Optical tweezers as sub-pico-newton force transducers

Huang, Chun-Cheng; Wang, Chia-Fong; Mehta, Dalip Singh; Chiou, Arthur

doi:10.1016/s0030-4018(01)01329-3

Cited by 24 publications

(12 citation statements)

References 22 publications

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“…Several technologies have been reported for the characterization of biological materials such as magnetic tweezers [7], optical tweezers [8], atomic force microscopy (AFM) [9][10], substrate stretching [11], micropipette aspiration [12] and MEMS-based devices.…”

Section: Introductionmentioning

confidence: 99%

Quantifying growth mechanics of living, growing plant cells in situ using microrobotics

et al. 2011

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Section: Introductionmentioning

confidence: 99%

Quantifying growth mechanics of living, growing plant cells in situ using microrobotics

et al. 2011

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“…[2][3][4][5][6][7] Various kinds of microparticles have been trapped by optical tweezers. [8][9][10][11] The particles which were absorbing or reflecting could be trapped in hollow beams like Laguerre Gaussian beams.…”

Section: Introductionmentioning

confidence: 99%

Optical trapping of fluorescent beads

Bhatt

Kumar

Singh

et al. 2013

Journal of Experimental Nanoscience

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Optical tweezers have been successfully used to trap a variety of particles and biological specimens for numerous applications. Particles which are reflective as well as absorbing could be trapped using beams such as optical vortex. Here we give the details of our efforts to trap fluorescent microparticles. We have set up an optical trap for these fluorescent microparticles using holographic optical tweezers; we observe that it is not possible to trap fluorescent microparticles with a Gaussian laser beam or a hollow beam. However, as the fluorescence of these particles gets degraded they could be trapped in custom-made holographic tweezers. Moreover, when a fluorescent particle is brought in the trap containing stably trapped non-fluorescent particle, the stably trapped non-fluorescent particle also escapes from the trap.

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“…Measurement with optical tweezers [1,2] is based on the interaction between light and micro-particles, i.e., the relationship of the force upon the micro-particles and the position in an optical trap. The theory and experiment [2][3][4] show that for different optical traps formed by different optical beams, a slight lateral displacement of the bead yields a good linear relationship of the lateral optical trap efficiency and the particle position.…”

Section: Introductionmentioning

confidence: 99%

“…The theory and experiment [2][3][4] show that for different optical traps formed by different optical beams, a slight lateral displacement of the bead yields a good linear relationship of the lateral optical trap efficiency and the particle position. Hence the region is called a harmonic region.…”

Section: Introductionmentioning

confidence: 99%

“…If the non-linear correction is included in the measurement system and the calibration and measurement of output value in the entire range with a linear relationship, we can expand the effective linear range of the force measuring of the optical tweezer system. In earlier studies, a triple polynomial has been used to fit the non-linear relation of optical trapping force and displacement of the particle [2,6,7]. Although the relation can be measured using the scope of harmonic areas and expands the range of the force measurement system, this method lacks accuracy.…”

Section: Introductionmentioning

confidence: 99%

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Application of BP neural networks in non-linearity correction of optical tweezers

Wang

Lou

et al. 2008

Front. Electr. Electron. Eng. China

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The back-propagation (BP) neural network is proposed to correct nonlinearity and optimize the force measurement and calibration of an optical tweezer system. Considering the low convergence rate of the BP algorithm, the Levenberg-Marquardt (LM) algorithm is used to improve the BP network. The proposed method is experimentally studied for force calibration in a typical optical tweezer system using hydromechanics. The result shows that with the nonlinear correction using BP networks, the range of force measurement of an optical tweezer system is enlarged by 30% and the precision is also improved compared with the polynomial fitting method. It is demonstrated that nonlinear correction by the neural network method effectively improves the performance of optical tweezers without adding or changing the measuring system.

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Optical tweezers as sub-pico-newton force transducers

Cited by 24 publications

References 22 publications

Quantifying growth mechanics of living, growing plant cells in situ using microrobotics

Quantifying growth mechanics of living, growing plant cells in situ using microrobotics

Optical trapping of fluorescent beads

Application of BP neural networks in non-linearity correction of optical tweezers

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