UV-patterned polymer dispersed liquid crystals: Impact of UV curing on electro-optical properties of image-embedded smart windows
Source abstract
Abstract
Polymer dispersed liquid crystal (PDLC) films are emerging as a promising technological candidate for smart windows, whereby spatial patterning of the films to yield visually appealing designs, logos or images can significantly broaden their application scenarios. This paper presents UV grayscale printing generated patterned-film of the PDLCs for smart windows. An inexpensive color-patterned polyethylene terephthalate (PET) film (< 1 US dollar for A4 size) was used as the mask for UV printing. A systematic investigation into the impact of composite ratio, and curing temperature on the electro-optical performance of PDLCs gave the optimized processing parameters for UV grayscale printing. Low threshold and saturation voltages below 40 V with contrast ratio as high as 4405 can be achieved. Specifically, we show that varying UV intensity by using UV grayscale printing can tune threshold voltage, saturation voltage, and hysteresis, and affect contrast in turn, whereby the pattern printing was achieved. The prototypes support three voltage-controlled states including the ‘dark state’ to protect privacy, the ‘total transparent state’ to see-through, and the ‘pattern display state’ to show images and texts. Furthermore, the prototypes can achieve kinds of embedded images in the pattern display by controlling the applied voltages through designing the UV grayscale printing. The proposed UV grayscale printing generated patterned film is compatible with the existing LC production process and roll-to-roll production line, which enables the grayscale pattern design and benefits the mass production of spatial-patterned PDLC films for image-embedded smart windows.
Source: expertdata · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Liquid Crystal Research Advancements · Advanced Materials and Mechanics · Semiconductor Lasers and Optical Devices
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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