Explosives are of significant interest to homeland security departments and forensic investigations. Fast, sensitive and selective detection of these chemicals is of great concern for security purposes as well as for triage and decontamination in contaminated areas. To this end, selective sorbents with fast binding kinetics and high binding capacity, either in combination with a sensor transducer or a sampling/sample-preparation method, are required. Molecularly imprinted polymers (MIPs) show promise as cost-effective and rugged artificial selective sorbents, which have a wide variety of applications. This manuscript reviews the innovative strategies developed in 57 manuscripts (published from 2006 to 2019) to use MIP materials for explosives. To the best of our knowledge, there are currently no commercially available MIP-modified sensors or sample preparation methods for explosives in the market. We believe that this review provides information to give insight into the future prospects and potential commercialization of such materials. We warn the readers of the hazards of working with explosives.
The reduced mobility of an ion is a key parameter for identifying ions and comparing spectra in drift time ion mobility spectrometry. As the resolution of spectrometers improves, accurate determination of the reduced mobility is increasingly important. The drift time, used to calculate the reduced mobility, is affected by the ion gate, and this effect has previously been compensated with a linear correction. These corrections, however, do not allow for changes in the distances that the ions must drift to reach the detector caused by the electric field around the ion gate. As these corrections are a linear correction, nonlinearity in the influence of the ion gate may also lead to greater errors. By measuring the length of the depletion zone in front of the ion gate the extra distance traveled by the ions may be corrected for. This measurement also provides the boundary conditions for when a correction to the drift time may be accurately applied. This work shows that the length of the depletion zone can be experimentally measured and that it is consistent for a particular geometry of ion gate.
Usage of commercially available electrochemical gas sensors is currently limited by both the working range of the sensor with respect to temperature and humidity and the spikes in sensor response caused by sudden changes in temperature or humidity. Using a thermostatically controlled chamber, the sensor response of ammonia and hydrogen sulfide sensors was studied under extreme, rapidly changing levels of humidity with the aim of analyzing nebulized water samples. To protect the sensors from damage, the gas stream was alternated between a saturated gas stream from a Flow Blurring® nebulizer and a dry air stream. When switching between high and low humidity gas streams, the expected current spike was observed and mathematically described. Using this mathematical model, the signal response due to the change in humidity could be subtracted from the measured signal and the sensor response to the target molecule recorded. As the sensor response is determined by the model while the sensor is acclimatizing to the new humid conditions, a result is calculated faster than that by systems that rely on stable humidity. The use of the proposed mathematical model thus widens the scope of electrochemical gas sensors to include saturated gas streams, for example, from nebulized water samples, and gas streams with variable humidity.
The cultivation of algae either in open raceway ponds or in closed bioreactors could allow the renewable production of biomass for food, pharmaceutical, cosmetic, or chemical industries. Optimal cultivation conditions are however required to ensure that the production of these compounds is both efficient and economical. Therefore, high-frequency analytical measurements are required to allow timely process control and to detect possible disturbances during algae growth. Such analytical methods are only available to a limited extent. Therefore, we introduced a method for monitoring algae release volatile organic compounds (VOCs) in the headspace above a bioreactor in real time. This method is based on ion mobility spectrometry (IMS) in combination with a membrane inlet (MI). The unique feature of IMS is that complete spectra are detected in real time instead of sum signals. These spectral patterns produced in the ion mobility spectrum were evaluated automatically via principal component analysis (PCA).The detected peak patterns are characteristic for the respective algae culture; allow the assignment of the individual growth phases and reflect the influence of experimental parameters. These results allow for the first time a continuous monitoring of the algae cultivation and thus an early detection of possible disturbances in the biotechnological process.
Zusammenfassung Für die Detektion von Geruchsmustern in wässrigen Lösungen wurde die Ionenmobilitätsspektromtrie mit einem NH 3 {\mathrm{NH}_{3}} - und einem H2S-Sensor kombiniert. Die leicht- und mittelflüchtigen geruchsaktiven Substanzen wurden mittels eines Nebulisers in die Gasphase überführt. Die Auswertung der Ionenmobilitätsspektren erfolgte mit einer Analyse der Peaks durch überwachte Klassifikation. Dabei wurden die einzelnen Peaks einer reinen Lösung durch Berechnung der stoffspezifischen Ionenmobilitätskonstante ( K 0 {K_{0}} -Wert) klassifiziert. Die entsprechenden Klassen wurden in einer Datenbank gespeichert. Durch die Berechnung der K 0 {K_{0}} -Werte unbekannter Peaks und deren Abgleich mit der Datenbank wurde eine Aussage über das Vorhandensein eines Fremdstoffes angegeben. Für die Auswertung der NH 3 {\mathrm{NH}_{3}} - und H2S-Daten wurden die Signalverläufe mit einer Funktion modelliert. Die beschreibenden Parameter dieser Funktion dienen zur Erstellung einer Regressionsgeraden in Abhängigkeit der Konzentrationen der Proben. Durch die mathematische Beschreibung der Kurvenverläufe konnte der Einfluss der Feuchtigkeitsausschläge und die benötigten Messdauer reduziert werden. Mit Hilfe der parametrisierten Funktion können die Signalverläufe von unbekannten Messdaten modelliert und mit den Regressionsgeraden die jeweiligen Konzentrationen bestimmt werden. Gesamtergebnis der Arbeit ist eine Software, in welcher die Messdaten der Sensorsysteme eingelesen und ausgewertet sowie die entsprechenden Ergebnisse in visueller Form dargestellt werden können. Zusammenfassend konnte mit der mathematischen Implementierung ein Programm realisiert werden, welches eine automatisierte Aussage über das Vorkommen von Fremdstoffen in wässrigen Lösungen generiert.
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