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Atemgasanalyse ist ein junges und vielversprechendes Feld im Bereich der diagnostischen Medizin. Der Ansatz verspricht einfach zugängliche und leicht wiederholbare Probennahme die zum einen non-invasiv ist und zugleich Rückschlüsse auf Vorgänge im menschlichen Körper und bspw. dessen Gesundheitszustand zulässt. Seit Ende des 20. Jahrhunderts gibt es Massenspektrometer die es ermöglicht haben mehrere Tausend verschiedene Stoffe in der Ausatemluft nachzuweisen. Diese Technologien verbessern sich stetig und ermöglichen es die Vorgänge und Zusammenhänge zwischen Zusammensetzung der Ausatemluft und systemischen Prozessen besser zu verstehen. Die bei Studien mit Massenspektrometern ermittelten Biomarker, deren qualitative und quantitative Detektion Gesundheitsdiagnosen ermöglichen, haben aber noch nicht den Weg in den klinischen Alltag gefunden. Das Problem sind meistens die hohen Anschaffungskosten, komplizierte Datenauswertung und zumeist geringe Verfügbarkeit und Immobilität dieser Messgeräte. Die photoakustische Spektroskopie ist eine selektive und hochsensitive Messmethode, die es ermöglichen soll den Biomarker „Aceton“, der grundsätzlich die Metabolisierung von Fetten widerspiegelt, schnell und reproduzierbar quantitativ zu detektieren. Dabei müssen Hindernisse wie Querempfindlichkeiten, ausgelöst durch die komplexe Zusammensetzung der Messmatrix Atemgas, bei gleichzeitig kleine Aceton Konzentrationen (200-800 parts-per-billion) überwunden werden. Verschiedene Wellenlängenbereiche mit unterschiedlichen Lichtquellen, akustisch resonante sowie innovative Messzellendesigns und anspruchsvolle Datenauswertung mittels komplexer Algorithmik sind nötig um das Ziel, die Entwicklung eines kompakten, günstigen und zuverlässigen Acetonsensors, zu erreichen.
With an atmospheric concentration of approximately 2000 parts per billion (ppbV, 10−9) methane (CH4) is the second most abundant greenhouse gas (GHG) in the atmosphere after carbon dioxide (CO2). The task of long-term and spatially resolved GHG monitoring to verify whether climate policy actions are effective, is becoming more crucial as climate change progresses. In this paper we report the CH4 concentration readings of our photoacoustic (PA) sensor over a five day period at Hohenpeißenberg, Germany. As a reference device a calibrated cavity ringdown spectrometer Picarro G2301 from the meteorological observatory was employed. Trace gas measurements with photoacoustic instruments promise to provide low detection limits at comparably low costs. However, PA devices are often susceptible to cross-sensitivities related to environmental influences. The obtained results show that relaxation effects due to fluctuating environmental conditions, e.g. ambient humidity, are a non-negligible factor in PA sensor systems. Applying algorithm compensation techniques, which are capable of calculating the influence of relaxational effects on the photoacoustic signal, increase the accuracy of the photoacoustic sensor significantly. With an average relative deviation of 1.11 % from the G2301, the photoacoustic sensor shows good agreement with the reference instrument.
The performance of a photoacoustic trace gas sensor for the detection of acetone in N2 and synthetic air is reported. The sensor system utilises an amplitude modulated UV LED. The light source has an emission maximum at 278 nm and a maximum CW output power of 300 mW according to the datasheet. Three different collimating and focusing approaches have been investigated to guide the highly divergent LED light into the acoustic resonator of the photoacoustic measurement cell. A 3D printed aluminium cell was designed to optimize light coupling by simultaneously minimizing the photoacoustic background signal generation. Hence, the diameter of the resonator was set to a comparable large diameter of 10 mm and the inner walls of the resonator were mirror polished. The additive manufacturing procedure allowed for integration of a spirally formed gas channel, enabling gas heating prior to detection. The sensor performance was investigated by measuring acetone in N2 and synthetic air at different concentrations. The UV LED current was set to 86 % of the maximum value according to the datasheet of the light source in order to increase the lifetime and thermal stability. An Allan-Werle deviation analysis validates a stable sensor performance. The limit of detection (LoD) was determined at a 3σ noise level with a 10 s lock-in amplifier time constant by sampling data points over 20 s with a data acquisition rate of 5 Hz. LoDs of 80.8 ppbV and 19.6 ppbV were obtained for acetone in N2 and synthetic air, respectively.
We present a sensitive UV LED photoacoustic setup for the detection of gaseous acetone and discuss its applicability towards breath analysis. We investigated the performance of the sensor for low acetone concentrations down to 0.1 parts per million (ppmV). The influences of temperature, flow, pressure, optical power and LED duty cycle on the measured signal have been examined. To gain a better understanding of the different effects on the photoacoustic signal, correlation analysis was applied and feature importance was determined using a large measured dataset. Furthermore, the cross-sensitivities towards O2, CO2 and H2O have been studied extensively. Finally, the sensor’s performance to detect acetone between 0.1–1 ppmV within gas mixtures simulating breath exhale conditions has been investigated, too. With a limit of detection (LoD) of 12.5 parts per billion (ppbV) (3σ) measured under typical breath exhale gas mixture conditions, the sensor demonstrated a high potential for the application of acetone detection in human breath analysis.
We present a sensitive and compact interband cascade laser (ICL) based photoacoustic setup for the detection of gaseous hydrocarbons and discuss its applicability towards trace gas analysis. We investigated the performance of the sensor for trace concentrations of methane, ethane and acetylene diluted in nitrogen. The excitation of methane and ethane was accomplished using one tunable diode laser, covering a range from 3360 to 3372 nm, which was replaced by a separate ICL at 3025 nm for acetylene detection. The influence of ambient parameters such as temperature, flow rate and pressure as well as potential cross-sensitivities towards O2 and H2O have been examined in terms of methane and acetylene detection. A series of simulations proved several of these influences to be attributed to relaxation effects. With a 3σ limit of detection (LoD) of 6.8 parts per billion (ppbV) in case of methane, 2.3 ppbV regarding ethane and 3.6 ppbV in terms of acetylene, the sensor demonstrates a great potential for applications in the field of trace gas analysis.
Successful transfer of photoacoustic gas sensors from laboratory to real-life applications requires knowledge about potential cross-sensitivities towards environmental and gas matrix changes. Multi-dimensional calibration in case of cross-sensitivities can become very complex or even unfeasible. To address this challenge, we present a novel algorithm to compute the collision based non-radiative efficiency and phase lag of energy relaxation on a molecular level (CoNRad) for photoacoustic signal calculation. This algorithmic approach allows to calculate the entire elaxation cascade of arbitrarily complex systems, yielding a theoretical photoacoustic signal. In this work the influence of varying bulk compositions, i.e. nitrogen (N2), oxygen (O2) and water (H2O) on the photoacoustic signal during methane (CH4) detection is demonstrated. The applicability of the algorithm to other photoacoustic setups is shown exemplary by applying it to the relaxational system investigated in [1]. Hayden et al. examined the effect of water on photoacoustic carbon monoxide (CO) detection.
Digital Twin of a Photoacoustic Trace Gas Sensor for Monitoring Methane in Complex Gas Compositions
(2022)
The digitalization of industrial processes requires smart sensor systems. Photoacoustic spectroscopy is well suited for this purpose as it allows for small-sized and low-cost trace gas analysis. However, the method is susceptible to changes in measurement conditions and standard calibration routines often fail to correct for all changes. We therefore created a Digital Twin (DT) of a photoacoustic trace gas sensor for methane and evaluated it regarding variations in gas composition (CH4, N2, O2, CO2, H2O), temperature and pressure. With a mean absolute percentage error of 0.8 % the accuracy of the sensor after DT compensation significantly exceeds the 24 % achieved based on standard calibration in nitrogen. For the first time, we can fully analytically compute the photoacoustic signal under moderate ambient conditions with an error in the ppbV range by taking a holistic approach. Assuming knowledge of the underlying energy transfer processes, the model of this Digital Twin can be adapted to any microphone based photoacoustic sensor for monitoring any analyte species.