Biomimetic Carbon-Fiber Systems Engineering: A Modular Design Strategy to Generate Biofunctional Composites from Graphene and Carbon Nanofibers
Kumar Mishra, Yogendra
ACS Applied Materials & Interfaces
American Chemical Society (ACS)
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Taale, M., Schütt, F., Carey, T., Marx, J., Kumar Mishra, Y., Stock, N., Fiedler, B., et al. (2019). Biomimetic Carbon-Fiber Systems Engineering: A Modular Design Strategy to Generate Biofunctional Composites from Graphene and Carbon Nanofibers. ACS Applied Materials & Interfaces https://doi.org/10.1021/acsami.8b17627
electrical conductivity. It is additionally advantageous if such materials resembled the structural and biochemical features of the natural extracellular environment. Here we show a novel modular design strategy to engineer biomimetic carbon-fiber based scaffolds. Highly porous ceramic zinc oxide (ZnO) microstructures serve as 3D sacrificial templates and are infiltrated with carbon nanotube (CNT) or graphene dispersions. Once the CNTs and graphene uniformly coat the ZnO template, the ZnO is either removed by hydrolysis or converted into carbon by chemical vapor deposition (CVD). The resulting 3D carbon scaffolds are both hierarchically ordered and free-standing. The properties of the micro-fibrous scaffolds were tailored with a high porosity (up to 93 %), high Young’s modulus (~0.027 to ~22 MPa), and an electrical conductivity of (~0.1 to ~330 S/m), as well as different surface compositions. Cell viability and fibroblast proliferation rate and protein adsorption rate assays have shown that the generated scaffolds are biocompatible and have a high protein adsorption capacity (up to 77.32 ±6.95 mg/cm3), so that they not only are able to resemble the ECM structurally, but also biochemically. The scaffolds also allow for the successful growth and adhesion of fibroblast cells showing that we provide a novel, highly scalable modular design strategy to generate biocompatible carbon-fiber systems that mimic the extracellular matrix with the additional feature of conductivity.
RA gratefully acknowledges partial project funding by the Deutsche Forschungsgemeinschaft under contract FOR1616. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. GrapheneCore2 785219. CS is supported by the European Research Council (ERC StG 336104 CELLINSPIRED, ERC PoC 768740 CHANNELMAT), by the German Research Foundation (RTG 2154, SFB 1261 project B7). MT acknowledges support from the German Academic Exchange Service (DAAD) through a research grant for doctoral candidates (91526555-57048249). We acknowledge funding from EPSRC grants EP/P02534X/1, ERC grant 319277 (Hetero2D) the Royal Academy of Engineering Enterprise Scheme, the Trinity College, Cambridge, and the Isaac Newton Trust.
EC FP7 ERC (319277)
European Commission Horizon 2020 (H2020) Future and Emerging Technologies (FET) (785219)
External DOI: https://doi.org/10.1021/acsami.8b17627
This record's URL: https://www.repository.cam.ac.uk/handle/1810/287702