PFI-TT: Commercial scale production of aligned polymer nanofiber materials and yarns

Rowan University, Glassboro NJ

Investigators

Abstract

The broader impact/commercial potential of this Partnerships for Innovation - Technology Translation (PFI-TT) project includes research and commercialization of a technology that will facilitate roll-to-roll production of aligned polymer nanofiber materials and strong nanofiber yarns up to hundreds of meters long. Aligned nanofiber materials are desirable for a wide spectrum of applications due to their ability to provide directional control over electrical and thermal conductivity and creation of precisely-patterned surfaces for targeted optical and surface properties. These materials can serve as essential building blocks for high-strength nanofiber composites and textiles. Despite the remarkable promise of aligned nanofibers, there is an absence of commercial-scale roll-to-roll aligned polymer nanofiber manufacturing due to diverse technical hurdles. This project connects an academic research team and an established nanofiber manufacturing company to translate technologies that will overcome these hurdles. Beyond its commercial impacts, this project will lead to the development of a new hands-on educational program and provide students with valuable experience and training opportunities in entrepreneurship, technology translation, and innovation. The proposed project aims to enhance the efficiency, throughput, and consistency of parallel track roll-to-roll electrospinning for aligned nanofiber manufacturing. It is hypothesized that computational electrical field models can predict production efficiency. Computational electrical field models will be generated based on manufacturing process parameters. The production efficiency will be measured as the mass of aligned nanofiber output on a roll, divided by the mass of polymer feed into the system. A convolutional neural network (CNN) machine learning model will also be utilized to correlate electrical field model images with experimentally measured production efficiency. Computational electrical field models can be generated for hundreds of different parameter combinations at the same time instead of testing only a few parameter combinations experimentally. Therefore, this approach allows for efficient in silico screening of the extensive parameter space associated with this complex manufacturing process to maximize the device efficiency. Optimized devices will be scaled, prototyped, and evaluated, demonstrating the capability of parallel track roll-to-roll aligned nanofiber electrospinning manufacture in a commercial context. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.