Article, 2024

Spatial Photo-Patterning of Nematic Liquid Crystal Pretilt and its Application in Fabricating Flat Gradient-Index Lenses

Advanced Materials, ISSN 0935-9648, Volume 36, 23, 10.1002/adma.202310083

Contributors

Modin A. 0000-0002-1195-1368 (Corresponding author) [1] Leheny R.L. 0000-0002-8924-1622 [1] Serra F. 0000-0002-7308-7616 (Corresponding author) [1] [2]

Affiliations

  1. [1] Johns Hopkins University
  2. [NORA names: United States; America, North; OECD];
  3. [2] University of Southern Denmark
  4. [NORA names: SDU University of Southern Denmark; University; Denmark; Europe, EU; Nordic; OECD]

Abstract

Liquid crystals offer a dynamic platform for developing advanced photonics and soft actuation systems due to their unique and facile tunability and reconfigurability. Achieving precise spatial patterning of the liquid crystal alignment is critical to developing electro-optical devices, programmable origami, directed colloidal assembly, and controlling active matter. Here, a simple method is demonstrated to achieve continuous 3D control of the directions of liquid crystal mesogens using a two-step photo-exposure process. In the first step, polarized light sets the orientation in the plane of confining substrates; the second step uses unpolarized light of a prescribed dose to set the out-of-plane orientation. The method enables smoothly varying orientational patterns with sub-micrometer precision. As a demonstration, the setup is used to create gradient-index lenses with parabolic refractive index profiles that remain stable without external electric fields. The lenses' focal length and sensitivity to light polarization are characterized through experimental and numerical methods. The findings pave the way for developing next-generation photonic devices and actuated materials, with potential applications in molecular self-assembly, re-configurable optics, and responsiveĀ matter.

Keywords

liquid crystal devices, microlenses, nematic pretilt, photoalignment

Funders

  • United States-Israel Binational Science Foundation
  • National Science Foundation

Data Provider: Elsevier