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Der Mensch ist in der Lage, sehr schnell den Zustand seiner Umgebung zu erfassen, indem er Informationen über verschiedene Sinneskanäle aufnimmt und miteinander verarbeitet. Für technische Systeme steht heute eine Vielzahl preiswerter Sensoren zur Verfügung, die in ihrer Leistungsfähigkeit teils deutlich über die menschlichen Sinnesorgane hinausgehen. Dennoch ist eine ähnlich umfassende Bewertung der Umgebung noch nicht möglich, weil die einzelnen Sensordaten nicht ausreichend fusioniert und interpretiert werden.
In der Anlagenüberwachung nicht nur in der chemischen Industrie sind heute dedizierte, d. h. für genau eine spezifische Applikation ausgelegte Sensorsysteme üblich, meist verbunden mit hohen Kosten, u. a. wegen der geringen Stückzahlen, die keine Economy of Scale erlauben. Ergänzt werden diese begrenzten technischen Systeme durch den Menschen, der mit seiner 'Sensorik' ungewöhnliche Zustände und mögliche Gefahrensituationen allerdings nur punktuell erfassen kann.
Durch die Verfügbarkeit ausreichender Rechenleistung zur Interpretation der entstehenden Datenflut ist ein Paradigmenwechsel in der sensorischen Überwachung von Anlagen möglich, der in diesem Projekt erstmalig adressiert werden soll. Erwünscht ist eine flächige Erfassung multimodaler Anlagendaten und damit eine deutliche Verbesserung der Bewertungsmöglichkeiten, z.B. zur frühzeitigen Erkennung von Leckagen bei Energie-trägern (Druckluft, Wasserdampf, Gas und zukünftig zunehmend Wasserstoff).
Optofluidic Sensor for Rapid and Sensitive Detection of Faecal Pigments in Water Quality Monitoring
(2026)
According to the World Health Organization (WHO), at least two billion people worldwide rely on drinking water sources contaminated with faeces.1 UNICEF reports that current methods for detecting faecal contamination are often expensive, time-consuming (typically requiring 18–24 hours), and generally unsuitable for on-site analysis.2 Hence, there is an urgent need for rapid analytical methods that can reliably assess drinking water quality directly in the field.
Our approach utilizes the weak intrinsic fluorescence of faecal pigments such as urobilin (UB), whose emission is enhanced through complexation with Zn²⁺ in alcoholic media, known as Schlesinger’s test. However, this classical method for faecal contaminant detection has significant limitations: UB–Zn²⁺ complexes exhibit only weak fluorescence in water, their fluorescence decays over time, and is interfered by fluorescence from humic substances naturally present in surface waters. These limitations in detection in aqueous media motivated us to explore an organic–aqueous extraction system using hexanol to improve fluorescence response and signal stability.
To address this, we present a dual strategy involving the use of different Zn²⁺ salts and hexanol as an extraction and fluorescence-enhancing medium. We observed a clear dependence of the fluorescence yield of UB–Zn²⁺ complexes on the counter anions of different Zn²⁺ salts. Among them, UB–Zn(NO₃)₂ complex was showing the highest fluorescence intensity in hexanol. The extraction of UB–Zn²⁺ complexes into hexanol provided enhanced and temporally stable fluorescence emission for a reliable sensing approach.3 The photophysics of the UB–Zn²⁺ complex in hexanol and Job’s plots confirmed non-trivial complex stoichiometries. Nonetheless, the developed analytical method showed sensitive (nano- and sub-nanomolar concentration) response for UB detection with negligible fluorescence interference from humic substances commonly present in environmental water.
Furthermore, a 3D-printed optofluidic platform was developed to perform in-channel extraction and real-time fluorescence detection. This platform was printed all at once using a commercial SLA printer with high resolution and transparent resins. The fluidic part allowed for droplet-based extraction by chaotic advection, by means of a miniaturized pump. The optical detection combined an LED for excitation and a USB photomultiplier tube module for low fluorescence signal digital acquisition, potentially on an embedded device such as a tablet. This configuration enabled rapid, sensitive, and interference-minimized detection of faecal pigments in water, demonstrating the potential of optofluidic sensing for on-site water quality monitoring.
Since the global COVID-19 pandemic, there has been an increased focus on systematically monitoring pathogens in raw wastewater - a practice known as wastewater-based epidemiology (WBE). This approach, aligned with the One Health concept, the revised EU Urban Wastewater Treatment Directive (2024), and Germany’s amended Infection Protection Act (2023), aims to generate health data independently of individual testing and reporting behaviors through wastewater surveillance. – Germany’s AMELAG project implemented wastewater surveillance at approximately 170 treatment plants, with biweekly sampling. This infrastructure - comprising treatment plants, logistics, laboratories, and health authorities - also provided us samples that were analyzed for their levels of a series of anthropogenic markers. These markers improve data accuracy by accounting for site-specific variations in wastewater composition and flow rates, such as those caused by stormwater runoff. Beyond epidemiology, wastewater surveillance provides valuable insights into the spread of antimicrobial resistance (AMR), drug consumption, industrial discharges, and the efficiency of wastewater treatment plants in eliminating indicator substances. To assess these factors, cost-effective, high-throughput methods such as ELISA (Enzyme-Linked Immunosorbent Assay) offer a practical solution. This study examines ELISA’s application in detecting diclofenac, carbamazepine, and bisphenol A in wastewater samples from various locations.
Micropollutants, including various emerging contaminants, are continuously released into the environment. Detecting their presence using conventional analytical methods is often expensive and time-consuming, making large-scale monitoring impractical. To effectively protect ecosystems and human health, rapid and cost-efficient screening methods are essential. Furthermore, the need to monitor the entire water cycle for micropollutants is becoming increasingly critical, particularly from a One Health perspective, as climate change and growing demands for water reuse amplify environmental challenges. – Antibody-based methods, commonly referred to as immunoassays, offer a promising solution. These rapid and cost-effective techniques can fill information gaps and provide sensors and process analytical technology with short response times. A wide range of immunoanalytical formats is available, from laboratory-based methods to portable analyzers and online sensors. Ensuring the availability of high-quality antibodies is essential to the reliability of these approaches. This talk presents how a whole range of immunoanalytical methods can be employed to trace emerging contaminants in the environment. An indicator for specific industrial inputs is bisphenol A which is also an endocrine disruptor. Additionally, pharmaceuticals serve as important markers of human impact on the water cycle. Natural tracers, such as endogenous hormones and bile acids, help track wastewater pathways, while anthropogenic markers - most notably caffeine - serve as indicators of human activity, frequently appearing in environmental water samples.
Methane emissions are a significant environmental and safety concern, yet many gas tomography systems intended to measure them require manual alignment, reliable high-bandwidth links, or fiducials. We present a lightweight, fully autonomous framework enabling line-of-sight inter-robot Tunable Diode Laser Absorption Spectroscopy (TDLAS) measurements without such constraints. A sensor robot equipped with a gimbal-mounted TDLAS unit tracks a reflector robot bearing an illuminated, color-controllable target. Coarse localization is achieved via RTK-GNSS, with vision-based fine tracking and passive time synchronization handled onboard. The system, based on off-the-shelf Pixhawk controllers and ArduPilot firmware, was validated in a 15m × 7m outdoor trial. Despite GNSS inaccuracies and deliberate occlusion by a methane-filled bag, the system retained lock, recovered from visual loss in under one second, and captured a 2800 ppm·m plume signature. These results demonstrate robust, scalable methane sensing for mobile gas tomography or standalone leak detection. Core components are released open-source to support future deployment.
Methane emissions are a significant environmental and safety concern, yet many gas tomography systems intended to measure them require manual alignment, reliable high-bandwidth links, or fiducials. We present a lightweight, fully autonomous framework enabling line-of-sight inter-robot Tunable Diode Laser Absorption Spectroscopy (TDLAS) measurements without such constraints. A sensor robot equipped with a gimbal-mounted TDLAS unit tracks a reflector robot bearing an illuminated, color-controllable target. Coarse localization is achieved via RTK-GNSS, with vision-based fine tracking and passive time synchronization handled onboard. The system, based on off-the-shelf Pixhawk controllers and ArduPilot firmware, was validated in a 15m × 7m outdoor trial. Despite GNSS inaccuracies and deliberate occlusion by a methane-filled bag, the system retained lock, recovered from visual loss in under one second, and captured a 2800 ppm·m plume signature. These results demonstrate robust, scalable methane sensing for mobile gas tomography or standalone leak detection. Core components are released open-source to support future deployment.
The demand for compact, high-performance optical components has driven the development of increasingly sophisticated and miniaturized optical elements, often requiring complex and costly fabrication methods. In this work, we propose a cost-effective and accessible methodology for the fabrication of lenses and free-form optics using a commercially available stereolithography (SLA) 3D printer. A systematic characterization of six transparent photopolymer resins was conducted in terms of their spectroscopic, optical, and morphological properties, i.e., surface and dimensional properties. The evaluation encompassed parameters such as transmittance, autofluorescence, refractive index, and surface roughness. A straightforward and robust printing and posttreatment protocol was developed, facilitating the fabrication of optical components with over 80% transmittance, minimal intrinsic fluorescence, and a surface quality that is compatible with demanding optical applications. The fabricated components demonstrated excellent dimensional fidelity to digital designs and high reproducibility. To demonstrate the versatility of this approach, aspherical, miniaturized, and free-form lenses were designed and integrated into three fluorescence sensing systems, including oil (strip based) and chlorine (microfluidic based) detection platforms, as well as a smartphone-based SARSCoV-2 biosensor. The integration of customized 3Dprinted optics has been shown to improve signal collection and readout performance, thereby highlighting the potential of this approach for broad application by a wide range of user groups in rapid prototyping and use in miniaturized optical systems. This work represents a significant advancement in the field of additive manufacturing, particularly in relation to the development of functional photonic devices. Furthermore, it opens new prospects for sensor applications in biosensing, microfluidics, imaging, and integrated optics.
Fecal pollution in water poses significant health risks, especially when contaminated sources are used for drinking and food production. Traditional water quality testing methods are expensive, slow, and require skilled personnel, limiting their accessibility. This work addresses these issues by developing a portable fluorometric assay for the detection of the fecal indicator pigment urobilin (UB). The assay uses silane-functionalized glass fiber strips impregnated with zinc chloride, providing a ‘drop-&-detect’ approach with enhanced fluorescence response mediated by the unique complexation properties of ZnCl2 and UB. This approach allows for the detection of UB at sub-nanomolar concentrations in less than 1 min using a 3D-printed setup with miniaturized optical components powered by a smartphone with its camera as a detector. The results validated with a benchtop fluorometer show the effectiveness of this method. The successful application of this userfriendly, rapid, and sensitive assay to real water samples from three rivers and the influx and efflux of a wastewater treatment plant advances field-based water quality monitoring, meets the WHO’s ASSURED criteria, and supports progress toward the global clean water and sanitation goals.
The growing demand for the detection of relevant chemical compounds as close as possible to their point of origin—whether in industrial processes, for (civilian or military) security, or for environmental monitoring—has increased the importance of functional polymers with molecular recognition capabilities. These materials must meet practical requirements arising from very different real-world scenarios in which simple, robust, and field-deployable approaches are needed and in which bioanalytical binders often suffer significant performance losses. Polymer recognition matrices therefore serve as an essential complement to established laboratory-based analytical technologies.
The realization of rapid and reliable onsite detection places specific demands on material design: polymeric recognition layers must be produced with minimal thickness, integrated onto suitable carrier media, and designed for both selectivity and operational robustness. This presentation will introduce our work on molecularly imprinted polymers (MIPs) that have been specifically developed for the detection of relevant contaminants such as pesticides and perfluorinated compounds. Beyond these target analytes, the presentation will show how such polymer layers can support robust, sustainable diagnostic concepts, and it will outline generalizable design principles that enable their extension to a broad spectrum of analytical challenges.
The advancement of portable analytical assays has transformed onsite analysis in several areas, including food safety, environmental monitoring and forensics. The SARS-CoV-2 pandemic has fueled a need for rapid, onsite solutions that enable immediate decision making without the need for and use of laboratory infrastructure. The integration of mobile devices with advanced cameras and significant computing power improves the accessibility and usability of these tests. However, many current methods are limited to the detection of single parameters. The next challenge is to develop robust multiplexed assays that can analyze multiple parameters simultaneously with high sensitivity. In this lecture, innovative approaches developed at BAM will be presented with a focus on supramolecular chemistry, luminescence detection, nanomaterials and miniaturization of devices. Examples will include mesoporous nanomaterials, gated indicator systems, imprinted polymers, microfluidic devices, test strips and smartphone-based analytical tools, focusing on two use cases, i.e., the detection of contaminants in surface waters and immunoanalytical explosives detection.