Open Access

Carbon fiber-epoxy laminates are used in aerospace manufacturing, e.g. as substrates for solar cells of satellites. Commonly, fibers or fibermats are impregnated with epoxy resin and placed in the required orientation. During subsequent curing, the resin molecules are crosslinked. Cured parts are characterized by their glass transition temperature (Tg). It has been observed that Tg of epoxy matrix resin vary with recorded absolute air humidity during wet fiber placement manufacturing. Based on the production data of a series production of 203 carbon fiber laminates for space application, an empirical linear relationship between the absolute air humidity at the beginning of each production day and the observed glass transition temperature of the fully cured laminate is formulated and validated. The empirical equation describes a linear decrease of achievable glass transition temperature with increasing absolute air humidity. The quantitative nature of the results encourages straightforward practical application to determine the maximum achievable Tg for given production conditions.

Battery power is crucial for wearable devices as it ensures continuous operation, which is critical for real-time health monitoring and emergency alerts. One solution for long-lasting monitoring is energy harvesting systems. Ensuring a consistent energy supply from variable sources for reliable device performance is a major challenge. Additionally, integrating energy harvesting components without compromising the wearability, comfort, and esthetic design of healthcare devices presents a significant bottleneck. Here, we show that with a meticulous design using small and highly efficient photovoltaic (PV) panels, compact thermoelectric (TEG) modules, and two ultra-low-power BQ25504 DC-DC boost converters, the battery life can increase from 9.31 h to over 18 h. The parallel connection of boost converters at two points of the output allows both energy sources to individually achieve maximum power point tracking (MPPT) during battery charging. We found that under specific conditions such as facing the sun for more than two hours, the device became self-powered. Our results demonstrate the long-term and stable performance of the sensor node with an efficiency of 96%. Given the high-power density of solar cells outdoors, a combination of PV and TEG energy can harvest energy quickly and sufficiently from sunlight and body heat. The small form factor of the harvesting system and the environmental conditions of particular occupations such as the oil and gas industry make it suitable for health monitoring wearables worn on the head, face, or wrist region, targeting outdoor workers.

Die vorliegende Masterarbeit analysiert und vergleicht die Resilienzstrategien Deutschlands und der Schweiz in Bezug auf ihre Bahninfrastruktur. In beiden Ländern wurden Maßnahmen entwickelt, die dazu dienen, die Infrastrukturen widerstandsfähiger gegen Naturkatastrophen und andere Risiken zu machen. Die deutsche Strategie verfolgt einen breiteren Ansatz, der neben dem Infrastrukturschutz auch die allgemeine Katastrophenvorsorge und den Klimawandel berücksichtigt. Die Schweizer Strategie fokussiert sich stärker auf den Schutz kritischer Infrastrukturen sowie auf die Zusammenarbeit zwischen öffentlichen und privaten Akteuren. Die Kombination von Literaturrecherche und Experteninterviews verdeutlicht, dass beide Länder effektive Ansätze verfolgen, jedoch noch Verbesserungspotenzial in Bereichen wie der Integration neuer Technologien und der Sensibilisierung der Bevölkerung besteht. Die vorliegende Arbeit präsentiert wertvolle Erkenntnisse und Empfehlungen zur Verbesserung der Resilienz im Bahninfrastrukturbereich, die auch auf andere Länder und Infrastrukturen übertragbar sind.

Artificial Intelligence (AI) combined with cyber-physical systems (CPS) can play a vital role in eliminating greenhouse gas emissions across sectors. The transition from fossil fuels to renewables is achieved through electrification, introducing complexity in systems deployment, integration, and efficient orchestration of electrified economic systems. AI-driven CPS are uniquely suited to manage this complexity, potentially accelerating decarbonisation efforts. This Policy Brief advocates for the mainstreaming of AI-driven CPS for climate change risk mitigation. To effectively realise the Intelligent Decarbonation (IDC) potential, AI-driven CPS must be elevated to a global level of collaboration and coordination, fostering clear IDC principles and guidelines, capacity building and technology transfer. The importance of IDC governance is emphasised to avoid unwanted path dependency and to avert a technology-centric approach, which has proven to yield limited results. A shift from trustworthy to sustainable AI is necessary to eliminate AI’s own carbon footprint.