Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Journal of Lightwave Technology
  • Vol. 35,
  • Issue 18,
  • pp. 3854-3861
  • (2017)

Design of a Wavelength-Tunable Optical Tweezer Using a Graded-Index Multimode Optical Fiber

Not Accessible

Your library or personal account may give you access

Abstract

A wavelength-tunable optical fiber tweezer based on a graded index multimode fiber with a flat endface is proposed. The design offers a noncontact optical fiber tweezer generating a stable optical trap that can be tuned precisely over a large range using a common wavelength-tunable laser. This property comes from the wavelength dependence of the graded index multimode fiber design parameters, such as the numerical aperture. Using an optical fiber tweezer with a flat endface is also more desirable than the tapered one because of the easier fabrication process. Our analysis also shows that the setup can form a stable three-dimensional optical trap in the Rayleigh regime in the absence of any microfluidic flow force.

PDF Article
More Like This
Graded-index fiber tip optical tweezers: Numerical simulation and trapping experiment

Yuan Gong, Ai-Yan Ye, Yu Wu, Yun-Jiang Rao, Yao Yao, and Song Xiao
Opt. Express 21(13) 16181-16190 (2013)

Graded-index optical fiber tweezers with long manipulation length

Yuan Gong, Wei Huang, Qun-Feng Liu, Yu Wu, Yunjiang Rao, Gang-Ding Peng, Jinyi Lang, and Ke Zhang
Opt. Express 22(21) 25267-25276 (2014)

Optical OAM tweezer based on graded-index multimode fibers

Wenxu Ren, Yandong Gong, Zhuo Zhang, and Ke Li
Appl. Opt. 60(25) 7634-7639 (2021)

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.