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    EXC 3120 BlueMat - Research Topic B2: Selective Electrosorption
    Reversible electrochemical processes offer promising options in water treatment for removing oxyanions, dissolved organic carbon, and partial desalination by ion adsorption. Sorbent effectiveness depends on pore size, volume, surface area, and charge. However, current electrode fabrication processes limit control over multiscale porosity and surface charge, reducing their effectiveness in selective ion removal. Additionally, these properties are static, limiting adaptivity to avoid clogging and the ability to switch between adsorption and desorption. This RT advances the field by tailoring multiscale porosity of material systems for utilization as selective ion adsorbents and membrane filters. Innovative control of adsorption and desorption via adjustable surface potentials and selective ion sorption will transform materials into reversible, selective electrosorption systems. This facilitates strategic ion removal with low energy consumption, like lithium from seawater, marking a significant leap in harvesting engineering-valuable elements. The key scientific questions are: How can we functionalize 3D structured materials with locally and reversibly tunable adsorption and desorption of water-dissolved ions? How can we study the ion structure (+ hydration shell) and the spatiotemporal ion concentration evolution under electric potential and external flow, as well as the coupling of both, in a multiscale porous medium? How can we use multiscale modeling for functional optimization of materials for fast ion adsorption and desorption and low electrode degeneration rates resulting either in selective removal (water treatment) or selective ion (element) harvesting?
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    EXC 3120 BlueMat - Research Topic C4: Scattering of Visible Light by Control of Water Distribution
    Porous media with periodic or random structures comparable to the wavelength of light can provide spectrally selective scattering. Here, the optical response or color is no longer dictated by the base materials but by the pore shape, orientation, and arrangement, as well as by pore filling. Embedding water into the pore space and controlling its distribution at the nm- and ?m-scale allows for modifying the scattering, thus opening new possibilities to dynamically adjust or switch optical appearance. Previously, water has only been used to slightly shift the spectral response of periodic media upon water infiltration. However, here, we plan to go beyond this state of the art, achieving broadband control of the spectral response and even switching the color on and off. In this respect, we aim to achieve a similar functionality as in the skin of chameleons or cephalopods, but using water in porous media. The key scientific questions are: How can we design and fabricate structures with self-organized multiscale porosity to have defined optical appearance? How can we control water distribution in multiscale porous framework structures to switch this optical appearance? How can we utilize these effects for switchable structural color and opacity, including adaptive functionality?
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    EXC 3120 BlueMat - Cross Area Modeling
    The characteristic behavior of water-driven materials results to a large extent from complex and as yet often poorly understood interactions across different scales. To unravel the fundamental physics and chemistry of water-driven materials, (1) we will develop novel multiscale modeling methods bridging from the quantum to the device level; (2) machine learning (ML) will help to bridge between the scales and leverage the unique imaging data collected in the CA Imaging. Including physical knowledge into ML architectures will help accelerate the design of water-driven materials by identifying, for example, process-structure-property relationships in a fast and automated manner (physics-informed ML). To achieve these ambitious goals, we will rely on extensive (3) research software engineering, providing a whole ecosystem of cutting-edge open-source research software. Overall, we will create a unique multiscale and multi-purpose open-source software ecosystem for computer simulation and ML to understand, predict and optimize Blue Materials from the quantum level to the device level, laying the foundations to leverage cutting-edge imaging and AI to go from “nature-inspired materials” to materials and functionalities “beyond nature”
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