Bogomolov A.,J and M Analytik AG |
Bogomolov A.,Samara State Technical University |
Hessling M.,Ulm University of Applied Sciences |
Wenzel U.,Ulm University of Applied Sciences |
And 7 more authors.
Sensors and Actuators, B: Chemical | Year: 2015
Three prototypes of mid-infrared (MIR) spectrometric sensor systems for simultaneous monitoring of ethanol and carbohydrates (in the present case glucose and fructose) in the course of biotechnological processes have been constructed based on recent developments in pyroelectric detection and fiber photonics. The sensors utilized were a grating spectrometer or a Fabry-Pérot interferometer adjusted for the detection of analytes' characteristic absorbance bands in the spectral region of "fingerprints" between 1050 and 950cm-1. The measurements were performed with an attenuated total reflection (ATR) probe connected to the spectrometer by a polycrystalline infrared fiber (PIR). Two probes with different ATR elements were tested: with a diamond crystal (for both spectrometers) and with a detachable PIR loop head (for grating spectrometer). The sensor performances were assessed and compared using partial least-squares (PLS) regression modeling and prediction statistics for two designed sample sets of binary ethanol-glucose and glucose-fructose aqueous solutions. The models based on the FT-IR spectroscopic analysis of the same designed samples using a diamond ATR probe (a "gold standard" method) were used as a benchmark. The system based on a grating spectrometer connected to an ATR probe with a PIR loop head was additionally tested under the process conditions of Saccharomyces cerevisiae fermentation. The resulting root mean-square errors of prediction were 4.74 and 13.33g/L, for ethanol and glucose models, respectively. Simultaneously, NIR spectroscopy in the range 1100-2100nm was used both for the analysis of designed samples and for the fermentation process monitoring. In the latter case a biomass content prediction model has been built along with those for ethanol and glucose. All tested full-spectroscopic and sensor-based methods of analysis have been compared and their practical applications discussed. © 2015 Elsevier B.V.
Artyushenko V.,Art Photonics GmbH |
Schulte F.,Art Photonics GmbH |
Zabarylo U.,Art Photonics GmbH |
Berlien H.-P.,Lasermedizin Evangelische Elisabeth Klinik |
And 9 more authors.
Progress in Biomedical Optics and Imaging - Proceedings of SPIE | Year: 2015
Cancer is one of the leading causes for morbidity and mortality worldwide. Therefore, efforts are concentrated on cancer detection in an early stage to enhance survival rates for cancer patients. A certain intraoperative navigation in the tumor border zone is also an essential task to lower the mortality rate after surgical treatment. Molecular spectroscopy methods proved to be powerful tools to differentiate cancerous and healthy tissue. Within our project comparison of different vibration spectroscopy methods were tested to select the better one or to reach synergy from their combination. One key aspect was in special fiber probe development for each technique. Using fiber optic probes in Raman, MIR and NIR spectroscopy is a very powerful method for non-invasive in vivo applications. Miniaturization of Raman probes was achieved by deposition of dielectric filters directly onto the silica fiber end surfaces. Raman, NIR and MIR spectroscopy were used to analyze samples from kidney tumors. The differentiation between cancer and healthy samples was successfully obtained by multivariate data analysis. © 2015 SPIE.
Eccleston R.,Cologne University of Applied Sciences |
Wolf C.,Cologne University of Applied Sciences |
Balsam M.,Cologne University of Applied Sciences |
Schulte F.,Art Photonics GmbH |
And 2 more authors.
Chemical Engineering and Technology | Year: 2016
To develop an online probe that is not only sufficiently robust, but also able to measure crucial process variables in biogas plants is a tough challenge. Therefore, a mid-infrared (MIR) spectroscopic attenuated total reflection (ATR) probe and robust probe fitting were established. A fully automated probe control, calibration after probe cleaning, and analysis of the absorption spectra using machine learning were implemented in order to reduce maintenance of the probe to a minimum. The relevant wavelengths in the MIR spectrum for organic acids, total alkalinity, and ammonium nitrogen concentration were identified. Finally, intensive lab testing was carried out, followed by operation of the complete online measurement system at an industrial biogas plant. In order to improve signal strength and sensitivity, microelectronic mechanical system (MEMS)-based Fabry-Pérot interferometers were also investigated. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.