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Record W1545000346 · doi:10.4236/msa.2011.25057

Electrochemical Behavior of Nanocrystalline Fe<sub>88</sub>Si<sub>12</sub> Alloy in 3.5% NaCl Solution

2011· article· en· W1545000346 on OpenAlex
Licai Fu, Jun Yang, Qinling Bi, Weimin Liu

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.

Bibliographic record

VenueMaterials Sciences and Applications · 2011
Typearticle
Languageen
FieldMaterials Science
TopicNanoporous metals and alloys
Canadian institutionsUniversity of Alberta
FundersNational Natural Science Foundation of China
KeywordsNanocrystalline materialMaterials scienceCorrosionAlloyMicrostructureGrain sizeElectrochemistryGrain boundaryMetallurgyNanocrystalNanotechnologyPhysical chemistryElectrodeChemistry

Abstract

fetched live from OpenAlex

Influence of microstructure on electrochemical behavior of nanocrystalline Fe88Si12 alloy has been investigated in 3.5 wt% NaCl solution. The results show that FFe88Si12 alloy with optimal corrosion resistance is composite of ordered Fe3Si and disordered Fe(Si) phases and grain size of 40 nm. Because the ordered Fe3Si structure is beneficial to form SiO2 film, which possesses good corrosion resistance compared with the Fe2O3 film from disordered Fe(Si). Moreover, although the decreased grain size is conducive to form preservative, as the grain size decreases to 10 nm, the grain boundary increases to above 30 vol%, which is the active sites for corrosion attack.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
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 score0.162
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.003
Science and technology studies0.0020.003
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.043
GPT teacher head0.275
Teacher spread0.232 · 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