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We present the development and characterization as well as comprehensive interference studies of a photoacoustic NO2 trace gas detection system. The system is based on an off-beam quartz enhanced photoacoustic scheme (off-beam QEPAS) and signal generation was initiated by amplitude modulating a low-cost diode laser emitting at 450 nm. The QEPAS sensor element features double-resonant amplification, still it is only ∼ 5 × 5 × 2.5 mm in size. The individual and combined resonance characteristics were investigated and specified to 52 dB amplification, adding up 15 dB acoustic- and 37 dB mechanical-resonance amplification. The linearity of the photoacoustic signal dependency on the analyte concentration was verified from 200 ppbV to 100 ppmV NO2 in synthetic air. The detection limit (3σ) was determined to 1.8 ppbV using a lock-in time constant of 10 s and an averaging time of 20 s. The normalized noise equivalent absorption coefficient was specified to 2.5·10−8 W cm−1 Hz−0.5. The stability of the signal was investigated over time and a slight drift by 1‰ was observed after 30 min without temperature stabilizing the photoacoustic cell (PAC). Noise analysis was performed by means of Allan deviation and the inverse dependency of response time and precision of the system on the lock-in time constant was outlined. We performed interference analyses towards N2, O2, CO2, H2O and acoustic noise, respectively. Although neither spectral interferences nor losses due to slow NO2 VT-relaxation were observed, O2 was identified to cause a 15% signal drop due to VVNO2-O2-relaxation. Changing H2O concentrations were found to cause acoustic detuning, which cannot be compensated by adjusting the frequency of modulation, because of the double-resonant feature of the PAC. However, alternative approaches of compensation were discussed. Finally, we carried out heavy traffic noise simulations and determined the QEPAS setup to be 46 times less susceptible towards ambient noise compared to standard microphone-based photoacoustic setups.
The analysis of surface water, groundwater, drinking water as well as sewage is important to get information about the contamination of the water cycle. Currently, these time-consuming investigations require special equipment, like for example hyphenated mass spectrometry. Surface plasmon resonance (SPR) is a faster alternative as it is highly sensitive to changes in the dielectric medium next to a thin metal layer and makes it a quasi-universal detector. Therefore, and due to the labelfree nature, SPR is a widely used sensing tool for real‐time monitoring of molecular interactions of various analytes. SPR imaging (SPRi) has several advantages to standard surface plasmon resonance, as it allows to observe many analytes in parallel as well as the integration of referencing technologies. However, the homogenous illumination of a large area (several millimeters) with a small light source is challenging and demands new approaches. Allopurinol, a drug used to lower the blood concentration of urate and hence decrease the affection of gout, gets metabolized to oxipurinol in the body and dropped out almost entirely by urinary excretion. After wastewater treatment, concentrations of oxipurinol up to 21.7 μg•L-1 are detected. Further tracking of oxipurinol in the urban water cycle showed its presence in rivers and streams or even in groundwater. Therefore, the high biological stability of oxipurinol allows this molecule to be used as a marker for domestic wastewater in the environment. For the detection of oxipurinol by SPR graphene was used as receptive layer, as the analyte can bind via π-stacking to this surface. An SPRi technique was developed and compared to conventional SPR system for the detection of oxipurinol.
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 describe the miniaturization of the Surface Plasmon Resonance (SPR) technology which mainly finds its applications in pharmaceutical screening and biotechnology so far. SPR spectroscopy is a label-free, non-destructive and highly sensitive measurement principle detecting changes in the refractive index in striking distance to a gold surface. A transfer of this technology to a miniaturized sensor will broaden the range of possible applications. A promising feature which is included in the miniaturized system is the angle-dependent recording of the SPR signals without moving parts. Commercial SPR assays are mainly working with a small number of sensing spots. In contrast, the SPR imaging system shown here will allow to use an array of many sensing spots. In combination with chemical receptors designed as an artificial nose, the simultaneous detection of many analytes is envisioned for future applications.
We describe how to build a homogeneous light source for Surface Plasmon Resonance Imaging (SPRi) which mainly finds its applications in pharmaceutical screening and biotechnology so far. SPR spectroscopy is a label-free, non-destructive and highly sensitive measurement principle for detecting changes in the refractive index in close vicinity of a gold surface. A transfer of this technology to a miniaturized sensor will broaden the range of possible applications. Commercial SPR assays are mainly working with a small number of sensing spots. In contrast, the SPR imaging system shown here will allow the use of an array of many sensing spots. In combination with chemical receptors designed as an artificial nose or an electronic tongue, the simultaneous detection of many analytes is envisioned. So far, lasers or other inhomogeneous light sources were used to illuminate the sensing surface, which is decreasing the systems sensitivity. We show a compact ( 300mm2) homogeneous top hat profile. The combination of a high bit-resolution camera with our new light source enables a reflectivity based surface plasmon resonance imaging system with a high refractive index unit (RIU) resolution.
Confidence in results of an Artificial Neural Networks (ANNs) is increased by preferring to reject data, that is not trustful, instead of risking a misclassification. For this purpose a model is proposed that is able to recognize data, which differs significantly from the training data, during inference. The proposed model observes all activations of the hidden layers, as well as input and output layers of an ANN in a grey-box view. To make ANNs more robust in safety critical applications, this model can be used to reject flawed data, that is suspected to decrease the accuracy of the model. If this information is logged during inference, it can be used to improve the model, by training it specifically with the missing information. An experiment on the MNIST dataset is conducted and its results are discussed.
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.