The paper presents a specimen and evaluation method for interface structural resolution testing of X-ray computed tomography systems based on CT simulations. The geometry is oriented to the norms of image quality investigation. The evaluation is based on profile lines of the cross-sectional images that pass through the boreholes. All statements on resolution refer to the entire measurement chain and, thus, in addition to the reconstruction algorithm also to the surface determination method used.

Differential scanning calorimetry (DSC) is a widely used tool to analyze thermal material properties. This study focuses on the advancement of a miniaturized DSC chip as an alternative to conventional devices. The first development steps for the integration of a weighing system are shown, starting with model considerations and simulation-based optimization to initial measurements. Three different measurement methods are investigated and show promising results.

Diabetes Mellitus (DM) is one of the very common diseases with no viable cure. However, it can be controlled by regulating the daily sugar intake. Diabetic patients need to prick their fingers a few times a day for monitoring sugar levels. To find an alternative, researchers have been working for decades on the development of a true non-invasive technique. In this effort, we developed a cost-effective non-invasive technique for measuring blood sugar levels using capacitance spectroscopy.

We present a photoacoustic sensor enabling fast, inexpensive, and highly sensitive methane detection in environmental monitoring applications. Six different T-cell designs were both theoretically and experimentally investigated. The aim was to understand the photoacoustic signal generation and resonances in relation to the different cell geometries, and determine the long-term stability and the detection limits for methane. These were below the methane background concentration in air of 1.8 ppm.

A fundamental problem of machine learning (ML) is measurement uncertainty and the influence on ML results. Measurement uncertainty, which is critical in hazardous gas detection, is directly addressed in this paper. A previously published toolbox is extended for regression. One of the benefits of this approach is obtaining a better understanding of where the overall system should be improved. This can be achieved by either improving the trained ML model or using a sensor with higher precision.

Imaging of greenhouse gases is of great interest due to global warming. A spectroscopic method, using an active illumination of the scene, is presented. It allows for imaging and concentration measurements of much smaller gas plumes and leaks than current state-of-the-art gas cameras (optical gas imaging cameras). A real-time camera is realized and validated using known methane concentrations.