journal article·2026-04-01

Inkjet-Printed Cholesteric Liquid Crystal Pixels with Frequency-Addressable Optical Memory for Energy-Efficient Reflective Displays

Jun-Seok Ma, Dongryul Lee, Hyun-Woo Oh, Gyungin Ryu, Jin-Young Choi, Seung-Won Oh, Jong-Hyun Ka, Adithya Pradeep, Jinge Guo, Sungjune Jung, Wook-Sung Kim

ACS Applied Materials & Interfaces· Volume 18· Issue 12
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Abstract

We present an inkjet-defined cholesteric liquid crystal (CLC) pixel architecture that enables frequency-addressable tristable optical memory for energy-efficient reflective modulation. Drop-on-demand printing forms individually programmable CLC droplets in a scalable, mask-free format, translating frequency-driven multistability into a manufacturable pixel platform. Each printed pixel can be electrically written into three optically distinct states: a transparent colored state, a colorless opaque concealment state, and a colored opaque memory state that remains stable after removal of the driving field. The tristability originates from frequency-selective competition between ion-mediated electrohydrodynamic convection at low frequency and dielectric realignment at high frequency. By encoding optical states through frequency programming rather than sustained bias, the device achieves true field-off retention without continuous power input. The printed arrays reach 63.5 dpi with uniform switching over areas up to 8.5 × 8.5 cm 2, exhibit repeatable cycling without threshold drift, and show negligible thermal load during operation. By integrating structural coloration, transmittance modulation, and nonvolatile optical memory within a scalable inkjet process, this work establishes a practical pathway toward large-area smart windows, reflective displays, and programmable photonic surfaces.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Liquid Crystal Research Advancements · Electrowetting and Microfluidic Technologies · Photonic Crystals and Applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Electrical Engineering

Pohang University of Science and Technology (POSTECH)

Natural Sciences Research Institute (NSRI)

Korea Advanced Institute of Science and Technology (KAIST)

Department of Materials Science and Engineering

Department of Electrical and Information Communication Engineering

Kangwon National University

Department of Engineering Science, University of Oxford, Parks Road, Oxford OX1 3PJ, U.K.

Funding

National Research Foundation of Korea · Korea Advanced Institute of Science and Technology

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