Heiko Ulmer

Odours and flavours identified with hybrid modular sensor systems

Abstract Hybrid sensor systems contain different types of chemical sensors whereby each type (transducer principle) contains an array of individual sensors. This leads to a large flexibility in the choice of transducers and sensor materials with the general aim of optimising the analytical performance of the total system. This concept makes it possible to optimise the quantitative analysis of mixtures of known gases as it will be demonstrated for mixtures of volatile organic compounds (VOCs). Alternatively this makes it possible to optimise the system for characterising odours and flavours. This will be demonstrated for different plastic as well as textile materials used in car industries and for different products of food industries, i.e. coffees, tobaccos, whiskeys, and olive oils. In our modular sensor systems we used arrays of different semiconductor gas sensors (based on metal oxides), of polymer coated quartz microbalance (QMB) sensors, of calorimetric sensors and of electrochemical sensors, with an option to add metal oxide semiconductor field effect transistor (MOSFET) sensors. These arrays are arranged as separate components in a modular sensor system ‘MOSES’. For the qualitative discrimination of different odour samples a headspace-autosampler was added and transient sensor signals were monitored. The use of different transducer principles is shown to be essential for an unequivocal identification of odours and flavours.

Detection of volatile organic compounds (VOCs) with polymer-coated cantilevers

Abstract Changes in the resonance frequency of polymer-coated cantilevers due to gas absorption is shown to be a promising detection mechanism for gases. We prepared SiNx cantilevers based on micromachined Si wafers and used polydimethylsiloxane (PDMS) as polymeric prototype coating. We measured the resonance frequency response of cantilevers end-coated with polymer on exposure to different vapor concentrations of n-octane, toluene, and n-butanole and determined high sensitivities with respect to cantilevers without polymer coating. By using the first higher resonance mode, we found with our configuration sensitivities up to −0.0988 Hz/ppm for small concentrations of n-octane. It is demonstrated here how the sensitivity of the chemical sensor can be improved by varying the deposited polymer mass.

“Electronic nose” detects major histocompatibility complex-dependent prerenal and postrenal odor components

Mice prefer to mate with individuals expressing different MHC genes from their own. Volatile components presenting MHC-dependent odor types are present in urine and can be detected by mice, as shown by extensive behavioral studies. Similar odor types are suspected to influence human behavior as well. Although a recent report indicates that MHC expression influences the ratio of volatile compounds such as phenylacetic acid, so far no other means than studying the behavior of mice or rats has been available to assess odor types. Here, we report the ability of a gas sensor array (referred to as “electronic nose”) to detect MHC-dependent odor types. The electronic nose consists of an array of chemophysical detectors, in our case quartz crystal microbalances and semiconducting metal-oxide sensors that change frequency or conductivity upon binding of very small numbers of individual molecules present in the gas phase of odorous fluids. The pattern of changes is characteristic for a particular smell. Our electronic nose distinguishes the urine odor types of MHC congenic mouse strains, MHC class I mutant mice, and HLA-A2 transgenic mice. In addition, MHC-dependent odor types can be detected in serum. The device also clearly differentiates between individual odor types of human sera from HLA homozygous individuals; however, HLA expression seems to have only a secondary influence. Thus, odor-type research can now be carried out with an objective and fast through-put system independent of behavioral studies.

Complementary analytical measurements based upon gas chromatography-mass spectrometry, sensor system and human sensory panel: a case study dealing with packaging materials

In co-operation with packaging material suppliers and a food manufacturer the quality of different kinds of wrapping foils for chocolate bars was investigated by using the hybrid Modular Sensor System (MOSES II). To check the reproducibility and to deduce quantitative predictions a gas chromatograph-mass spectrometer (GC/MS)-unit connected to a headspace-sampler (HSS) was used as a well established analytical reference instrumentation. All analysed samples were also qualified by a human sensory panel according to the sniff-test. The different packaging material species could be distinguished in a principal component analysis (PCA). With the aid of a principal component regression (PCR) a correlation between human and technical odour perception was carried out. The odour prediction of MOSES II was very satisfying particularly if compared to the human sensory assessments. Additionally, in order to follow the sensor fluctuations the sensor responses upon exposure to a standard sample have been monitored for 5 months. The results of these measurements and the investigations of four different MOSES II units demonstrated the long-term stability of the individual sensors and the high reproducibility from system to system.

Standardization methods for handling instrument related signal shift in gas-sensor array measurement data

Abstract This paper describes two different approaches that attempt to solve the problem of signal shift between measurements acquired with gas-sensor array systems of identical construction. Both methods provide standardization models that can be used to compensate such instrument related signal shifts by postprocessing of the measurement data. The first approach is a straightforward univariate direct standardization method, based on linear regression, where unique shift compensation models are created for each sensor. The other approach is a multivariate method, based on partial least squares regression, which can be used to design shift compensation models for the whole gas-sensor array. Both methods effectively removed signal shift after being applied on measurement data acquired with five commercial instruments of identical configuration with quartz micro balance (QMB) sensor arrays.

Sensor arrays with only one or several transducer principles? The advantage of hybrid modular systems

Abstract Artificial olfaction by means of “electronic noses” aims at the determination of chemical features to characterize molecules, odors, environmental conditions, process parameters, etc. In order to achieve sufficient discrimination a broad spectrum of independent features has to be determined. Since the choice of suitable materials for each individual transducer is limited, different transducers have to be combined in a sensor system to obtain a sufficiently broad discrimination power. This is illustrated for typical examples chosen from the food and textile industries which illustrate the advantage of such “hybrid modular systems”.

Quality tests of electronic noses: the influence of sample dilution and sensor drifts on the pattern recognition for selected case studies

Abstract Arrays of chemical sensors have a broad spectrum of applications, e.g., in the field of process control and quality analysis. Especially for the fast and objective evaluation of food quality and off-flavour contents in plastic materials, such sensor systems, often called “Electronic Noses”, have an increasing demand. In this context, the performance and reproducibility of an array analysis is usually not checked systematically. The present paper therefore deals with the influence of sample dilution (external effect) and of changed sensor parameters with time (internal effect) on the subsequent results of pattern recognition.

Detection of off-odors using a hybrid modular sensor system

Experimental results are presented of a qualitative analysis of off-odors in packaging materials, obtained with a hybrid modular sensor system. The sensing elements are combined in two modules of the hybrid modular sensor system MOSES II which contains different types of transducers. The modules chosen in the present study consist of 8 metal oxide-based semiconductor gas sensors and 8 polymer coated quartz microbalance sensors (QMB). Pattern recognition was performed by principal component analysis (PCA). For packaging materials a discrimination between unprinted and printed materials could be achieved successfully by comparing three different samples. These results characterize the performance and reproducibility of the newly designed hybrid modular sensor system for investigations of a broad spectrum of other applications.