An inexpensive UV-LED photoacoustic based real-time sensor-system detecting exhaled trace-acetone.

In this research we present a low-cost system for breath acetone analysis based on UV-LED photoacoustic spectroscopy. We considered the end-tidal phase of exhalation, which represents the systemic concentrations of volatile organic compounds (VOCs) - providing clinically relevant information about the human health. This is achieved via the development of a CO2-triggered breath sampling system, which collected alveolar breath over several minutes in sterile and inert containers. A real-time mass spectrometer is coupled to serve as a reference device for calibration measurements and subsequent breath analysis. The new sensor system provided a 3σ detection limit of 8.3 ppbV and an NNEA of 1.4E-9 Wcm-1Hz-0.5. In terms of the performed breath analysis measurements, 12 out of 13 fell within the error margin of the photoacoustic measurement system, demonstrating the reliability of the measurements in the field.

Semi-Selective Array for the Classification of Purines with Surface Plasmon Resonance Imaging and Deep Learning Data Analysis.

In process analytics or environmental monitoring, the real-time recording of the composition of complex samples over a long period of time presents a great challenge. Promising solutions are label-free techniques such as surface plasmon resonance (SPR) spectroscopy. They are, however, often limited due to poor reversibility of analyte binding. In this work, we introduce how SPR imaging in combination with a semi-selective functional surface and smart data analysis can identify small and chemically similar molecules. Our sensor uses individual functional spots made from different ratios of graphene oxide and reduced graphene oxide, which generate a unique signal pattern depending on the analyte due to different binding affinities. These patterns allow four purine bases to be distinguished after classification using a convolutional neural network (CNN) at concentrations as low as 50 µM. The validation and test set classification accuracies were constant across multiple measurements on multiple sensors using a standard CNN, which promises to serve as a future method for developing online sensors in complex mixtures.

A sub-ppbv-level Acetone and Ethanol Quantum Cascade Laser Based Photoacoustic Sensor - Characterization and Multi-Component Spectra Recording in Synthetic Breath.

Trace gas analysis in breath is challenging due to the vast number of different components. We present a highly sensitive quantum cascade laser based photoacoustic setup for breath analysis. Scanning the range between 8263 and 8270 nm with a spectral resolution of 48 pm, we are able to quantify acetone and ethanol within a typical breath matrix containing water and CO2. We photoacoustically acquired spectra within this region of mid-infra-red light and prove that those spectra do not suffer from non-spectral interferences. The purely additive behavior of a breath sample spectrum was verified by comparing it with the independently acquired single component spectra using Pearson and Spearman correlation coefficients. A previously presented simulation approach is improved and an error attribution study is presented. With a 3σ detection limit of 6.5 ppbv in terms of ethanol and 250 pptv regarding acetone, our system is among the best performing presented so far.

Correlation of Acceleration Curves in Gravitational Direction for Different Body Segments during High-Impact Jumping Exercises.

Osteoporosis is a common disease of old age. However, in many cases, it can be very well prevented and counteracted with physical activity, especially high-impact exercises. Wearables have the potential to provide data that can help with continuous monitoring of patients during therapy phases or preventive exercise programs in everyday life. This study aimed to determine the accuracy and reliability of measured acceleration data at different body positions compared to accelerations at the pelvis during different jumping exercises. Accelerations at the hips have been investigated in previous studies with regard to osteoporosis prevention. Data were collected using an IMU-based motion capture system (Xsens) consisting of 17 sensors. Forty-nine subjects were included in this study. The analysis shows the correlation between impacts and the corresponding drop height, which are dependent on the respective exercise. Very high correlations (0.83-0.94) were found between accelerations at the pelvis and the other measured segments at the upper body. The foot sensors provided very weak correlations (0.20-0.27). Accelerations measured at the pelvis during jumping exercises can be tracked very well on the upper body and upper extremities, including locations where smart devices are typically worn, which gives possibilities for remote and continuous monitoring of programs.

An Algorithmic Approach to Compute the Effect of Non-Radiative Relaxation Processes in Photoacoustic Spectroscopy.

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 relaxation 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.

Graphene-enhanced plasmonic nanohole arrays for environmental sensing in aqueous samples.

The label-free nature of surface plasmon resonance techniques (SPR) enables a fast, specific, and sensitive analysis of molecular interactions. However, detection of highly diluted concentrations and small molecules is still challenging. It is shown here that in contrast to continuous gold films, gold nanohole arrays can significantly improve the performance of SPR devices in angle-dependent measurement mode, as a signal amplification arises from localized surface plasmons at the nanostructures. This leads consequently to an increased sensing capability of molecules bound to the nanohole array surface. Furthermore, a reduced graphene oxide (rGO) sensor surface was layered over the nanohole array. Reduced graphene oxide is a 2D nanomaterial consisting of sp2-hybridized carbon atoms and is an attractive receptor surface for SPR as it omits any bulk phase and therefore allows fast response times. In fact, it was found that nanohole arrays demonstrated a higher shift in the resonance angle of 250-380% compared to a continuous gold film. At the same time the nanohole array structure as characterized by its diameter-to-periodicity ratio had minimal influence on the binding capacity of the sensor surface. As a simple and environmentally highly relevant model, binding of the plasticizer diethyl phthalate (DEP) via π-stacking was monitored on the rGO gold nanohole array realizing a limit of detection of as low as 20 nM. The concentration-dependent signal change was studied with the best performing rGO-modified nanohole arrays. Compared to continuous gold films a diameter-to-periodicity ratio (D/P) of 0.43 lead to a 12-fold signal enhancement. Finally, the effect of environmental waters on the sensor was evaluated using samples from sea, lake and river waters spiked with analytically relevant amounts of DEP during which significant changes in the SPR signal are observed. It is expected that this concept can be successfully transferred to enhance the sensitivity in SPR sensors.