Integrated Fabrication of Novel Inkjet-Printed Silver Nanoparticle Sensors on Carbon Fiber Reinforced Nylon Composites

Inkjet-printing technology enables the contactless deposition of functional materials such as conductive inks on surfaces, hence reducing contamination and the risk of substrate damage. In printed electronics, inkjet technology offers the significant advantage of controlling the volume of material deposited, and therefore the fine-tuning of the printed geometry, which is crucial for the performance of the final printed electronics. Inkjet printing of functional inks can be used to produce sensors to detect failure of mechanical structures such as carbon fiber reinforced composite (CFRC) components, instead of using attached sensors, which are subject to delamination. Here, silver nanoparticle-based strain sensors were embedded directly in an insulated carbon-fiber laminate by using inkjet printing to achieve an optimized conductive and adhesive geometry, forming a piezoresistive strain sensor. Following the inkjet-printing optimization process, the sensor conductivity and adhesion performance were evaluated. Finally, the sensor was quantified by using a bending rig which applied a pre-determined strain, with the response indicating an accurate sensitivity as the resistance increased with an increased strain. The ability to embed the sensor directly on the CFRC prevents the use of interfacial adhesives which is the main source of failure due to delamination.

Detecting Changes in Fiber Orientation in a Simulated Chopped Fiber Plate Using Curvature Mode Shapes

The use of chopped fibers in the manufacturing of carbon fiber composite parts is becoming more popular in order to reduce production costs, especially in the automotive, wind, and gas storage industries. The orientation of the fibers in a chopped fiber part is important because the material properties of the part depend upon it. Phenomena such as shear alignment can result in undesired material properties, and therefore, a method for detecting the presence of undesired fiber orientations is needed. In this paper, a metric based on a part's curvature mode shapes is developed to identify the presence and location of fibers whose orientation is different from that of a desired alignment. A proof-of-concept experimental analysis shows the effectiveness of the metric at locating a region in a carbon fiber laminate plate that has been modified by rotating the fibers 90 deg. A finite element model is also developed to validate the experimental results and explore other modification scenarios. In each case, the metric is effective in identifying areas in which fiber alignment changed relative to a baseline model. In one case, a change as small as 3 deg was identified.