Amanda Mills

A rigorous and systematic series of experiments designed to research optimal fabric composition, define embedded electrode sizing, optimize electronic-to-sensor interface sites to further explore longevity, enhance robustness, and promote manufacturability from Phase 1 prototypes.

In our proposed project we develop a predictive modeling method that will allow determination of the upper and lower mechanical parameters of specialty yarns, especially those with conductive properties, to inform if and how (i.e., construction) they can be used in fabrics. Furthermore, we will review and adapt current testing and evaluation methodologies to assess the end-product performance and to measure critical fiber, yarn or fabric input parameters that will allow prediction of end product performance. The initial set of tasks presented here will act as a demonstrator project and will focus on knitted goods, especially those applicable to the US Army. We will develop an analytical model (mathematical model with a closed-form solution) of knit fabrics with smart yarns. The model will integrate fiber and yarn properties, knit constructions and the potential energy stored from the stretching and bending during the manufacturing process, allowing a direct and universal solution to yarn knittability in one operation of partial differential equations. The model will be validated via experiments and FEA model simulations. The model may then be used to predict the mechanical requirements of specialty yarns and allow the prediction of knitted fabric mechanical performance. Furthermore, the tactile comfort of smart knitted textiles will be evaluated by the model and experiment as a demonstration of the production feasibility and usability for military use.

Product design in textiles is fundamentally driven by the ability to understand how the materials and components selection dictates the final performance of that product. Through a product inspection, one can understand the relationship between textile construction and the resulting product behaviors or functions. Learning from a working, finished product is vastly different from the understanding one gains when building a new device and can reduce the time needed to complete the design cycle on a new product.

Product design in textiles is fundamentally driven by the ability to understand how the materials and components selection dictates the final performance of that product. Through a product inspection, one can understand the relationship between textile construction and the resulting product behaviors or functions. Learning from a working, finished product is vastly different from the understanding one gains when building a new device and can reduce the time needed to complete the design cycle on a new product.

The objective of this project is to explore layered conductive structures using ink jet printing and to investigate toward manufacturing of simple electronic components. The scope of the investigation would include: ��������������� The synthesis of fluid chemistries suitable for ink-jetting and their subsequent processing. ��������������� Lab scale validation of multi-layered ink-jet printed metal/dielectric structures on flexible substrates. ��������������� Detailed measurement of the multi-layered interface structure through processing (printing to annealing) the subsequent influence on capacitor device performance. ��������������� Techno-economic analysis of the ink-jet printing of capacitor designs that details the benefits and challenges relating device performance characteristics to scale-up processing (manufacturing speed, material usage, and device pattern design).

NC State will explore a number of prototype EMG electrodes using various conductive fabrics and materials according to specifications laid out by Porticos. After a down selection of the electrodes, 10 prototype headbands according to the pattern supplied by Porticos will be produced.