@article{MuellerWeiglMuellerWilliamsetal., author = {M{\"u}ller, Max and Weigl, Stefan and M{\"u}ller-Williams, Jennifer and Lindauer, Matthias and R{\"u}ck, Thomas and Jobst, Simon and Bierl, Rudolf and Matysik, Frank-Michael}, title = {Comparison of photoacoustic spectroscopy and cavity ring-down spectroscopy for ambient methane monitoring at Hohenpeißenberg}, series = {Atmospheric Measurement Techniques}, volume = {16}, journal = {Atmospheric Measurement Techniques}, number = {18}, publisher = {Copernicus Publications}, issn = {1867-8548}, doi = {10.5194/amt-16-4263-2023}, pages = {4263 -- 4270}, abstract = {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 5 d period at Hohenpeißenberg, Germany. As a reference device, a calibrated cavity ring-down spectrometer, Picarro G2301, from the meteorological observatory of the German Weather Service (DWD) 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 fluctuating environmental conditions, e.g. ambient humidity. The obtained results show that for PA sensor systems non-radiative relaxation effects induced by varying humidity are a non-negligible factor. Applying algorithm compensation techniques, which are capable of calculating the influence of non-radiative relaxation 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\% from the G2301, the photoacoustic sensor shows good agreement with the reference instrument.}, language = {en} } @unpublished{PangerlMoserMuelleretal., author = {Pangerl, Jonas and Moser, Elisabeth and M{\"u}ller, Max and Weigl, Stefan and Jobst, Simon and R{\"u}ck, Thomas and Bierl, Rudolf and Matysik, Frank-Michael}, title = {A Highly Sensitive Acetone and Ethanol Quantum Cascade Laser Based Photoacoustic Sensor: Characterization and Multi-Component Spectra Recording in Synthetic Breath}, series = {SSRN Electronic Journal}, journal = {SSRN Electronic Journal}, publisher = {Elsevier}, doi = {10.2139/ssrn.4305376}, abstract = {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 8260 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.}, language = {en} } @misc{OlbrichPongratzBierletal., author = {Olbrich, Florian and Pongratz, Christian and Bierl, Rudolf and Ehrlich, Ingo}, title = {Method and System for Evaluating a Structural Integrity of an Aerial Vehicle}, language = {en} } @inproceedings{PellerZanklFischeretal., author = {Peller, Sebastian and Zankl, Tobias and Fischer, Christoph and Bierl, Rudolf}, title = {Fast sound field characterization of beamforming capable capacitive micromachined ultrasonic transducer (CMUT) arrays by refracto-vibrometry}, series = {IEEE IUS 2023, International Ultrasonics Symposium, Montr{\´e}al, September 3-8, 2023}, booktitle = {IEEE IUS 2023, International Ultrasonics Symposium, Montr{\´e}al, September 3-8, 2023}, publisher = {IEEE}, isbn = {979-8-3503-4645-9}, issn = {1948-5727}, doi = {10.1109/IUS51837.2023.10308126}, pages = {1 -- 3}, abstract = {We introduce a time-optimized setup based on refracto-vibrometry for the purpose of scanning the sound field of capacitive micromachined ultrasonic transducer (CMUT) arrays primarily for the qualification of their beamforming capability. In comparison to commonly used microphones on a traversing stage the proposed method is substantially faster and consumes only a few minutes of time for a complete two-dimensional sound field containing about 100.000 scan points.}, language = {en} } @misc{RueckBierlLechneretal., author = {R{\"u}ck, Thomas and Bierl, Rudolf and Lechner, Alfred and Graf, Antonia and Dams, Florian and Schreiner, Rupert and Auchter, Eberhard and Kriz, Willy and Deubzer, MIchael and Schiller, Frank and Mottok, J{\"u}rgen and Niemetz, Michael and Margull, Ulrich and Hagel, Georg and Utesch, Matthias and Waldherr, Franz and B{\"o}hm, Matthias and Fraunhoffer, Judith and Gardeia, Armin and Schneider, Ralph and Streubel, Janet and Landes, Dieter and Studt, Reimer and Peuker, Dominik and Scharfenberg, Georg and Hook, Christian and Schuster, Dietwald and Ehrlich, Ingo and Dinnebier, Heinrich and Briem, Ulrich and L{\"a}mmlein, Stephan and Koder, Alexander and Bialek, Adam and Genewsky, Axel and Neumeier, Michael and Schlosser, Philipp and Rabl, Hans-Peter and Paule, Matthias and Galster, Christoph and Schiedermeier, Michael and Zwickel, Andreas and Hobmeier, Christoph and Bischoff, Tobias and Rill, Georg and Schaeffer, Thomas and Arbesmeier, Martin and Groß, Andreas and Schlegl, Thomas and Becker, Mark and Senn, Konrad and Schliekmann, Claus and Scholz, Peter and Sippl, Christian and Grill, Martin}, title = {Forschungsbericht 2011 / Hochschule f{\"u}r Angewandte Wissenschaften - Fachhochschule Regensburg}, editor = {Eckstein, Josef}, address = {Regensburg}, organization = {Hochschule f{\"u}r Angewandte Wissenschaften Regensburg}, issn = {1868-3533}, doi = {10.35096/othr/pub-732}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-7321}, language = {de} } @inproceedings{RothHauslerBierl, author = {Roth, Carina and Hausler, Peter and Bierl, Rudolf}, title = {Einbindung eines 2D-Photodetektors in einen hochintegrierten SPR-Imaging-Sensor}, series = {7. MikroSystemTechnik Kongress "MEMS, Mikroelektronik, Systeme", 23.-25. Oktober 2017, M{\"u}nchen}, booktitle = {7. MikroSystemTechnik Kongress "MEMS, Mikroelektronik, Systeme", 23.-25. Oktober 2017, M{\"u}nchen}, publisher = {VDE-Verlag}, address = {M{\"u}nchen}, isbn = {978-3-8007-4491-6}, pages = {848 -- 850}, abstract = {Die Oberfl{\"a}chenplasmonenresonanzspektroskopie (SPR) ist eine hochempfindliche Messmethode, die es erlaubt, Gase und Fl{\"u}ssigkeiten zerst{\"o}rungs- und markierungsfrei in Echtzeit zu analysieren. Bisher vornehmlich im Labormaßstab in der Bioanalytik und dem Wirkstoffscreening eingesetzt, soll diese Technologie nun miniaturisiert und f{\"u}r weitere Anwendungsgebiete zug{\"a}nglich gemacht werden. Dazu wird ein kompakter Micro-Opto-Electro-Mechanical Systems Sensor (MOEMS) entwickelt, der mit Hilfe des SPR Imaging {\"A}nderungen der chemischen Zusammensetzung verschiedener Fl{\"u}ssigkeiten inline messen kann.}, language = {de} } @inproceedings{BauerVitzthumeckerBierletal., author = {Bauer, Lukas and Vitzthumecker, Thomas and Bierl, Rudolf and Ehrnsperger, Matthias}, title = {Machine-learning-based detection and severity estimation of drought stress in plants using hyperspectral imaging data}, series = {Remote Sensing for Agriculture, Ecosystems, and Hydrology XXVII}, booktitle = {Remote Sensing for Agriculture, Ecosystems, and Hydrology XXVII}, publisher = {SPIE}, doi = {10.1117/12.3072011}, pages = {7}, abstract = {Growing food demand due to population growth, coupled with increasingly frequent and severe droughts caused by climate change make water increasingly scarce. To address this, accurate assessment of plant water demand is essential for precise drought treatment and water conservation. Hyperspectral imaging (HSI) captures hypercubes, a combination of spectral and spatial data and offers promising capabilities for detection of plant stresses. However, most reported approaches only use selected spectral bands or indices, neglecting the full hypercube information. This is assumed to limit the detection accuracy. To overcome these limitations, we aim to develop a measurement pipeline to generate a comprehensive dataset comprising hypercubes of plants under varying drought stress levels along with selected physiological, environmental, and illumination data. This dataset will be used to train suitable data-driven models that enable improved drought stress detection as well as the non-invasive determination of physiological parameters based on HSI data.}, language = {en} } @unpublished{FischerHirschReitmeieretal., author = {Fischer, Johannes and Hirsch, Thomas and Reitmeier, Torsten and Bierl, Rudolf}, title = {Real-time hardware-based processing of high-precision detector signals for surface plasmon resonance spectroscopy}, doi = {10.2139/ssrn.5971170}, pages = {16}, abstract = {Surface plasmon resonance (SPR) is limited by small-signal detectability and drift when subtraction occurs in software after digitization. We introduce an SPR detector that performs on-detector amplification and analog differential readout, eliminating moving parts and software-heavy correction. The hardware-native subtraction boosts the usable ADC range and suppresses illumination and environmental noise. In fixed-angle refractive-index steps (NaCl), the platform resolves Δn_min ≈ 1.8 × 10⁻⁷ RIU compared to 4.6-7.2 × 10⁻⁶ RIU on a commercial comparator and improves small-signal SNR by up to ∼5,000-fold, while remaining competitive at high signal levels. In a model IgG-BSA assay, the detector's low noise floor clarifies early binding and equilibrium transitions. By generating inherently clean raw signals, this hardware-native approach dramatically enhances sensitivity and long-term stability for label-free biosensing and inline process analytics while rendering AI-based or complex post-processing entirely unnecessary. The concept generalizes across platforms and opens a compact route to robust, high-fidelity SPR in complex environments, with a clear path toward multi-wavelength and arrayed detectors for high-throughput chemical monitoring.}, language = {en} }