Acoustofluidic self-assembly of colloidal materials for additive manufacturing

Additive manufacturing techniques like 3D printing are being used extensively to produce custom-designed products in all walks of life- from household items to human organs to space shuttle parts. However, most additive manufacturing platforms use single materials or use extremely complicated processes to print multi-material products. Also, the microstructure of the materials cannot be controlled in many cases. The 3D printing sector is a USD 7 Billion market and is expected to grow at a rate of 25% per annum. At this rate of development, the use of printing multi-material components and creating programmable material structures will be crucial for the already booming market. In order to create programmable materials, it has been shown extensively that nano- and micro-material inclusions can produce customized material properties. Bottom-up material fabrication techniques like external-field directed self-assembly have been used to create programmable materials using colloidal particles, just like building a Lego structure. However, these self-assembled materials have been manufactured at the micro-scale and are often batch-produced, that makes it difficult to create bulk materials. Also, most self-assembled materials require clean-room and high-end equipment to fabricate the materials, which makes it highly expensive, inaccessible to common man and high complicated to integrate with additive manufacturing systems. I intend to use a combination of bottom-up colloidal self-assembly techniques with additive manufacturing platforms to create programmable, smart-materials that can be fabricated using 3D printing multi-material platforms and create portable additive manufacturing platforms to make it accessible for all. A high-throughput, continuous flow self-assembled material platform where colloidal particles, are self-assembled to create colloidal crystals in an acoustic field is developed. The colloidal crystals are embedded in a polymer, creating continuous colloidal particle-polymer composites fibers that can be 3D printed. Since the concentration of the colloidal solution and the acoustic field can be controlled, precise and programmable structures with varying mechanical, electrical and magnetic composite materials are developed. Our preliminary results show increased mechanical properties in PMMA-UV cured resin composites compared to randomly distributed composites and we demonstrate a graphene monolayer-polymer composite that can conduct selectively in particular regions. Similarly, we are working on creating a magnetic monolayer-polymer composite that can be used in robotic actuators. I am working on assembling the acoustic self-assembly platform on a CNC machine to 3D print the composited to form bulk materials. In addition, I worked on understanding the effect of acoustic and fluid fields on the assembly process to understand and the assembly kinetics using Force-biased Monte Carlo simulations to obtain defect-free materials. I have used various quantitative techniques like micro-Particle Image Velocimetry (PIV), order parameter analysis and image processing to analyze the experiments and correlate and compare them with the Monte Carlo simulations