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Cited by 419

The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.

Construction of multiple-beam optical traps with nanometer-resolution position sensing

Visscher, K., Gross, S.P., Block, S.M.·1996·IEEE Journal of Selected Topics in Quantum Electronics

Abstract

We describe the design and construction of two different types of multiple-beam optical tweezers, each equipped with nanometer-resolution position detectors. Multiple optical traps can be created either by splitting a laser beam in two parts, based on its polarization, or time-sharing a single beam among several different locations. The advantages and disadvantages of optical tweezers based on either scheme are discussed, along with details of specific implementations. Various ways to detect microscopic movements of an optically trapped object are presented and compared, including designs that are relatively insensitive to absolute location of a trapped particle within the field of view. Two of many possible applications for such instruments are illustrated: the detection of molecular steps by kinesin motor molecules, and determinations of the stiffness of single microtubules.

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Metadata

Authors
Visscher, K., Gross, S. P., & Block, S. M.
Venue
IEEE Journal of Selected Topics in Quantum Electronics
Published
1996
Volume
2
Issue
4
Pages
1066-1076
ISSN
1077-260X (ISSN-L)
OpenAlex
W2075540443
Cited by
419
References
28
FWCI
3.60
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Construction of multiple-beam optical traps with nanometer-resolution position sensing. https://app.cochat.ai/papers/10.1109/2944.577338
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Visscher, K., Gross, S. P., & Block, S. M. (1996). Construction of multiple-beam optical traps with nanometer-resolution position sensing. IEEE Journal of Selected Topics in Quantum Electronics. https://doi.org/10.1109/2944.577338

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.