Polymer stabilized cholesteric liquid crystals enhanced by functional nanofibers loaded with CuS NPs and ATO NPs for efficient smart windows and advanced infrared camouflage/anti-counterfeiting technologies
Source abstract
Abstract
The development of multifunctional smart windows with infrared anti-counterfeiting capabilities is a key research priority. However, achieving both high visible light (VIS) transparency and effective near-infrared (NIR) blocking remains a significant challenge. In this study, a multi-field responsive polymer stabilized cholesteric liquid crystal (PSCLC) smart window was successfully prepared. By adjusting the electric field, the smart window enables controlled adjustment of incident VIS and NIR light for temperature control. Optimization of polymerization conditions and nanofiber loading enhanced the bandwidth reflectance from 256 to 507 nm. The smart window employs an optimized drive scheme for coordinated IR modulation via direct current (DC). The copper sulfide (CuS) and antimony tin oxide (ATO) nanoparticles were loaded in the PSCLC system using electrostatic spinning technique. The loading of nanoparticles using nanofibers greatly increased the number of nanoparticles compared to direct doping of nanoparticles. Therefore, the nanofibers loaded with nanoparticles greatly enhanced the infrared shielding ability and electrical response of the system. In addition, the enhancement of nanofibers also improves the thermal and electrical durability of the PSCLC smart window, and the controlled distribution of nanofibers results in a highly flexible and reliable infrared anti-counterfeiting smart window. This research provides the development of multifunctional liquid crystal smart windows with infrared light modulation, camouflage and anti-counterfeiting functions.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Liquid Crystal Research Advancements · Advanced Materials and Mechanics · Advanced Sensor and Energy Harvesting Materials
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (45)
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