Manufacturing Multi-Material Nanostructures Using Supercritical CO2-Assisted Spray Deposition

Texas A&M Engineering Experiment Station, College Station TX

Investigators

Abstract

This grant supports research that contributes new knowledge in manufacturing of nanostructured surfaces, promoting both the U.S. progress in manufacturing science and technology and advancing national prosperity. Nanostructured surfaces, often fabricated by depositing and patterning nanomaterials on desired substrates, are essential to provide functionalities such as structural, electrical, thermal, magnetic, optical, and audio in many devices. There are many manufacturing techniques to fabricate nanostructured surfaces. However, almost all these techniques require costly multi-step processes to prepare both nanomaterials and surfaces, could use hazardous solvents and are limited in the choice of materials. If multiple functionalities are required in a single application, these techniques are often incapable of depositing multiple types of materials at once on a single substrate. This grant supports fundamental research to provide needed knowledge for the development of a spray-deposition manufacturing process that enables scalable and high-precision manufacturing of multifunctional nanostructured surfaces with multiple materials without the need for costly preparations or use of hazardous solvents. This research enables manufacturing of structural multifunctional nanostructured surfaces with sizes ranging from micrometer to centimeter at large scale and reduced final costs with applications in functional coatings, wearable electronics, smart textiles and paints, and electronic devices. The results from this research will equip multiple U.S. industries with a new scalable manufacturing technique and thus benefit the U.S. economy and society with increased domestic job opportunities and more public access to smart technology. This research is an interdisciplinary effort that involves processing and manufacturing science, mechanics, materials science, and chemistry and trains the next generation of highly skilled engineers and scientists for the U.S. workforce. In addition, this research will provide unique research opportunities for women, underrepresented minority groups, and veteran students in STEM fields. The research findings will contribute to the education of K-12 students through training high-school teachers on nanomaterials and nanostructure manufacturing and help them integrate these concepts into their educational curriculum. The supercritical CO2-assisted spray-deposition manufacturing process can generate precisely patterned three-dimensional multi-material nanostructures by composing different nanomaterials patterns. This research will overcome several limitations existing in fabrication of nanostructured surfaces such as slow and costly treatment of the particles/substrates/solvent, use of external stimuli, narrow selection of materials due to compatibility of nanomaterials and solvent, and small build areas. This project intends to overcome these barriers by generating new knowledge on the development of nanomaterial patterns that form surface nanostructures controlled by intermolecular forces. This research will resolve the evolution of intermolecular force balance between nanomaterials and solid-liquid-gas interfaces in evaporating droplets and elucidate the effect of amphiphilicity and droplet properties on these forces. The research combines experimental characterization with density functional theory and molecular dynamics simulations to map specific intermolecular forces to nanomaterial patterns and the resultant nanostructures. This knowledge establishes Force-Pattern-Microstructure-Property relationship to transform the researched method into a viable material-agnostic manufacturing technique for fabrication of next generation of structural multifunctional components. 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.