FMRG: Cyber: Scalable Precision Manufacturing of Programmable Polymer Nanoparticles Using Low-temperature Initiated Chemical Vapor Deposition Guided by Artificial Intelligence

Polymer nanoparticles have a broad range of significant applications, including drug delivery, soft robotics and nanomedicine, etc. However, existing manufacturing of such materials are limited by batch production, quality variability and a narrow range of particle functionality, resulting in a slow development cycle, often decade long, for new materials, recipes, and use at scale.

To enable a future technology in manufacturing versatile polymer nanoparticles, it is necessary to radically change such a paradigm into one that enables data-driven decision-making for processing conditions. This unique future manufacturing research grant (FMRG) will advance fundamental research in the principles for continuous and highly reproducible manufacturing of polymer nanoparticles with an expanded palette of sizes, shapes and chemical functionalities for wide-ranging applications in various industries.

The new paradigm for the studied cyber-manufacturing of polymer nanoparticles will be achieved through critical breakthroughs in chemical-vapor-deposition based continuous synthesis and in-line characterization of polymeric nanostructures, integrated using artificial intelligence (AI)-guided selections of complex processing conditions. This research, if successful, will unlock vast design space for future nanomedicine, with a potential to substantially impact the healthcare industry and improve the quality of life of the society by and large.

Moreover, to prepare a diverse workforce for future manufacturing advancements, rigorous education research across an academic lifespan, from K-12 outreach to undergraduate and graduate education, as well as industry engagements, the team will establish a framework to understand identity-based motivation, which may in turn lead to broadened participation in STEM.

The overall goal of this future manufacturing research is to develop and investigate a novel paradigm to revolutionize manufacturing of polymer nanomaterials by integrating continuous processing, in-line characterization and AI-enabled accelerated data analysis to guide the production of programmed polymer nanoparticles. The core of this future manufacturing technology, also the key innovation, is a low-temperature initiated chemical vapor deposition (iCVD) polymerization with the use of gradient-surface-templated liquid crystals, which will leave optical fingerprints of fabricated features (spatial and temporal) that can be utilized for precision computer-vision image and data acquisitions.

The high-throughput experimental data will be employed to train a convolutional neural network to identify the size, shape and chemistry of polymer particles. The neural network will be further tested with separate data sets for validations to achieve AI-accelerated analytics and processing decision making. The outcome of the interdisciplinary research will generate new knowledge in iCVD, processing monitoring and mechanism using cyber-driven approaches.

The findings are expected to enable the novel manufacturing technology, scalable and modular, for unprecedented polymer structures, unachievable by traditional manufacturing means.

This FMRG is supported by the Divisions of Civil, Mechanical and Manufacturing Innovation (ENG/CMMI), Mathematical Sciences (MPS/DMS), Chemistry (MPS/CHE), Engineering Education and Centers (ENG/EEC), and the Division of Undergraduate Education (EHR/DUE).

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.