CAREER: Evaluating the Process-Structure-Property Relationships of Carbon Nanotube Forests with In-Situ Synthesis Observation and Dynamic Simulations

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This Faculty Early Career Development (CAREER) Program research project investigates how carbon nanotubes interact with one another during collective growth by using direct observation and complimentary numerical simulation. Nanoscale materials such as carbon nanotubes offer superior mechanical, electrical, and thermal properties relative to many other conventional engineering materials. When vast arrays of carbon nanotubes are synthesized together they form interconnected and self-organized populations known as carbon nanotube forests. The interactions between growing nanotubes lead to the structures bending and kinking which detract from their mechanical properties. Numerical simulations employing artificial intelligence and machine learning will facilitate the rapid exploration of high-dimensional processing space associated with nanotube formation and will guide the experimental aspects of this project. The results of this work and the understanding of the synthesis process will help control the mechanisms of carbon nanotube interactions during their synthesis, leading to enhanced and engineered carbon nanotube forest properties. Middle school students will be engaged with the research through a one-week summer camp in which hands-on nanoscale materials engineering will be merged with artistic expression through collaboration with the University of Missouri Museum of Art and Archeology. The results of these investigations will enable the use of the art and observation at the nanoscale to engage and inspire grade school children in STEM-based learning in cooperation with the university art museum.The forces and mechanisms that drive carbon nanotube forest self-assembly are currently poorly understood, in part because in-situ diagnostic techniques with sufficient resolution to interrogate the evolving mechanical interactions are lagging. This project will implement direct visualization of carbon nanotube forest growth and assembly using in-situ synthesis methods within scanning and transmission electron microscopes. A variety of synthesis conditions will be investigated to link the role of important processing factors to the observed behaviors. Transmission electron microscope techniques will facilitate not only time-resolved visual inspection of individual nanotubes and their host catalyst nanoparticles but also compositional analyses at or near atomic resolution. Scanning electron microscope techniques will examine coordinated assembly of carbon nanotubes within the larger population at length scale ranging from tens of nanometers of tens of microns. Experimental observations will be input into a time-resolved finite element simulation to interrogate the forces generated during nanotube forest assembly. After synthesis, the mechanical properties of carbon nanotube forests will be measured using in-situ scanning electron microscope compression and simulated with the finite element model for validation. The validated model will serve as a vehicle for rapid assessment of process-structure-property relationships using an artificial intelligence algorithm to autonomously search for appropriate synthesis conditions that satisfy user-defined forest property sets. A carbon nanotube forest synthesis simulation tool will be made publically available at nanohub.org to facilitate broader impact of the simulations developed in this project.