ERI: Additive Manufacturing of Polymer-Matrix Composites with High Concentration of Silicon-Carbide Particles by Novel Digital Light Projection
- Institution
- University of North Carolina at Charlotte, NC
- Principal investigator
- Erina Baynojir Joyee
- Funding
- $200K
- Duration
- 2023–2025
Moonbase score
Still being scored
Abstract
Additive manufacturing (AM) offers a versatile platform for fabricating ceramic-polymer composites of complex structures. Over the last two decades, various innovative AM processes have been successfully developed for ceramic-polymer 3D printing. Especially, methods based on digital light projection (DLP) enable the direct digital fabrication of intricate structures made of ceramic-polymer composites. Despite potential advantages, current DLP AM have difficulty in printing composites with a high concentration of ceramic particles, e.g., silicon carbide (SiC), desired to enhance the functionality of printed parts. The challenge lies upon the increased viscosity resulted from the particle-polymer interactions, causing high resistance to the feedstock flow. This Engineering Research Initiation (ERI) award supports fundamental research to understand the physics behind printing of ceramic-included photopolymers that are highly viscous. The research involves multi-disciplinary integration of physics, materials science, surface engineering, and manufacturing technology. The project will have strong technological and economic impacts by streamlining production of components with complex geometries, e.g., gyroid structures, for scaffolding and heat exchangers, in an efficient and cost-effective manner, while ensuring the quality in part dimensions as well as microstructures. Moreover, this project will involve minority students in research and teaching, thus, enhancing the STEM education and their representation in advanced manufacturing workforce. The goal of this ERI project is to understand the fundamentals behind two major roadblocks, namely, high separation forces and light scattering, in 3D digital-light printing of complex-shaped parts using highly viscous ceramic suspensions. The project will first address the challenge of high separation forces through the “resin replenishment” mechanism by integrating oxygen permeability into the system, introducing micro-textured air channels to accelerate the resin re-coating and reduce the separation force between the printed part and the build window. Secondly, a dynamic mask image projection strategy will be modeled and employed to minimize the effect of light scattering and undesired photo patterns within the printed part. This will enable high-accuracy and high-speed fabrications of 3D polymer-ceramic parts with complex geometry and precise micro-features. If successful, the project will make a transformative impact of applying surface engineering techniques to oxygen permeable air channels for bottom-up layer-by-layer 3D printing of SiC-polymer composite structures with enhanced mechanical properties. The research will also advance the knowledge of novel projection using dynamic mask images to compensate for the influence of light scattering on curing results. Accordingly, a new technology will be developed to avoid curing defects or failures in high-viscosity ceramic printing and enable producing complex geometries that are challenging to make using existing systems. 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.
LOADING MOONBASE SCORE
Questions for University of North Carolina at Charlotte
Answered by the team behind this research.
No questions yet. Sign in to ask the first one
Related grants
Same institution, same topic, scored first.
- NSF · University of North Carolina at Charlotte61
Collaborative Research: MoDL: Graph-Optimized Cellular Connectionism via Artificial Neural Networks for Data-Driven Modeling and Optimization of Complex Systems
Minwoo Lee · $224K · 2023–2026
- NSF · University of North Carolina at Charlotte55
CRII:SCH:Self-Supervised Contrastive Representation Learning for Medical Time Series
Xiang Zhang · $175K · 2023–2026
- NSF · University of North Carolina at Charlotte54
CRII: CIF: Leveraging the Laplacian Paradigm for Efficient Non-Convex Optimization in Transportation and Payment Channel Networks
Christian E Kümmerle · $175K · 2024–2025