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Record W2539894455 · doi:10.1002/sia.6186

Characterization of high‐aspect‐ratio periodic structures by X‐ray photoelectron spectroscopy

2016· article· en· W2539894455 on OpenAlexafffund
Kevin McEleney, Jared P. Bruce, Michael S. Freund

Bibliographic record

VenueSurface and Interface Analysis · 2016
Typearticle
Languageen
FieldMaterials Science
TopicElectron and X-Ray Spectroscopy Techniques
Canadian institutionsUniversity of ManitobaChildren's Hospital Research Institute of Manitoba
FundersCanada Excellence Research Chairs, Government of CanadaCanada Foundation for InnovationUniversity of Manitoba
KeywordsX-ray photoelectron spectroscopySubstrate (aquarium)SiliconCharacterization (materials science)Analytical Chemistry (journal)Base (topology)Materials scienceSurface (topology)RodPlanarSpectroscopyChemistryNanotechnologyOptoelectronicsPhysicsGeometryComputer scienceNuclear magnetic resonanceMathematicsGeology

Abstract

fetched live from OpenAlex

X‐ray photoelectron spectroscopy (XPS) is a powerful surface characterization technique often relied on for quantification of surface species and coverages. Investigation of silicon microrods, considered a model for high‐aspect‐ratio structures, at different angles with respect to substrate normal was determined to have a significant impact on the relative sensitivity of surface‐bound species on rods relative to the base substrate. Comparison between planar silicon and microrod arrays demonstrates that the angular dependence is complicated and that careful studies must optimize conditions to differentiate between surfaces. In addition, the use of reverse angle resolved XPS, where the substrate is turned away from the X‐ray source, is shown to assist in simplifying the spectrum by removing underlying signal from the substrate near the base. Copyright © 2016 John Wiley & Sons, Ltd.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.005
GPT teacher head0.252
Teacher spread0.247 · 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 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

Citations1
Published2016
Admission routes2
Has abstractyes

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