Abstract This paper describes the preparation, physical properties, and electric bending actuation of a new class of active materials—ionic liquid crystal elastomers (iLCEs). It is demonstrated that iLCEs can be actuated by low‐frequency AC or DC voltages of less than 1 V. The bending strains of the unoptimized first iLCEs are already comparable to the well‐developed ionic electroactive polymers. Additionally, iLCEs exhibit several novel and superior features, such as the alignment that increases the performance of actuation, the possibility of preprogrammed actuation patterns at the level of the cross‐linking process, and dual (thermal and electric) actuations in hybrid samples. Since liquid crystal elastomers are also sensitive to magnetic fields and can also be light sensitive, iLCEs have far‐reaching potentials toward multiresponsive actuations that may have so far unmatched properties in soft robotics, sensing, and biomedical applications. 
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                            Tunable, Low–Cost, Multi–Channel, Broadband Liquid Crystal Shutter for Fluorescence Imaging in Widefield Microscopy
                        
                    
    
            Bistable liquid crystal (LC) shutters have attracted much interest due to their low energy consumption and fast response time. In this paper, we demonstrate an electrically tunable/switchable biostable LC light shutter in biological optics through a three–step easy–assembly, inexpensive, multi–channel shutter. The liquid crystal exhibits tunable transparency (100% to 10% compared to the initial light intensity) under different voltages (0 V to 90 V), indicating its tunable potential. By using biomedical images, the response time, resolution, and light intensity changes of the LC under different voltages in three common fluorescence wavelengths are displayed intuitively. Particularly, the shutter’s performance in tumor images under the near–infrared band shows its application potential in biomedical imaging fields. 
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                            - Award ID(s):
- 1808436
- PAR ID:
- 10382660
- Date Published:
- Journal Name:
- Micromachines
- Volume:
- 13
- Issue:
- 8
- ISSN:
- 2072-666X
- Page Range / eLocation ID:
- 1310
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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