Christian Rembe

For the use of diarylethenes (DAE) in optical microscopy with the aim of overcoming the Abbe limit, interdependent parameters must be coordinated. These include, in particular, the fatigue resistance XA, the position of the isosbestic points (λisos > 400 nm), and the molar extinction coefficients of the closed form (εclosed > 20,000 L/mol·cm). Thirteen photoswitchable DAEs were prepared and spectroscopically characterized (λisos, εclosed, quantum yields φ), among those a first example of a pyridazine substituted derivative. The spectroscopic properties of the closed form of known and hitherto unknown DAEs can be predicted using the spectroscopic Hammett equation, since the excitation energy differences ET,R – ET,H/2.303·R·T correlate linearly with the Hammett parameters σp. Matrix effects of eight different polymers in the spin-coated absorbance modulation layer (AML) on the properties of model DAEs were investigated. A correlation was found between the glass transition temperature Tg and the degradation rate of the photochrome. We found that replacing PMMA with ZEONEX480R results in a 3-fold increase in photostability. DFT calculations of the frontier orbital profiles of the DAEs as well as the changes in the geometric requirements of the 6π-electrocyclic ring closure provide insights into structure–property relationships.

The resolution of an optical microscope is constrained by Abbe’s resolution limit, which assumes linear imaging behavior of the optical system. Fluorescence microscopy, the STED (stimulated emission depletion) method, in particular, exploits nonlinear saturation effects during the stimulated emission depletion of fluorescent molecules to achieve a resolution significantly below the Abbe limit. The DFG collaborative project “Nanoscopy of Composite Materials with Thin Photochromic Layers” (NanoVidere) is investigating how the principle of STED nanoscopy can be transferred to reflection microscopy, thus enabling reflection nanoscopy. This approach involves the use of thin photochromic layers, which can be used to dynamically generate a near-field aperture directly on the sample surface. A major challenge has been the number of switching cycles of the photochromic molecules, which has so far permitted only high-resolution line scans rather than area imaging. The consortium has therefore researched and tested a wide range of new photochromic molecules. The results achieved so far already clearly demonstrate the feasibility of reflection microscopy with resolution beyond the diffraction limit. This approach aims to enable nanoscale spectroscopic measurements with nanometer-scale spatial resolution. In this article, we provide an overview of the progress achieved so far.

This paper presents an image-based laser tracking system with Kalman-filter motion prediction for tracking moving targets. The system uses a scanning laser Doppler vibrometer with two scanning mirrors and an integrated camera, while an ArUco marker serves as the visual target landmark. The proposed method addresses a key limitation of conventional vision-based tracking, namely, loss of tracking during temporary target occlusion. The marker centroid is extracted from the image, and a Kalman filter is applied to predict target motion. As a result, the marker position can still be estimated during short occlusions. A discrete PID controller drives the laser beam to minimize the positional error between the marker centroid and the laser position. Experimental validation on a rotating wheel compares vibration measurements and laser tracking under no-tracking, faulty-tracking, and proper-tracking conditions. Rotation-induced mode splitting is observed in the no-tracking case but is eliminated when reliable tracking is maintained. In addition, tracking provides more stable and sharper harmonic peaks. When the marker is temporarily blocked, conventional image-based tracking fails, whereas the proposed Kalman-assisted approach preserves stable laser alignment and improves tracking robustness.

As William Thomson said, “to measure is to know” – advances in measurement technology drive social progress: digital cameras enable bank transfers, atomic clocks in satellites enable precise navigation, magnetic resonance imaging provides non-invasive insights into the body, and laser measuring sticks enable contactless length measurements. Uncrewed aerial vehicles (UAV) as mobile measuring platforms represent a paradigm shift. Until now, image data has mostly provided only qualitative information, often supported by AI. However, quantitative measurements with known uncertainties are necessary to make statements about the structural integrity of bridges or wind turbines. Therefore, a priority program aims to understand the mechanisms of action of active measurement systems (i.e. exciting the measurement object) and sensor systems on flying platforms. It investigates which laboratory measurement principles can be transferred to UAVs despite limitations of weight, space, energy, and time, and what measurement quality can be achieved. To this end, new measurement principles, sensor technology, signal and communication methods, and the analysis of measurement uncertainties are being researched. Depending on the quantity being measured, the projects are divided into the four application areas: a) geometry, b) position, vibrations and acoustics, c) solids and fluids, d) gases and particles. The results will reveal the previously untapped potential of UAV-based measurement systems, provide quantitative data with valid uncertainties, and thus improve safety of humans, mobility and energy infrastructure as well as environmental monitoring, raw material localization, and groundwater assessment.

Advanced industrial applications in nanotechnology, MEMS, and semiconductor manufacturing demand laser-Doppler vibrometers with femtometer displacement sensitivity. Conventional heterodyne interferometers provide high linearity and accuracy for industrial measurements but are fundamentally limited by quantum shot noise, whose disruptive influence effectively decreases with increasing measured light power. Although laser safety regulations permit a laser power of up to 10mW for a 1550nm measuring beam, temperature-sensitive structures often require lower light power. Note that a laser power of 10mW focused on 10 µm^2 corresponds to an irradiance of 1GWm^(−2). Highest resolution needs to be achieved at low laser powers of the measurement beam, which presents a challenge for shot-noise-limited measurements. In this work, we present a new resolution record for the demodulated displacement signal of our squeezedlight- enhanced heterodyne laser-Doppler vibrometer. Our system achieved a displacement sensitivity of 2.6 fm/√Hz with only 0.36 mW of measurement power. Our results demonstrate improved performance beyond the shot noise limit without increasing optical power, approaching sub-fm precision in vibration measurements.

Unmanned Aerial Vehicles (UAVs) have become integral to modern applications, including smart agricultural robotics, where reliability is essential to ensure safe and efficient operation. It is commonly recognized that traditional fault diagnosis approaches usually rely on vibration and noise measurements acquired via onboard sensors or similar methods, which typically require continuous data acquisition and non-negligible onboard computational resources. This study presents a portable Laser Doppler Vibrometer (LDV)-based system designed for noncontact, offboard, and high-sensitivity measurement of UAV vibration signatures. The LDV measurements are analyzed using a Deep Extreme Learning-based Neural Network (DeepELM-DNN) capable of identifying both propeller fault type and severity from a single 1 s measurement. Experimental validation on a commercial quadcopter using 50 datasets across multiple induced fault types and severity levels demonstrates a classification accuracy of 97.9%. Compared to conventional onboard sensor-based approaches, the proposed framework shows strong potential for reduced computational effort while maintaining high diagnostic accuracy, owing to its short measurement duration and closed-form learning structure. The proposed LDV setup and DeepELM-DNN framework enable noncontact fault inspection while minimizing or eliminating the need for additional onboard sensing hardware. This approach offers a practical and scalable diagnostic solution for large UAV fleets and next-generation smart agricultural and industrial aerial robotics.

Pupillary oscillations can correlate with brain activity as measured using electroencephalography (EEG), particularly in the region of the frontal lobe of the brain. Based on this approach, a non-contact EEG has been developed in our lab, offering the advantages that come with remote measuring, such as ease-of-use and flexibility. However, the frequency spectra resulting from the Fourier transform of pupil-size time-series data are in need of pre-processing, in order to show useful signal data. In this contribution, we discuss different pre-processing methods, and show best practices when using this novel approach of working with pupillary spectra. We deal with artefacts and noise; and demonstrate, using data from the ongoing work with our optical EEG setup, the improvements that can be made, recovering a synthetical sine of only 0.04 px² amplitude, invisible in the unfiltered data.

Heterodyne interferometers with a Bragg cell (an acousto-optical modulator) as a frequency shifter are widely used, for example as the sensor in a Laser Doppler Vibrometer (LDV). An optical phase-locked loop (OPLL) can replace the Bragg cell and allows the carrier frequency to be set flexibly. We derived an electric network model for the OPLL based on the small-signal approximation and used it to explore the influence of phase delays generated by optical pathlengths in the interferometer. This small-signal model of the OPLL-LDV, which includes power feedback, is derived from network theory for an OPLL matched to an LDV. Our model allows the investigation of noise performance in dependence of OPLL-LDV phase delays, OPLL bandwidth, laser noise and working distance of the LDV. The comparison with measurements performed with our experimental setup confirms the validity of our model. Finally, we explore the degradation of coherence (related to the noise behavior of the photodetector) at different delays introduced by varying the working distance. The insights of this investigation allow to set the phase delay in the OPLL optimally in respect to the working distance of the interferometer.

Heterodyne interferometers with a Bragg cell (an acousto-optical modulator) as a frequency shifter are widely used, for example as the sensor in a Laser Doppler Vibrometer (LDV). An optical phase-locked loop (OPLL) can replace the Bragg cell and allows the carrier frequency to be set flexibly. We derived an electric network model for the OPLL based on the small-signal approximation and used it to explore the influence of phase delays generated by optical pathlengths in the interferometer. This small-signal model of the OPLL-LDV, which includes power feedback, is derived from network theory for an OPLL matched to an LDV. Our model allows the investigation of noise performance in dependence of OPLL-LDV phase delays, OPLL bandwidth, laser noise and working distance of the LDV. The comparison with measurements performed with our experimental setup confirms the validity of our model. Finally, we explore the degradation of coherence (related to the noise behavior of the photodetector) at different delays introduced by varying the working distance. The insights of this investigation allow to set the phase delay in the OPLL optimally in respect to the working distance of the interferometer.