This paper presents a new additive manufacturing (AM) process to directly and continuously print piezoelectric devices from polyvinylidene fluoride (PVDF) polymeric filament rods under a strong electric field. This process, called ‘electric poling-assisted additive manufacturing or EPAM, combines AM and electric poling processes and is able to fabricate free-form shape piezoelectric devices continuously. In this process, the PVDF polymer dipoles remain well-aligned and uniform over a large area in a single design, production and fabrication step. During EPAM process, molten PVDF polymer is simultaneously mechanically stresses in-situ by the leading nozzle and electrically poled by applying high electric field under high temperature. The EPAM system was constructed to directly print piezoelectric structures from PVDF polymeric filament while applying high electric field between nozzle tip and printing bed in AM machine. Piezoelectric devices were successfully fabricated using the EPAM process. The crystalline phase transitions that occurred from the process were identified by using the Fourier transform infrared spectroscope. The results indicate that devices printed under a strong electric field become piezoelectric during the EPAM process and that stronger electric fields result in greater piezoelectricity as marked by the electrical response and the formation of sharper peaks at the polar β crystalline wavenumber of the PVDF polymer. Performing this process in the absence of an electric field does not result in dipole alignment of PVDF polymer. The EPAM process is expected to lead to the widespread use of AM to fabricate a variety of piezoelectric PVDF polymer-based devices for sensing, actuation and energy harvesting applications with simple, low cost, single processing and fabrication step.

Abstract.A lab scale infiltration experiment was conducted in a sand tank to evaluate the use of time-lapse multi-offset ground-penetrating radar (GPR) data for monitoring dynamic hydrologic events in the vadose zone. Sets of 21 GPR traces at offsets between 0.44-0.9 m were recorded every 30 s during a 3 h infiltration experiment to produce a data cube that can be viewed as multi-offset gathers at unique times or common offset images, tracking changes in arrivals through time. Specifically, we investigated whether this data can be used to estimate changes in average soil water content during wetting and drying and to track the migration of the wetting front during an infiltration event. For the first problem we found that normal-moveout (NMO) analysis of the GPR reflection from the bottom of the sand layer provided water content estimates ranging between 0.10-0.30 volumetric water content, which underestimated the value determined by depth averaging a vertical array of six moisture probes by 0.03-0.05 volumetric water content. Relative errors in the estimated depth to the bottom of the 0.6 m thick sand layer were typically on the order of 2 %, though increased as high as 25 % as the wetting front approached the bottom of the tank. NMO analysis of the wetting front reflection during the infiltration event generally underestimated the depth of the front with discrepancies between GPR and moisture probe estimates approaching 0.15 m. The analysis also resulted in underestimates of water content in the wetted zone on the order of 0.06 volumetric water content and a wetting front velocity equal to about half the rate inferred from the probe measurements. In a parallel modeling effort we found that HYDRUS-1D also underestimates the observed average tank water content determined from the probes by approximately 0.01-0.03 volumetric water content, despite the fact that the model was calibrated to the probe data. This error suggests that the assumed conceptual model of laterally uniform, onedimensional vertical flow in a homogenous material may not be fully appropriate for the experiment. Full-waveform modeling and subsequent NMO analysis of the simulated GPR response resulted in water content errors on the order of 0.01-0.03 volumetric water content, which are roughly 30-50 % of the discrepancy between GPR and probe results observed in the experiment. The model shows that interference between wave arrivals affects data interpretation and the estimation of traveltimes. This is an important source of error in the NMO analysis, but it does not fully account for the discrepancies between GPR and the moisture probes observed in the experiment. The remaining discrepancy may be related to conceptual errors underlying the GPR analysis, such as the assumption of uniform one-dimensional flow, a lack of a sharply defined wetting front in the experiment, and errors in the petrophysical model used to convert dielectric constant to water content.

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