Topological defects in the orientational order that appear in thin slabs of a nematic liquid crystal, as seen in the standard Schlieren texture, behave as a random quasi–two–dimensional system with strong optical birefringence. We present an approach to creating and controlling the defects using air pillars trapped by micropatterned holes in the silicon substrate. The arrayed air pillars stabilize and position the defects into regular two-dimensional lattices. We explore the effects of hole shape, cell thickness, lattice symmetry, and surface treatment on the resulting lattices of defects and explain their arrangements by application of topological rules. We also fabricate topological solitons with knotted continuous field configurations embedded in a uniform background, which occur in cosmology, biology, and electromagnetism. Direct visualization can be conducted due to our platform's proper size and time scale. We rationalize the real-time observation of the generation and transformation of topological solitons using the chiral nematic LC confined in the patterned substrates (Fig. 1). Furthermore, we control the topological defects and their interaction appearing in fixed spherical microparticle arrays fabricated by capillarity-assisted particle assembly (CAPA) technique, which has not yet been experimentally observed over large areas because of a lack of robust strategies to fix three-dimensional spherical particles within tailored arrays. Boojum defect arrays are generated in fixed planar anchoring silica microparticle lattice in the nematic liquid crystal media, and separation-dependent behavior of interacting boojum defects on the particles is observed.
We also present a facile approach to fabricate a physical unclonable function (PUF) based on topological solitons. Our platform operates as artificial fingerprints, and authenticity can be determined with high reliability and discernibility by an optical microscope cooperated with machine learning-based object detection. “Information” in the resultant system is sufficiently randomized to be challenging to predict and even can be reconstructed by thermal phase transitions in tens of seconds.
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean Government (MSIT) RS-2023-00273025, 2019K1A3A1A14065772, and 2018R1A5A1025208.
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