Field-assisted 3D printing of multi-functional materials
March 8 – 12, 2020
The emergence of flexible, robust additive manufacturing platforms has created potentially transformative opportunities to integrate multiple functionalities: in particular, mechanical efficiency with mass transport, thermal management and conductivity. Field-assisted assembly of multi-phase materials holds promise for numerous applications, including flexible composites, patterning of cells in extracellular matrix in synthetic tissue, controlling ion transport in batteries, etc. Experiments involving acoustic field-assisted assembly of microscale particles will be used to elucidate the role of acoustic fields on structure formation, and the resulting opportunities to tailor macroscopic conductivity in novel ways. Figure 1 below illustrates results for conductive carbon fibers an elastomer matrix, with patterned lines created via acoustic focusing. A key advantage of the approach is the ability to create strong connected networks of second phase particles at volume fractions that are well-below that associated with the percolation threshold, which greatly facilitates the development of printable functional inks. In-situ and ex-situ observations of direct write printing will then be used to identify regimes that enable ‘on-the-fly’ control of microstructure during macroscopic patterning. Figure 1: (a) Acoustically patterned composites of Ag-coated glass fiber 2.6v% in 1:1 M:CH-A polymer matrix, which undergo small, recoverable changes in conductivity when deformed. (b) Unpatterned, dispersed-fiber composites made of the same components, but higher filler particle loading in order approach the conductivity of the patterned composites. The higher loading required compromises their flexibility, so that large, unpredictable, and irreversible losses in conductivity occur at relatively low strains (a 90 degree twist and normal handling resulted in failure by fracture). In flexible conductive materials there is a well-documented trade-off between conductivity and flexibility as the conductive filler loading increases which currently limits the viability of printable flexible conductors [Sekitani 2010 3.1.2, Rodgers 2010, Ray 2019]. Here we present a method for subverting this trade-off by using acoustophoresis to assemble filler particles into highly efficient percolated networks within the composites, forming conductive networks at low particle loading which have high tolerance for strain and little change in conductivity. We demonstrate that the acoustic patterning process simultaneously decreases the fiber filler loading necessary for percolation by an order of magnitude and increases the conductivity of the material by an order of magnitude by forming many parallel percolated branches in the network. This low loading required for high conductivity allows the material to maintain <6% change in conductivity between the flat and bent (0.7 mm radius) states with no degradation over 500 cycles, due to the low particle loading and encapsulation of particle networks. Furthermore, using acoustic assembly during printing of these materials allows on-the-fly modulation between this conductive material and un-percolated insulating material during printing, with additional control over the anisotropy of the conductive network, all with the same nozzle and ink. This allows versatile design of integrated circuits in 3d printed soft components, as well as tuning of strain tolerance in multiple directions, without the cost and manufacturing limitations of lithography, or CNT growth steps, prestretch/burn-off steps, or liquid metal safety concerns. Acoustically patterned: >5000 S/m @ 2.6v% Unpatterned: <1500 S/m @ 13v% (a)
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Matthew Begley, "Field-assisted 3D printing of multi-functional materials" in "Innovative Materials For Additive Manufacturing (IMAM)", Daniel Schmidt, Luxembourg Institute of Science and Technology, Luxembourg Nikhil Gupta, New York University, USA Chua Chee Kai, NTU, Singapore Brett G. Compton, University of Tennessee, USA Eds, ECI Symposium Series, (2020). https://dc.engconfintl.org/imam/11