We have summarised typical applications of our technology at customers and partners in the following list of Application Note documents.
Monitoring the production of urea from CO2 and ammonia bears multiple challenges in an industrial environment: high pressure, high corrosivity, very sensitive reaction equilibria, and the inaccessibility of representative process samples. It needs Process Raman and intelligent quantitative modelling to solve it!
Silanes are highly versatile materials for a multitude of applications. Product properties are adjusted by blending additives or stabilizers, according to the field of application, which needs precise release control. Low-field nuclear magnetic resonance spectroscopy (LF-NMR) is the key to success here, combined with spectral analysis using spectral Hard Modeling.
Hydrocarbon streams in Petrochemical processes require composition analysis, both P-I-O-N-A contents (n-/iso-/cyclo-paraffins, olefins, aromatics) and detail signle component analysis. Real-time access to this information is given through Process Raman technology. Intelligent calibration approaches reduce the effort for multi-parameter calibrations dramatically.
The generation of synthetic rubber from dienes and olefins is monitored in real-time with inline Raman spectroscopy, allowing to track the insertion type of the monomers into the polymer immediately and in detail. Laborious and time-consuming offline analysis can be substituted, speeding up recipe optimisation tremendously.
Does spectral analysis always need to rely on the same method/approach? Taking bioprocesses with their abundancy of process parameters typically modelled by multivariate statistics only, we show how to use the entire chemometrics toolbox more efficiently with PEAXACT.
A Kaiser Raman analyzer with multiple probes is used to monitor a distillation column, operated with isomer mixtures for performance characterisation. Raman spectroscopy is capable of tracking down composition changes in the sub-percent range.
The multi-step synthesis sequence of a fine chemical is elucidated by applying Hard Modeling Factor Analysis (HMFA) to MIR spectra measured inline. The estimated pure component spectra are validated through mixtures samples prepared in the lab and thus allow to develop set up the reaction network.
CO2 is converted with epoxides into innovative polyethercarbonates. The formation of carbonate and polyether moieties is observed inline with ATR-MIR spectroscopy under harsh conditions. Indirect Hard Modeling (IHM) allows bottom-up spectral modelling for quantification.
The robustness of a Raman and mid-IR based substance identification has been proved with the help of a discriminant analysis approach. Spectra of typical Pharma ingredients have been recorded under systematically varied conditions. Classification models were trained and validated with independent material samples.
# 304, Raman
Platform chemicals based on renewable feedstocks typically require the hydrogenation of plant-based carbohydrates (sugars, cellulose, …) in pressurised reactors before they undergo consecutive reactions. These conversions are well observable with fibre-optical inline Raman spectroscopy.
The development of an API crystallization process is monitored with ATR-MIR spectroscopy throughout lab and pilot plant scale. Model transfer is significantly facilitated through the use of Indirect Hard Modeling.
In a high-pressure autoclave the phase composition of a biphasic reaction is monitored in both phases simultaneously. Reaction progress and mass transfer can easily be separated for a model-based process optimisation.
The generation of bio-methane in a converter of industrial sewage sludge is monitored by gas-phase Raman spectroscopy. Measurements are performed directly in the product gas stream. The influence of process parameter changes is well reflected in the predicted methane profiles.
Acrylic acid and related monomers are continuously polymerised in aqueous solution. For MIR spectroscopic monitoring, probes are installed along the entire reactor length. Indirect Hard Modeling is required to separate monomer and polymer contributions to the spectra.
Substrate and product content in an industrial bio-process are monitored by Raman spectroscopy. Time resolution is improved dramatically compared to offline analysis. The immediate access to the process performance is capable of online process control.
Carotenoid contents of various food samples are determined with UV spectroscopy. Though similar in structure, an Indirect Hard Modeling analysis is capable of separating the overlapping spectral contributions of the different components.
Gas chromatograms are classified before quantitative analysis. A model-based unsupervised approval procedure in PEAXACT Chrom identifies typical irregularities like missing or additional peaks, retention time shifts, etc. Batch approval times are significantly reduced.
Benchtop NMR spectrometers nowadays generate spectra of such a high quality that quantitative analyses of mixtures are significantly facilitated. In case of very similar mixture components (here sugars), Indirect Hard Modeling (IHM) is a valuable analysis method for the deconvolution of mixture spectra.
A glass-made tray column is equipped with a 4-sensor MIR spectroscopic system. Concentrations are not only measured in sump and head product stream, but also on the trays. The Indirect Hard Modeling analysis restricts the required reference measurements to ambient temperature.
A continuous esterification is performed in micro-structured reactors and monitored with miniaturised MIR spectroscopy. Measured spectra are immediately analysed with PEAXACT. Predictions allow for real-time observation or control of the process.
Water Vapour compensation through Indirect Hard Modeling
Water vapour in MIR spectra is compensated through an Indirect Hard Modeling approach. Treating water vapour as a regular mixture component allows to account for variations in the overall content. The main component profiles emerge free of interference.
Inline Monitoring of Fermentations for Organic Acids Production
MIR spectroscopy is applied for process monitoring in a pilot-scale fermentation of sugars. Thanks to an Indirect Hard Modeling approach, the water spectrum is accounted for in the analysis step. Online substrate content prediction can act as a shut-off criterion for the process.
Quantifying molecular interactions through Indirect Hard Modeling
The influence of water traces on the properties of Ionic Liquids is assessed by MIR spectroscopy. Spectra are analysed with the Indirect Hard Modeling method. Resulting peak parameters, e.g. peak shifts, are used for quantitative determination of mixture physics.