Programmable Surfaces by Scalable Self-assembly of Particles Printed by Two-photon Polymerization

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Textured surfaces with micro-scaled features have many engineering applications such as self-cleaning, enhanced gripping and directional light scattering, etc. However, it is challenging to manufacture textured surfaces over a large area with high fidelity, needless to mention the issues with quality control, pattern complexity and special equipment needs, etc. This award supports fundamental research in self-assembling of countless polyhedral particles in a solution to achieve a wide range of micro-textured patterns. Beyond common geometry that can be fabricated using conventional lithography techniques, the unique innovation of this project is the use of two-photon polymerization to fabricate particles of complex shapes, which enable tunable in-plane and out-of-plane periodicities and out-of-plane protrusions in the self-assembly of micro-patterned surfaces. The studied self-assembled textured surfaces can potentially be programmed and achieve controllable wettability or be used as coatings, especially attractive for curved and/or delicate substrates in applications such as organic photovoltaics and wearable sensors. The educational activities consist of developing and implementing a particle self-assembly learning module for elementary school students, hosting a student, via summer internship, from a local Hispanic community college, and incorporating the topic of self-assembly into a graduate course on defects in crystalline solids.Using a three-dimensional printing technology, namely, two-photon polymerization, this project will fabricate micro-scaled particles for self-assembly into textured surfaces. Arrays on the order of 200,000 particles will be printed on a solid substrate, transferred to a liquid-filled well, and then self-assembled through a balance of sedimentation, diffusion, interparticle and particle-substrate interactions. Particles of different geometries will be investigated including tetrahedrons and square pyramids of varying sized as well as binary particle systems, to obtain a tunable feature height and periodicity formed at a millimeter scale. An optical microscope will be utilized to acquire video images of particle motions along the self-assembling time with automated image analyses to evaluate the quality of the self-assembled surface. The bond and body order parameters will be analyzed to understand the degree of uniformity that can be achieved under different processing conditions, and the types of defects generated during such a self-assembly process. Theoretical studies will include the Brownian motion modeled using the Einstein-Stokes equation and the energetic driving force modeled using the DLVO principle to design self-assembly experiments that are likely to succeed, and then compared against experimental results to gain new knowledge of what governs the self-assembly mechanisms.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.