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Record W4400496275 · doi:10.1063/5.0210675

Photoelectric charging and lofting of dust particles on a conducting surface with external electric fields

2024· article· en· W4400496275 on OpenAlexaff
Kelyan Taylor, Amanda Elliott, Xu Wang, M. Horányi, Rudiger Schmidt, Daniel Wollmann, Christoph Wiesner, Philippe Belanger

Bibliographic record

VenuePhysics of Plasmas · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDust and Plasma Wave Phenomena
Canadian institutionsTRIUMF
FundersNational Science Foundation
KeywordsPhysicsPhotoelectric effectElectric fieldPlasmaQuantum electrodynamicsAstrophysicsMechanicsAerospace engineeringOpticsNuclear physicsQuantum mechanics

Abstract

fetched live from OpenAlex

We present a laboratory study of photoelectric charging of dust particles and their lofting on a conducting surface in the presence of external electric fields. Insulating particles with diameter <45 μm are dispersed on a conducting surface exposed to ultraviolet (UV) light. In addition to the UV exposure, a positive or negative external electric field is applied. Independent of the orientation of the external electric field, the dust particles are found to be positively charged but with different mechanisms. It is shown that the orientation of the external electric field controls the dynamics of photoelectrons emitted from the dust particles and the conducting substrate surface. Distinctly different lofting results are shown between these two electric field cases. The results provide insight for understanding dust charging and release and helping develop mitigation solutions in particle accelerators, semiconductor manufacturing, fusion reactors, and space exploration to planetary bodies.

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 categoriesnone
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 score0.304
Threshold uncertainty score0.505

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)0.0000.000

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 head0.024
GPT teacher head0.241
Teacher spread0.217 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2024
Admission routes1
Has abstractyes

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