Benefits of employing graphene nanopletlates (GNPLs) in composite structures include mechanical as well as multifunctional properties. Understanding the impedance behavior of GNPLs reinforced syntactic foams may open new applications for syntactic foam composites. In this work, GNPLs reinforced syntactic foams were fabricated and tested for DC and AC electrical properties. Four sets of syntactic foam samples containing 0, 0.1, 0.3, and 0.5 vol% of GNPLs were fabricated and tested. Significant increase in conductivity of syntactic foams due to the addition of GNPLs was noted. AC impedance measurements indicated that the GNPLs syntactic foams become frequency dependent as the volume fraction of GNPLs increases. With addition of GNPLs, the characteristic of the syntactic foams are also observed to transition from dominant capacitive to dominant resistive behavior.
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Additive manufacturing of complex micro-architected graphene aerogels
Graphene is one of the stiffest materials ever measured, and yet foams of this material experience such massive degradation in mechanical properties at low densities that they are worse than polymer foams. (Z. Qin, G. S. Jung, M. J. Kang and M. J. Buehler, Sci. Adv., 2017, 3, e1601536). 3D printed mechanical metamaterials have shown the unprecedented ability to alleviate such degradation, but all current 3D printing techniques capable of printing graphene foam are unable to reproduce the complex metamaterial architectures (e.g. insufficient resolution, toolpath limitations, etc.). Here we demonstrate high-resolution graphene foams incorporating hierarchical architecture which reduces mechanical degradation of graphene foams with decreasing density. Our technique achieves an order-of-magnitude finer resolution and far more intricate structures than any previous method. This technique opens new possibilities not only to enhance graphene foam mechanical properties, but to explore complex architectures and mesoscale effects for other graphene applications including energy storage and conversion, separations, and catalysis.
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- Award ID(s):
- 1727492
- PAR ID:
- 10066575
- Date Published:
- Journal Name:
- Materials horizons
- ISSN:
- 2051-6355
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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