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Record W4385841160 · doi:10.1063/5.0130235

<i>In-plasma</i> analysis of plasma–surface interactions

2023· article· en· W4385841160 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueReview of Scientific Instruments · 2023
Typearticle
Languageen
FieldEngineering
TopicIon-surface interactions and analysis
Canadian institutionsPhoton Etc (Canada)Plasmionique (Canada)Université de Montréal
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaUniversité de MontréalCanada Foundation for Innovation
KeywordsElastic recoil detectionMaterials sciencePlasmaRaman spectroscopyAtomic physicsPlasma processingPlasma diagnosticsExcited stateIonIonizationAnalytical Chemistry (journal)Thin filmOpticsChemistryPhysicsNanotechnology

Abstract

fetched live from OpenAlex

During deposition, modification, and etching of thin films and nanomaterials in reactive plasmas, many active species can interact with the sample simultaneously. This includes reactive neutrals formed by fragmentation of the feed gas, positive ions, and electrons generated by electron-impact ionization of the feed gas and fragments, excited states (in particular, long-lived metastable species), and photons produced by spontaneous de-excitation of excited atoms and molecules. Notably, some of these species can be transiently present during the different phases of plasma processing, such as etching of thin layer deposition. To monitor plasma-surface interactions during materials processing, a new system combining beams of neutral atoms, positive ions, UV photons, and a magnetron plasma source has been developed. This system is equipped with a unique ensemble of in-plasma surface characterization tools, including (1) a Rutherford Backscattering Spectrometer (RBS), (2) an Elastic Recoil Detector (ERD), and (3) a Raman spectroscopy system. RBS and ERD analyses are carried out using a differentially pumped 1.7 MV ion beam line Tandetron accelerator generating a beam at grazing incidence. The ERD system is equipped with an absorber and is specifically used to detect H initially bonded to the surface; higher resolution of surface H is also available through nuclear reaction analysis. In parallel, an optical port facing the substrate is used to perform Raman spectroscopy analysis of the samples during plasma processing. This system enables fast monitoring of a few Raman peaks over nine points scattered on a 1.6 × 1.6 mm2 surface without interference from the inherent light emitted by the plasma. Coupled to the various plasma and beam sources, the unique set of in-plasma surface characterization tools detailed in this study can provide unique time-resolved information on the modification induced by plasma. By using the ion beam analysis capability, the atomic concentrations of various elements in the near-surface (e.g., stoichiometry and impurity content) can be monitored in real-time during plasma deposition or etching. On the other hand, the evolution of Raman peaks as a function of plasma processing time can contribute to a better understanding of the role of low-energy ions in defect generation in irradiation-sensitive materials, such as monolayer graphene.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.487
Threshold uncertainty score0.758

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.007
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 head0.016
GPT teacher head0.280
Teacher spread0.265 · 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