Extinction cross section measurements for a single optically trapped particle
Bibliographic record
Abstract
Bessel beam (BB) optical traps have become widely used to confine single and multiple aerosol particles across a broad range of sizes, from a few microns to < 200 nm in radius. The radiation pressure force exerted by the core of a single, zeroth-order BB incident on a particle can be balanced by a counter-propagating gas flow, allowing a single particle to be trapped indefinitely. The pseudo non-diffracting nature of BBs enables particles to be confined over macroscopic distances along the BB core propagation length; the position of the particle along this length can be finely controlled by variation of the BB laser power. This latter property is exploited to optimize the particle position at the center of the TEM00 mode of a high finesse optical cavity, allowing cavity ring-down spectroscopy (CRDS) to be performed on single aerosol particles and their optical extinction cross section, σext, measured. Further, the variation in the light from the illuminating BB elastically scattered by the particle is recorded as a function of scattering angle. Such intensity distributions are fitted to Lorenz-Mie theory to determine the particle radius. The trends in σext with particle radius are modelled using cavity standing wave Mie simulations and a particle’s varying refractive index with changing relative humidity is determined. We demonstrate σext measurements on individual sub-micrometer aerosol particles and determine the lowest limit in particle size that can be probed by this technique. The BB-CRDS method will play a key role in reducing the uncertainty associated with atmospheric aerosol radiative forcing, which remains among the largest uncertainties in climate modelling.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".