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In fibre-reinforced composites (FRCs), which occur in nature, reinforcing fibres such as collagen or cellulose fibrils are embedded in a shaping matrix of lignin, hemicellulose or collagen. The fibre strands run in a load-bearing manner. The composite fabrics are mainly produced using solution-based physicochemical processes that take place at ambient temperature. Similar to nature, new 3D printing processes with continuous fibre reinforcement also make it possible to place the fibre strands in the right place (topology optimisation) and in the right direction to suit the load. However, natural fibres such as cellulose fibres are sensitive to higher temperatures. They therefore cannot be processed in the classic thermoplastic 3D printing process.
The result of the research work is 3D-printed fibre composite components consisting of continuous cellulose fibres embedded in a cellulose-based matrix. A manufacturing process was developed that enables 3D printing at ambient temperature. This means that, as in nature, the material and component can be produced simultaneously in a single operation at ambient temperature.The cellulose fibre strand is first stabilised with a binder for processing in the printer. The specially designed print head converts the binder into a matrix with which the continuous cellulose fibres are coated. As the cellulose fibres and the matrix have a similar chemical structure, the component is very stable. The mechanical properties, such as breaking strength, are extremely good.
The solution-based and energy-efficient manufacturing method developed by the research team can also be used in other composite manufacturing processes. It is particularly suitable for processing temperature-sensitive materials such as natural or cellulose fibres, which are in high demand.
The research project „CellLoes 3D printing“ is funded by the Federal Ministry of Education and Research as part of the ideas competition „Biologisation of technology“.
The above texts, or parts thereof, were automatically translated from the original language text using a translation system (DeepL API).
Despite careful machine processing, translation errors cannot be ruled out.