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Record W2082905254 · doi:10.3791/4424

Optical Trapping of Nanoparticles

2013· article· en· W2082905254 on OpenAlexafffund
Jarrah Bergeron, Ana Zehtabi-Oskuie, Saeedeh Ghaffari, Yuanjie Pang, Reuven Gordon

Bibliographic record

VenueJournal of Visualized Experiments · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicOrbital Angular Momentum in Optics
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTrappingOptical tweezersNanoparticleNanotechnologyMaterials scienceBiophysicsBiologyOpticsPhysicsEcology

Abstract

fetched live from OpenAlex

Optical trapping is a technique for immobilizing and manipulating small objects in a gentle way using light, and it has been widely applied in trapping and manipulating small biological particles. Ashkin and co-workers first demonstrated optical tweezers using a single focused beam. The single beam trap can be described accurately using the perturbative gradient force formulation in the case of small Rayleigh regime particles. In the perturbative regime, the optical power required for trapping a particle scales as the inverse fourth power of the particle size. High optical powers can damage dielectric particles and cause heating. For instance, trapped latex spheres of 109 nm in diameter were destroyed by a 15 mW beam in 25 sec, which has serious implications for biological matter. A self-induced back-action (SIBA) optical trapping was proposed to trap 50 nm polystyrene spheres in the non-perturbative regime. In a non-perturbative regime, even a small particle with little permittivity contrast to the background can influence significantly the ambient electromagnetic field and induce a large optical force. As a particle enters an illuminated aperture, light transmission increases dramatically because of dielectric loading. If the particle attempts to leave the aperture, decreased transmission causes a change in momentum outwards from the hole and, by Newton's Third Law, results in a force on the particle inwards into the hole, trapping the particle. The light transmission can be monitored; hence, the trap can become a sensor. The SIBA trapping technique can be further improved by using a double-nanohole structure. The double-nanohole structure has been shown to give a strong local field enhancement. Between the two sharp tips of the double-nanohole, a small particle can cause a large change in optical transmission, thereby inducing a large optical force. As a result, smaller nanoparticles can be trapped, such as 12 nm silicate spheres and 3.4 nm hydrodynamic radius bovine serum albumin proteins. In this work, the experimental configuration used for nanoparticle trapping is outlined. First, we detail the assembly of the trapping setup which is based on a Thorlabs Optical Tweezer Kit. Next, we explain the nanofabrication procedure of the double-nanohole in a metal film, the fabrication of the microfluidic chamber and the sample preparation. Finally, we detail the data acquisition procedure and provide typical results for trapping 20 nm polystyrene nanospheres.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.376
Teacher spread0.355 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2013
Admission routes2
Has abstractyes

Explore more

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