The gas-sensing performance of the CuO/Cu₂O functionalized with Au NPs towards CO₂, CO, and HC_Mix was investigated by resistance measurement. The type of ligands has an impact on the sensing behaviour of CuO/Cu₂O sensors, and the highest response (39 %) for CO₂ is achieved by Au NPs stabilized with citrate. These differences in behaviour of the films depending on their ligands could be due to insufficient thermal degradation of the ligands.

Ferromagnetic materials change their magnetic properties under load, enabling the implementation of a force sensor. The magnetic field emerging from such a sensor can be measured by secondary sensors to approximate the load acting on the sensor. A test setup simulating a potential application environment is described and its measurement results are presented. Furthermore, relevant magnetic material properties of an exemplarily chosen cold working steel are discussed.

This contribution deals with the exploration of human–robot collaboration using an infrared sensor and artificial intelligence (AI) to improve the safety and efficiency of the collaboration. The main contribution is the unique thermal dataset WLRI-HRC generated in a manufacturing environment and the evaluation of the dataset using different AI network methods.

Microelectromechanical systems mirrors are used in applications such as projection, biological imaging, and light detection and ranging due to their compact size, affordable price, and low power consumption. Piezoelectric actuation with lead zirconate titanate offers high force and fast response but raises environmental concerns due to its lead content. Potassium sodium niobate is a promising lead-free alternative, exhibiting high performance on 200 mm silicon substrates.

In the context of climate change adaptation of cities to mitigate heat stress, citizen participation is a promising approach. A densely distributed measurement network of 59 quality-controlled meteorological low-cost sensors was set up in an urban study area in Pune for continuous data collection by engaging local communities. Analyses of measurements show the suitability of the monitoring network for scientific modelling applications and identify a high active interest of involved citizens.

To improve the accuracy of polarization random noise signal recognition and the noise suppression effect, a polarization random method of noise suppression in a two-dimensional force sensor based on random forest is proposed.