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Record W2130322281 · doi:10.1017/s143192761200150x

Contribution of a New Generation Field-Emission Scanning Electron Microscope in the Understanding of a 2099 Al-Li Alloy

2012· article· en· W2130322281 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

VenueMicroscopy and Microanalysis · 2012
Typearticle
Languageen
FieldMaterials Science
TopicElectron and X-Ray Spectroscopy Techniques
Canadian institutionsHydro-QuébecMcGill University
FundersHydro-QuébecAlcoa
KeywordsMaterials scienceScanning electron microscopeMicrostructureAlloyField emission gunScanning transmission electron microscopyCharacterization (materials science)Transmission electron microscopyTexture (cosmology)MicroanalysisGrain boundaryLithium (medication)Field emission microscopyMetallurgyNanotechnologyDiffractionComposite materialOpticsChemistryPhysics

Abstract

fetched live from OpenAlex

Aluminum-lithium alloys are widespread in the aerospace industry. The new 2099 and 2199 alloys provide improved properties, but their microstructure and texture are not well known. This article describes how state-of-the-art field-emission scanning electron microscopy (FE-SEM) can contribute to the characterization of the 2099 aluminum-lithium alloy and metallic alloys in general. Investigations were carried out on bulk and thinned samples. Backscattered electron imaging at 3 kV and scanning transmission electron microscope imaging at 30 kV along with highly efficient microanalysis permitted correlation of experimental and expected structures. Although our results confirm previous studies, this work points out possible substitutions of Mg and Zn with Li, Al, and Cu in the T1 precipitates. Zinc and magnesium are also present in "rice grain"-shaped precipitates at the grain boundaries. The versatility of the FE-SEM is highlighted as it provides information in the macro- and microscales with relevant details. Its ability to probe the distribution of precipitates from nano- to microsizes throughout the matrix makes FE-SEM an essential technique for the characterization of metallic alloys.

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)0.001
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 score0.030
Threshold uncertainty score0.575

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.021
GPT teacher head0.309
Teacher spread0.288 · 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