Genetically identical cells observed as a population can be significantly heterogeneous when studied individually, and this heterogeneity can change the behavior of entire cell populations. In particular, some trace elements play important roles in cell processes. Classical analytical methods to measure (trace) elemental composition in cells (naturally present or taken up by them, e.g. nanoparticles) provide information only about the average of the cell population thus disregarding important cell-to-cell variances. In this context, single-cell inductively coupled plasma-mass spectrometry has been gaining special attention to evaluate elements and nanoparticles as well as multiparameters in single cells. However, our currently available information and quantitative data on multielemental composition and uptake of toxic elemental species and metal oxide nanoparticles in single cells are still scarce. NanoMuSiC project will develop new sensitive and accurate analytical methods based on the coupling between a microdroplet generator to the state-of-the-art inductively coupled plasma-time of flight-mass spectrometry for multielement quantification and for evaluating the uptake of elemental species and metal-based nanoparticles in single cells. These methods will be applied to proof-of-concept ecotoxicological applications employing diatoms (single cells) and environmentally relevant elemental species and nanoparticles. Through these developed methodologies and results, the NanoMuSiC project will provide new insights on cellular elemental composition and elemental species-cell and nanoparticle-cell interactions. Besides, they will support further investigations of effects and potential risks of elemental species and nanoparticles to the environment and human health, two relevant issues within EU Commission priorities for 2019-24, e.g. European Green Deal strategy to protect the environment and human health by cutting pollution.

WHO estimates that 2 billion people worldwide consume drinking water that has been contaminated with faeces, yet scientific testing for faecal contamination in water currently takes at least 10 to 24 h, as per UNICEF reports. Thus, there is an urgent need for methods that allow to unequivocally test drinking water quality on site, therefore significantly contributing to the United Nations’ Sustainable Development Goals, in particular to SDG 6 (access to clean water and sanitation). However, currently, no rapid, portable, sensitive and cost-effective method or device for the detection of faecal pigments outside of a lab is available. The proposed sustainable method to be developed in RIFF represents a shift from a faecal indicator bacteria (FIB) to a faecal indicator pigment (FIP) paradigm in faecal contaminant detection technology. This interdisciplinary project will demonstrate (1) a rapid and cost-effective sensory device for the real-time analysis of FIPs having as (2) a key element, a specifically tailored hybrid filter membrane for selective and sensitive FIP enrichment and detection (10 pg/L to 1 µg/L). Besides membrane tailoring for selective FIP capture, interfacial chemistry and assay integration will enhance the detection performance of a final device. The proposed method eliminates the need for solution-based FIP analysis, thus mitigating the technical issues associated with real-time water quality testing as well as bringing user-friendliness and operational stability. Hence RIFF will have a significant societal impact towards providing novel solutions for health challenges associated with drinking water contamination. The successful completion of the project will give me the opportunity to acquire multidisplinary skills in the field of sensor material development, device construction and rapid testing, which is necessary for establishing my future research career as an independent researcher in the field of water research & water quality monitoring.

Hydrogen is seen as secure, clean and inexpensive energy of the future. To this aim, the European union has laid out strategies for large-scale production and deployment of hydrogen in the future. This translates to the most economical way of transmission of hydrogen through existing natural gas pipelines. However, one of the serious issues that can present a setback to this ambitious project is the failure of pipelines due to defects. One such less-addressed/hard-to-detect failure mechanism called Hydrogen Induced Cracks (HICs) is considered for the proposed work. In order to detect HICs in hydrogen-loaded gas transmission pipelines, an ultrasonic guided wave (UGW) based NDT technique will be developed. Towards this, a torsional guided wave mode will be optimized for its frequency from the perspective of defects (HICs) in pipe segments using the Scaled Boundary Finite Element Method (SBFEM) simulation tool available at BAM. An array of shear mode piezo-crystals for the optimized frequency will be used in the generation of the torsional mode. Towards UGW based testing, pipe segments with actual HICs will be prepared at hydrogen test rig at BAM under the guidance of BAM’s material scientists. Additionally, pipe segments with artificial notches simulating HICs will also be prepared. Further, Laser-based measurements will be carried out to map the wave fields around the crack to understand the physics of wave-defect interaction. Further, the effect of operational conditions of a pipeline such as pressure and temperature on torsional mode will be studied using both experiments and simulation. Overall, the project will involve both simulation and experiments to gain deeper understanding of the problem. Emphasis is also given on the validation of simulation results for the smooth progress of the project. Furthermore, ultrasonic phased array testing will also be carried out to successfully validate the UGW measurements pertaining to defects and to localize and size them.

What are the structural characteristics of ultrastable metallic glasses? The recently discovered ultrastable state of metallic glasses (MGs) exhibits a variety of thermodynamic stability levels in combination with an enhanced kinetic stability. As a hypothesis, observed levels of excess enthalpy originate from faster relaxation contributions that are locally embedded in an otherwise stable structure. Such features remind strongly of novel MG-states of structurally heterogeneous glasses that were recently reported by experiments on conventional MGs and molecular dynamics simulations. The aim of the PathAge project is to test the hypothesis in terms of the ultrastable MGs relation to these novel structural states. This builds on quantifying the evolution of the ultrastable state in response to thermal stimulus by tracing the structural transformation towards the supercooled liquid or eventual crystallization. Three possible mechanistic routes will be considered: First, a front-initiated process as observed for ultrastable molecular glasses. Second, a homogeneous structural evolution triggered by fast relaxation contributions. Third, a transformation involving an underlying phase transition of a heterogeneous glass state. In order to distinguish between the proposed transformation scenarios, the following novel experimental approaches will be used in addition to traditional methods: The so-called single-parameter-ageing formalism known from the field of molecular glasses, which will allow for predicting and testing the homogeneous ageing scenario. Surface sensitive methods that probe nanoscale heterogeneities revealing the formation of structurally heterogeneous glassy states. Spatially resolved electron diffraction combined with atomistic simulations to identify preferred local structural motifs. In concert, these approaches will significantly enhance the understanding of the unique ultrastable MG-state, thereby unlocking potential for novel applications of MGs.

A major challenge for the green transition is our inability to rationally design inorganic materials with tailor-made properties. This project will tackle this inability by transforming our understanding of chemical bonding in inorganic materials. Understandable rules based on chemical bonds have greatly advanced chemistry but are missing for most material properties, severely limiting the rational design of materials. Until recently, quantum chemical bonding analysis of inorganic materials has only been carried out on a small scale, making it impossible to derive such rules using machine learning. In addition, quantum chemical bonding analysis primarily focuses on two-center bonds. However, multicenter bonds play a critical role in material properties: For example, multicenter bonds have been held responsible for the superhardness of boron-containing compounds and the unusual properties of phase-change materials. By significantly going beyond my recent results on two-center bonds predicting materials properties with simple machine-learning models, I propose to overcome these challenges. The overarching objective of MultiBonds is to derive understandable and universal rules based on chemical bonds for inorganic materials properties through large-scale quantum-chemical bonding analysis considering multicenter bonds. We will 1) develop and apply innovative automated quantum-chemical methods to compute, for the first time, multicenter bonding indicators on a large scale. The generated database will then be used for 2) developing novel predictive deep-learning models and 3) intuitive human-understandable rules for materials properties. As initial applications, we will focus on phase-change materials with low thermal conductivities, magnetic and hard materials, since their properties are known to be governed by multicenter bonds, and they have critical applications (e.g., as thermoelectrics and in the green transition of vehicles).