Lithium ion batteries play an increasing role in everyday life, giving power to handheld devices or being used in stationary storage solutions. Especially for medium or large scale solutions, the latter application confines a huge amount of energy within a small volume; however, increasing the hazard potential far above the common level. Furthermore, as the safety hazards of lithium ion cells have been known for years, impressively shown by several burning cars or laptops, the need for a further enhancement of the safety of these systems is rising. This manuscript presents measurements of the gas emission from lithium ion batteries in case of a malfunction for different scenarios, showing a large variety of species with mostly toxic to highly toxic properties. The measurements were carried out using a combination of gas chromatography-mass spectrometry (GC-MS), quadrupole mass spectrometry (QMS), photoacoustic spectroscopy, and chemical analysis. It is shown that the inflammation of a cell can be overcome, also preventing a cascading effect to neighboring cells, but giving rise to worse toxic gas emission. Furthermore, a filtration concept is presented that decreases the concentration of the emitted components significantly and promises filtration below immediately dangerous to life or health (IDLH) equivalent levels.

In this scientific publication, a new sensor approach for status monitoring, such as state of charge and state of health, of lithium ion batteries by using special Bragg gratings inscribed into standard optical glass fibers is presented. In addition to well-known core gratings, embedded into the anode of 5 Ah lithium ion pouch cells as a strain monitoring unit, the manufacturing of a surface cladding waveguide Bragg grating sensor incorporated into the cell’s separator, that is sensitive to changes of the refractive index of the surrounding medium, is demonstrated. On the basis of the experiments carried out, characteristics of the cell behavior during standard cyclization and recognizable marks in subsequent post-mortem analyses of the cell components are shown. No negative influence on the cell performance due to the integrated sensors have been observed; however, the results show a clear correlation between fading cell capacity and changes of the interior optical signals. Additionally, with the novel photonic sensor, variations in the electrolyte characteristics are determinable as the refractive index of the solution changes at different molar compositions. Furthermore, with the manufactured battery cells, abuse tests by overcharging were conducted, and it was thereby demonstrated how internal battery sensors can derive additional information beyond conventional battery management systems to feasibly prevent catastrophic cell failures. The result of the research work is an early stage photonic sensor that combines chemical, mechanical and thermal information from inside the cell for an enhanced battery status analysis.

In this work, an evanescent Bragg grating sensor inscribed in a few-mode planar polymer waveguide was integrated into microchannel structures and characterized by various chemical applications. The planar waveguide and the microchannels consisted of epoxide-based polymers. The Bragg grating structure was postprocessed by using point-by-point direct inscription technology. By monitoring the central wavelength shift of the reflected Bragg signal, the sensor showed a temperature sensitivity of −47.75 pm/K. Moreover, the functionality of the evanescent field-based measurements is demonstrated with two application examples: the refractive index sensing of different aqueous solutions and gas-phase hydrogen concentration detection. For the latter application, the sensor was additionally coated with a functional layer based on palladium nanoparticles. During the refractive index sensing measurement, the sensor achieved a sensitivity of 6.5 nm/RIU from air to 99.9% pure isopropyl alcohol. For the gas-phase hydrogen detection, the coated sensor achieved a reproducible concentration detection up to 4 vol% hydrogen. According to the reported experimental results, the integrated Bragg-grating-based waveguide sensor demonstrates high potential for applications based on the lab-on-a-chip concept.

Water is an essential resource required for various human activities such as drinking, cooking, growing food, and personal hygiene. As a key infrastructure of public services, access to clean and safe drinking water is an essential factor for local socio-economic development. Despite various national and international efforts, water supply is often not guaranteed, especially in rural areas of Africa. Although many water resources are theoretically available in these areas, bodies of water are often contaminated with dangerous pathogens and pollutants. As a result, people, often women and children, have to travel long distances to collect water from taps and are exposed to dangers such as physical violence and accidents on their way. In this article, we present a socio-economic case study for rural development. We describe a drinking water treatment plant with an annual capacity of 10,950 m³ on Kibumba Island in Lake Victoria (Tanzania). The plant is operated by a photovoltaic mini-grid system with second-life lithium-ion battery storage. We describe the planning, the installation, and the start of operation of the water treatment system. In addition, we estimate the water prices achievable with the proposed system and compare it to existing sources of drinking water on Kibumba Island. Assuming a useful life of 15 years, the installed drinking water system is cost-neutral for the community at a cost price of 0.70 EUR/m³, 22% less than any other source of clean water on Kibumba Island. Access to safe and clean drinking water is a major step forward for the local population. We investigate the socio-economic added value using social and economic key indicators like health, education, and income. Hence, this approach may serve as a role model for community-owned drinking water systems in sub-Saharan Africa.

An ultra-short fiber Bragg grating with a grating length of 0.2 mm and constant grating period (uniform FBG) is proposed as an integrated dispersive element for spectral analysis in a single-mode glass fiber. This dispersive element is used to set up a fiber optical spectrometer that demonstrated an average spectral resolving power of 825, a pixel resolution of 0.02 nm/pixel, and a 40 nm bandwidth covering the 810-850 nm wavelength range. Furthermore, the dependence of this dispersive element on light polarization was examined, which induces a reduction in the wavelength accuracy up to ±0.05 nm. Finally, the investigated spectrometer to function well as a part of a readout device for fiber Bragg grating sensors is presented. Short uniform Bragg gratings as dispersive elements allow the manufacturing of miniaturized, compact spectrometers without additional focusing components between the FBG and detector.

Shape-sensing optical fibers have become increasingly important in applications requiring flexible navigation, spatial awareness, and deformation monitoring. Fiber Bragg Grating (FBG) sensors inscribed in multi-core optical fibers have been democratized over the years and nowadays offer a compact and robust platform for shape reconstruction. In this work, we propose a novel, computationally efficient method for determining the 3D tip position of a bent multi-core FBG-based optical fiber using a second-order polynomial approximation of the fiber’s shape. The method begins with a calibration procedure, where polynomial coefficients are fitted for known bend configurations and subsequently modeled as a function of curvature using exponential decay functions. This allows for real-time estimation of the fiber tip position from curvature measurements alone, with no need for iterative numerical solutions or high processing power. The method was validated using miniaturized test structures and achieved sub-millimeter accuracy (<0.1 mm) over a 4.5 mm displacement range. Its simplicity and accuracy make it suitable for embedded or edge-computing applications in confined navigation, structural inspection, and medical robotics.