Molecular-Layer-Engineered Inorganic-Organic Hybrid Materials
Date du début: 1 févr. 2014,
Date de fin: 31 janv. 2019
"On-demand-designed and precision-synthesized multicomponent or hybrid materials with unorthodox combinations of properties are potential keys to fascinating next-generation devices. At the same time there is a strong scientific desire to create a comprehensive repertory of basic understanding, design strategies and experimental tools to construct such outstanding smart materials from different building blocks and to shape them into sophisticated hierarchical architectures.In LAYERENG-HYBMAT I propose a fundamentally new category of nanocomposite materials, that is, layer-by-layer grown coherent inorganic-organic hybrid materials where the cohesion between the layers is based on covalent bonding. Such materials are – once carefully designed and fabricated – able to display in a single material a tailored combination of properties of conventional inorganics and organics, and even beyond. The core hypothesis is that such intimately fused outstanding hybrids are materialized in a simple but extremely elegant manner by mimicking the state-of-the-art thin-film technology, i.e. ALD (atomic layer deposition), originally developed for purely inorganic thin films. The proposed method combines ALD and MLD (molecular layer deposition) cycles and enables the layer-by-layer deposition of coherent inorganic-organic thin films and coatings through sequential self-limiting gas-surface reactions with high precision for the composition and polymer-chain dispersity. With additional nanostructuring capacity these materials have the potential to open up new horizons in electronics, photonics, thermoelectrics, diagnostics, packaging, etc.The project builds on my long experience in frontier new-material research on other types of multilayered materials and successful proof-of-the-concept ALD/MLD experiments, and addresses all the fundamental aspects of new-material design, modelling, precision synthesis, property tailoring and function characterization."
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