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Record W2043714894 · doi:10.1086/320963

Forces on Dust Grains Exposed to Anisotropic Interstellar Radiation Fields

2001· article· en· W2043714894 on OpenAlexaff
Joseph C. Weingartner, B. T. Draine

Bibliographic record

VenueThe Astrophysical Journal · 2001
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsCanadian Institute for Theoretical AstrophysicsUniversity of Toronto
Fundersnot available
KeywordsAnisotropyPhotoelectric effectPhysicsRadiationRadiation pressureAbsorption (acoustics)Interstellar mediumCosmic dustStarlightPhotonScatteringRadiation damageAstrophysicsStarsComputational physicsAtomic physicsOpticsGalaxy

Abstract

fetched live from OpenAlex

Grains exposed to anisotropic radiation fields are subjected to forces due to the asymmetric photon-stimulated ejection of particles. These forces act in addition to the "radiation pressure" due to absorption and scattering. Here we model the forces due to photoelectron emission and the photodesorption of adatoms. The "photoelectric" force depends on the ambient conditions relevant to grain charging. We find it is comparable to the radiation pressure when the grain potential is relatively low and the radiation spectrum is relatively hard. The calculation of the "photodesorption" force is highly uncertain since the surface physics and chemistry of grain materials are poorly understood at present. For our simple yet plausible model, the photodesorption force dominates the radiation pressure for grains larger than ~0.1 μm exposed to starlight from OB stars. We find that the anisotropy of the interstellar radiation field is ~10% in the visible and ultraviolet. We estimate size-dependent drift speeds for grains in the cold and warm neutral media and find that micron-sized grains could potentially be moved across a diffuse cloud during its lifetime.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.244
Teacher spread0.230 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations73
Published2001
Admission routes1
Has abstractyes

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