Excellence in Research: Direct Ink Writing of Continuous Fiber-reinforced Smart Composites: Adaptive Processing with Sustainable Design Integration

North Carolina Agricultural & Technical State University, Greensboro NC

Investigators

Abstract

4D printing, a form of additive manufacturing that fabricates “smart” structures capable of changing shape in response to external stimuli, offers a promising solution for self-disassembly of multiple components. However, broader adoption of 4D printing for environmentally favorable applications is hindered by challenges such as the difficulty of printing high-strength structures with precise shape-morphing properties and high printing fidelity, as well as the lack of methodologies to optimize structures for functionality, mechanical strength, and sustainability. This award funds research that seeks to advance process science by developing a versatile 4D printing platform for creating mechanically reinforced, smart structures that enable self-actuation and self-(dis)assembly, ultimately fostering circularity in manufacturing. By advancing computational and design tools, research funded by this award seeks to transform modern additive manufacturing platforms with improved material compatibility that are better suited for environmentally sustainable applications. The findings are also expected to support a cutting-edge experimental and computational framework to expand access to high-quality engineering education and training for students. Research to be enabled by this award is expected to develop a versatile direct ink writing-based 4D printing platform for continuous fiber-reinforced stimuli-responsive composites and advance its capability through three tasks: (i) Developing a cross-material multi-property prediction framework to accurately map matrix material and fiber compositions to their stimuli-response behaviors and mechanical properties, accommodating a broad range of composite configurations; (ii) Advancing direct printing techniques with reinforcement learning-based adaptive control with transfer learning modules for improved algorithmic generalization to enhance printing fidelity and adaptability across different materials and printing platforms; and (iii) Establishing a concurrent design method for continuous fiber-reinforced smart composites, ensuring high-performance structures that balance mechanical strength and shape-morphing capabilities for sustainability-driven applications. The research looks to generate new insights into material representation and multi-property prediction for smart composites and develop adaptive processing strategies to establish a generalizable and accessible smart manufacturing infrastructure. The outcomes may also inspire the design and manufacture of functionally engineered, advanced materials tailored for dynamic environments and environmentally conscious applications. 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.