J and M Analytik AG

Essingen, Germany

J and M Analytik AG

Essingen, Germany
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Huhn C.,Jülich Research Center | Huhn C.,Leiden University | Huhn C.,J and M Analytik AG | Huhn C.,Aalen University of Applied Sciences | And 7 more authors.
Electrophoresis | Year: 2012

The combination of optical detection techniques like photometry (UV) or laser-induced fluorescence (LIF) with mass spectrometry for capillary electrophoresis offers advantages, both for later use of stand-alone CE-UV or CE-LIF systems and for combined CE-UV-MS or CE-LIF-MS analysis. Faster method development is enabled, the identification of analytes is facilitated, and it allows christian the optical detection scheme to be used for more precise quantification. However, shortcomings of current methodology and equipment hindered the broader use of such detection combinations mainly due to the long distance between the detection points (at least 20 cm). Large shifts in migration times and changes in resolution are visible between the detection traces hindering their straightforward comparison. We present here novel equipment for a robust coupling of CE-LIF-MS with the shortest possible distance between detection points (12 cm) determined by the length of the electrospray needle. In addition, we encourage the use of a normalization of detection traces using a scale of effective electrophoretic mobility to obtain the same x-scale for both detection traces. As an example, the proposed methodology is applied to a mixture of labeled as well as non-labeled N-glycans. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Kucheryavski S.,University of Aalborg | Esbensen K.H.,University of Aalborg | Bogomolov A.,J and M Analytik AG
Journal of Chemometrics | Year: 2010

Image analysis is an efficient technique used in many areas of science and industry. However, in process analytical applications it tends to be an ancillary tool, used mainly for visual monitoring or measuring some geometrical properties. At the same time, there are many other important aspects of the process samples appearance, besides measurable distances, that may be connected to the information of interest. In the present paper, the methods of image analysis were applied to at-line monitoring of fluid bed pellet coating process. The quantitative description of images of pellet samples, taken from different process stages, has been obtained using two different approaches: wavelet decomposition and angle measure technique (AMT). Both methods revealed a strong correlation between image features and process parameters. However, the AMT results turned out to be more accurate and stable. It has been shown that pellet images, taken with a conventional digital camera, can be used for at-line monitoring of the process course, specifically, the growth of pellets due to the coating. An algorithm for precise counting of pellets has been developed. Combined with the sample weighing, it enables an accurate determination of the mean added pellets' weight. The method can be used for the determination of the mean layer thickness, either by itself for at-line analysis or as a reference technique, when modeling the process from in-line spectroscopy data. Copyright © 2010 John Wiley & Sons, Ltd.

Ermakov V.V.,Samara State Technical University | Bogomolov A.,J and M Analytik AG | Bykov D.E.,Samara State Technical University
Journal of Environmental Management | Year: 2012

Oil-containing industrial wastes tend to accumulate and present a growing environmental danger. This is of particular concern in certain areas of Russia. For effective processing of depositories, the wastes' physico-chemical properties and depository characteristics should both be taken into account.Representative sample sets were collected from fifty four depositories of different age, origin, and location in Samara region and analyzed using multivariate data analysis: Principal Component Analysis (PCA) and Partial Least-Squares (PLS) regression. PCA results provide a better understanding of the internal data structure, i.e. variable correlations and groupings. Based on the PCA results, a new approach to the classification of oil sludge depositories has been suggested. Another practically important task of site assessment has been solved by PLS regression modeling. The method has been successfully applied to the accurate estimation of the depository processing profitability for a specific site. © 2012 Elsevier Ltd.

Bogomolov A.,J and M Analytik AG | Bogomolov A.,Samara State Technical University | Melenteva A.,Samara State Technical University
Chemometrics and Intelligent Laboratory Systems | Year: 2013

Accurate prediction models for fat and total protein content in raw milk have been built on visible and short-wave near infrared spectra (400-1100. nm) of a designed sample set with systematically varied nutrient composition and homogenization degree. Unlike the conventional approach to the spectroscopic milk analysis, exploiting the components' absorbance, the present method basically relies on the phenomenon of light scatter by fat globules and protein micelles.It has been shown that partial least-squares (PLS) regression on raw spectral data results in higher prediction accuracies of fat and total protein content compared to scatter-corrected spectra. Interpretation given to individual PLS factors confirms a dominating role of scatter in the modeling and aids in general understanding of quantitative multivariate analysis based on complex optical responses resulting from multiple scattering by different particles at significantly varying size distributions. This new approach can be used in the raw milk laboratory or field analysis as well as for in-line monitoring of various milk transfer and production stages.Practical modeling issues, i.e. experimental design of the sample set, model validation and refinement, have been also elaborated in this study. Variable selection by interval PLS (iPLS) regression essentially improved the model performance. Selected intervals can be utilized for technical simplification of suggested method of milk analysis. © 2013 Elsevier B.V.

Bogomolov A.,JandM Analytik AG | Bogomolov A.,Samara State Technical University | Melenteva A.,Samara State Technical University | Dahm D.J.,Rowan University
Journal of Near Infrared Spectroscopy | Year: 2013

Step-wise homogenisation has been applied to raw milk samples of different composition to investigate the effect of fat globule size distribution on diffuse transmission spectra in the region 400-1100 nm. Homogenisation results in significant spectral changes with two distinct phases. Initial even growth of spectral intensity across the whole spectral range, observed at lower degrees of homogenisation, was followed by a drastic fall in absorbance at the long-wave end of spectrum as the fat globules reached some critical size. Fat and protein content in the sample significantly affected the observed dependences of spectra on the applied homogenisation time. These observations have been explained as a superposition of two effects: growing fat globule density and changes in scatter nature as the particle sizes approach the light wavelengths in a corresponding spectral range. The representative layer theory has been used to illustrate the nature of the spectral effects.

Bogomolov A.,J and M Analytik AG
Chemometrics and Intelligent Laboratory Systems | Year: 2011

Modern process analytical chemistry and technology applications are reviewed from the point of view of acquisition, resolution and analysis of trajectories in a designed analytical space. © 2011 Elsevier B.V.

Pomerantsev A.L.,RAS Semenov Institute of Chemical Physics | Rodionova O.Y.,RAS Semenov Institute of Chemical Physics | Melichar M.,GEA Pharma Systems AG | Wigmore A.J.,GEA Pharma Systems AG | Bogomolov A.,J and M Analytik AG
Analyst | Year: 2011

A new method for the prediction of the drug release profiles during a running pellet coating process from in-line near infrared (NIR) measurements has been developed. The NIR spectra were acquired during a manufacturing process through an immersion probe. These spectra reflect the coating thickness that is inherently connected with the drug release. Pellets sampled at nine process time points from thirteen designed laboratory-scale coating batches were subjected to the dissolution testing. In the case of the pH-sensitive Acryl-EZE coating the drug release kinetics for the acidic medium has a sigmoid form with a pronounced induction period that tends to grow along with the coating thickness. In this work the autocatalytic model adopted from the chemical kinetics has been successfully applied to describe the drug release. A generalized interpretation of the kinetic constants in terms of the process and product parameters has been suggested. A combination of the kinetic model with the multivariate Partial Least Squares (PLS) regression enabled prediction of the release profiles from the process NIR data. The method can be used to monitor the final pellet quality in the course of a coating process. © 2011 The Royal Society of Chemistry.

Bogomolov A.,JandM Analytik AG | Dietrich S.,JandM Analytik AG | Boldrini B.,Reutlingen University | Kessler R.W.,Reutlingen University
Food Chemistry | Year: 2012

A new optical spectroscopic method for milk fat and total protein analysis has been developed. In contrast to the conventional approach that generally relies on the components' absorption, the suggested method is based on the phenomenon of light scatter by fat and protein particles. This fundamental distinction enables shifting the measurement to the cost-effective visible and adjacent near infrared region (below 1000 nm), where the scatter strongly dominates. Partial Least-Squares regression modelling on a designed set of training and validation milk samples resulted in root mean-square prediction errors of 0.05% and 0.03% for fat and protein content, respectively, which is close to the accuracy of reference analysis. It has been shown that multivariate data analysis is capable of distinguishing individual scatter spectra of fat and protein. This conclusion has been supported by Mie-theory calculations. The method is suitable for routine laboratory analysis or in-line quality monitoring in the dairy production. © 2012 Elsevier Ltd. All rights reserved.

Bogomolov A.,J and M Analytik AG | Engler M.,J and M Analytik AG | Melichar M.,GEA Pharma Systems AG | Wigmore A.,GEA Pharma Systems AG
Journal of Chemometrics | Year: 2010

Near infrared (NIR) and Raman spectroscopic analyzers applied through an immersion Lighthouse Probe (LHP) were used for simultaneous in-line monitoring of a fluid bed pellet coating process. Multivariate curve resolution analysis of data, collected from four pilot-scale batches, has shown that the two techniques deliver complementary information about the process and their combination may be synergistic. This data analysis enabled a much better understanding of some of the process observations and also gave some interesting insights into the best way to use the techniques themselves. PLS regression analysis of the product moisture and the quantity of coating material sprayed was performed using NIR and Raman data blocks both separately and in combination. The performance of method combination compared to individual techniques is analyzed and discussed. Copyright © 2010 John Wiley & Sons, Ltd.

Bogomolov A.,J and M Analytik AG | Grasser T.,Ulm University of Applied Sciences | Hessling M.,Ulm University of Applied Sciences
Journal of Chemometrics | Year: 2011

Fluorescence analysis, in particular two-dimensional excitation-emission matrix (EEM) spectroscopy, is a sensitive in-line process monitoring tool in the biotechnological production. Before it can be widely adopted by the industry, fast effective algorithms for the analysis of massive and complex fluorescence data should be developed. Weak emission signals are prone to various interferences complicating the modeling, such as excitation light Rayleigh scatter. The scatter is usually considered as an unwanted background to be avoided or removed. This work is focused on effective usage of the entire spectral information. It has been shown that scatter peaks coming from the excitation or an external light source can be used in the data analysis to improve the performance of a multivariate model. A new fluorescence Lighthouse Probe™ (LHP) has been applied in-line to monitor Saccharomyces cerevisiae fermentation in a lab reactor. Exploratory data analysis of two fed-batch cultivations has been performed using Partial Least Squares regression and Multivariate Curve Resolution. A simple algorithm for the resolution of process profiles and two-dimensional spectra of individual fluorophores from three-way fluorescence data in the presence of intensive scatter has been suggested and applied to the process diagnostics. © 2011 John Wiley & Sons, Ltd.

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