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Proceedings Paper

Planar micro-nano-coils for electrically driving liquid crystal microlenses based on wireless power transmission
Author(s): Cheng Chen; Wei Hu; Jun Luo; Yu Lei; Qing Tong; Xinyu Zhang; Hongshi Sang; Changsheng Xie
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Paper Abstract

In this paper, the planar micro-nano-coils (PMNCs) with diverse planar spiral structures are designed for electrically driving and controlling liquid crystal microlenses (LCMs) based on wireless power transmission approaches. The PMNCs with different basic shapes are fabricated, including typical micro-triangle, micro-square, micro-pentagon, micro-hexagon, and micro-circle. According to the designed microstructures, using loop iterative approximation means based on Greenhouse algorithm, the inductance values of the microcoils can be calculated through combining self-inductance with mutual-inductance. In experiments, both the wet and dry etching technologies are adapted to obtain the desired PMNCs over aluminum-coated glass substrates. The etching technologies utilized by us are implemented on initial glass substrates spread by photoresist mask, which has been processed by common ultraviolet lithography. And the wet and dry etching technologies are different in the way of eroding aluminum film. Usually, the wet etching is a kind of the chemical reaction of alkali element in the developing liquid used, but the dry etching is a type of physical etching process such as the ion beam etching so as to fabricate microstructures with smaller size than that of wet etching. After the fabrication of the PMNCs, the electrical testing circuit for the inductance of the PMNCs is built to obtain their actual inductance values. By comparing inductances with theoretical prediction, the improved PMNCs are proposed for driving and controlling LCMs, which demonstrates enhanced light transmission efficiency of the PMNCs, and makes it more efficient to adjust LCMs developed by us.

Paper Details

Date Published: 17 December 2015
PDF: 7 pages
Proc. SPIE 9811, MIPPR 2015: Multispectral Image Acquisition, Processing, and Analysis, 981105 (17 December 2015); doi: 10.1117/12.2204807
Show Author Affiliations
Cheng Chen, Huazhong Univ. of Science and Technology (China)
Wei Hu, Huazhong Univ. of Science and Technology (China)
Jun Luo, Huazhong Univ. of Science and Technology (China)
Huazhong Agricultural Univ. (China)
Yu Lei, Huazhong Univ. of Science and Technology (China)
Shijiazhuang Tiedao Univ. (China)
Qing Tong, Huazhong Univ. of Science and Technology (China)
Xinyu Zhang, Huazhong Univ. of Science and Technology (China)
Wuhan National Lab. for Optoelectronics (China)
Hongshi Sang, Huazhong Univ. of Science and Technology (China)
Changsheng Xie, Wuhan National Lab. for Optoelectronics (China)


Published in SPIE Proceedings Vol. 9811:
MIPPR 2015: Multispectral Image Acquisition, Processing, and Analysis
Jinxue Wang; Zhiguo Cao; Jayaram K. Udupa; Henri Maître, Editor(s)

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