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Highly flexible nanocomposites have tremendous potential as smart, self-sensing materials because their conductivity is inherently linked to their mechanical state. Herein, carbon nanofiber (CNF)/polyurethane (PU)nanocomposites are studiedfor tactile imaging and distributed strain sensing via electrical impedance tomography (EIT) by investigatingthe influence of filler volume fraction on microscale morphology, piezoresistive response while bonded to mechanically loaded substrates, and sensitivity to distributed strain.Load testing of the bonded sensor reveals that viscoelasticity and filler volume fraction profoundly affect the piezoresistive response. EIT is able to accurately capture and discern between multiple points of contact in each volume fraction with lower volume fractions being more sensitivethereby demonstrating the potential of utilizing tomographic methods for tactile imaging and distributed strain sensing in PU-based nanocomposites.

We employ an analytical model of a harmonically excited bistable vibration energy harvester to determine criteria governing continuous high-energy orbit (HEO) dynamics that maximize harvesting performance. Derivation of the criteria stems from previously unexplored dynamic relationships predicted by the model indicating critical conditions for HEO; experimental evidence of the phenomenon is provided as validation. The criteria are vastly more concise than existing HEO prediction methodology and can more accurately delineate HEO boundaries. This research addresses an essential need to create effective tools for high performance and robust bistable harvester design.

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