction in the framework of the European Union’s Horizon 2020 project CONSENS. Online low-field NMR (LF NMR) data was analysed by IHM with low calibration effort, compared to a multivariate PLS-R (Partial Least Squares Regression) approach, and both validated using online high-field NMR (HF NMR) spectroscopy.
Flexible automation with compact NMR spectroscopy for continuous production of pharmaceuticals
(2019)
Modular plants using intensified continuous processes represent an appealing concept for the production of pharmaceuticals. It can improve quality, safety, sustainability, and profitability compared to batch processes; besides, it enables plug-and-produce reconfiguration for fast product changes. To facilitate this flexibility by real-time quality control, we developed a solution that can be adapted quickly to new processes and is based on a compact nuclear magnetic resonance (NMR) spectrometer. The NMR sensor is a benchtop device enhanced to the requirements of automated chemical production including robust evaluation of sensor data. Beyond monitoring the product quality, online NMR data was used in a new iterative optimization approach to maximize the plant profit and served as a reliable reference for the calibration of a near-infrared (NIR) spectrometer. The overall approach
was demonstrated on a commercial-scale pilot plant using a metal-organic reaction with pharmaceutical relevance.
The application of Raman spectroscopy as a monitoring technique for bioprocesses is severely limited by a large background signal originating from fluorescing compounds in the culture media. Here, we compare time-gated Raman (TG-Raman)-, continuous wave NIRprocess Raman (NIR-Raman), and continuous wave micro-Raman (micro-Raman) approaches in combination with surface enhanced Raman spectroscopy (SERS) for their potential to overcome this limit. For that purpose, we monitored metabolite concentrations of Escherichia coli bioreactor cultivations in cell-free supernatant samples. We investigated concentration transients of glucose, acetate, AMP, and cAMP at alternating substrate availability, from deficiency to excess. Raman and SERS signals were compared to off-line metabolite analysis of carbohydrates, carboxylic acids, and nucleotides. Results demonstrate that SERS, in almost all cases, led to a higher number of identifiable signals and better resolved spectra. Spectra derived from the TG-Raman were comparable to those of micro-Raman resulting in well-discernable Raman peaks, which allowed for the identification of a higher number of compounds. In contrast, NIR-Raman provided a superior performance for the quantitative evaluation of analytes, both with and without SERS nanoparticles when using multivariate data analysis.