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Plasmas Afterglows with N2 for Surface Treatments New Results

2024· book-chapter· en· W4399019071 on OpenAlexaboutno aff
A. Ricard

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldMedicine
TopicPlasma Applications and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsAfterglowAtomic physicsPhysicsAtom (system on chip)MetastabilityCrystallographyChemistryQuantum mechanicsGamma-ray burst

Abstract

fetched live from OpenAlex

It presently reported new results of previous books Plasmas Afterglows with N2 for Surface Treatments, editions 1-3, published by Bookpi – editions in 2021, 2022 and 2023. These previous books were focused on the production of plasma active species with \(\mathrm{N}_2\) which contain molecules in electronic, vibrational and rotational states and dissociated atoms or radicals. The method of NO titration of \(\mathrm{N}\) and \(\mathrm{O}\)-atoms density and that of the percentage of afterglow resulting from \(\mathrm{N}\)-atom recombination were detailed. The relevant kinetics equations in the afterglow and the intensity ratio method to obtain the radiative species density from that of \(\mathrm{N}\)-atoms were elucidated. By this method, it was obtained the densities of \(\mathrm{O}, \mathrm{H}\) and \(\mathrm{C}\)-atoms, of \(\mathrm{N}_2(A)\) and \(\mathrm{N}_2(X, v>13)\) metastable molecules, and of \(\mathrm{NH}, \mathrm{NO}\) and \(\mathrm{CN}\) radicals. The plasmas and afterglows were obtained by a microwave supply at reduced gas pressures in the Montreal and Toulouse Univ. and at atmospheric gas pressure in the Orsay, Pau and Toulouse Univ. From recent results obtained in Laplace Lab. concerning the Laser fluorescence measurements (TALIF) of \(\mathrm{N}\) and \(\mathrm{H}\) atoms density in \(\mathrm{N}_2-\mathrm{H}_2\) afterglows (PHD thesis of V.Ferrer, Toulouse 2023), it is deduced in the first chapter that the rate coefficient of the \(\mathrm{N}+\mathrm{H}+\mathrm{M}\left(\mathrm{N}_2, \mathrm{Ar}\right) \rightarrow \mathrm{NH}+\mathrm{M}\left(\mathrm{N}_2, \mathrm{Ar}\right)\) reaction, chosen in Chapter 2, 4 and 13 of the previous books (editions 1-3, 2021-23) must be divided by 50 with \(M=\mathrm{N}_2\) and 20 with \(M=A r\) that confirms the assumed value of \(10^{-33} \mathrm{~cm}^6 \mathrm{~S}^{-1}\) for \(M=\mathrm{N}_2\) of Gordiets et al. 1998. It is also discussed in this new chapter on the method to obtain the a \({ }_{N+N}\) part of the \(N+N\) recombination to produce the \(N_2\left(B, v^{\prime}=11\right)\) radiative state, the key to calibrating the \(\mathrm{N}\)-atom density in the flowing afterglow.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.265
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)0.0000.001

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 head0.028
GPT teacher head0.270
Teacher spread0.242 · 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 designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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