Flexible Graphene/Carbon Nanotube Electrochemical Double-Layer Capacitors with Ultrahigh Areal Performance
Authors: Valentino Romano, Beatriz Martin-Garcia, Sebastiano Bellani, Luigi Marasco, Jaya Kumar Panda, Reinier Oropesa-Nunez, Leyla Najafi, Antonio Esau Del Rio Castillo, Mirko Prato, Elisa Mantero, Vittorio Pellegrini, Giovanna D Angelo, Francesco Bonaccorso
Abstract: The fabrication of electrochemical double-layer capacitors (EDLCs) with high areal capacitance relies on the use of elevated mass loadings of highly porous active materials. Herein, we demonstrate a high-throughput manufacturing of graphene/nanotubes hybrid EDLCs. Wet-jet milling (WJM) method is exploited to exfoliate the graphite into single/few-layer graphene flakes (WJM-G) in industrial volume (production rate ~0.5 kg/day). Commercial single/double walled carbon nanotubes (SDWCNTs) are mixed with graphene flakes in order to act as spacers between the graphene flakes during their film formation. The latter is obtained by one-step vacuum filtration, resulting in self-standing, metal- and binder-free flexible EDLC electrodes with high active material mass loadings up to 30 mg cm-2. The corresponding symmetric WJM-G/SDWCNTs EDLCs exhibit electrode energy densities of 539 uWh cm-2 at 1.3 mW cm-2 and operating power densities up to 532 mW cm-2 (outperforming most of the EDLC technologies). The EDCLs show excellent cycling stability and outstanding flexibility even under highly folded states (up to 180 degrees). The combination of industrial-like production of active materials, simplified manufacturing of EDLC electrodes, and ultrahigh areal performance of the as-produced EDLCs are promising for novel advanced EDLC designs.
Explore the paper tree
Click on the tree nodes to be redirected to a given paper and access their summaries and virtual assistant
Look for similar papers (in beta version)
By clicking on the button above, our algorithm will scan all papers in our database to find the closest based on the contents of the full papers and not just on metadata. Please note that it only works for papers that we have generated summaries for and you can rerun it from time to time to get a more accurate result while our database grows.