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Record W2099811340 · doi:10.24050/reia.v9i18.259

RESISTENCIA AL DESGASTE EROSIVO-CORROSIVO DE ACEROS AUSTENÍTICOS FERMANAL (EROSIVE-CORROSIVE WEAR RESISTANCE OF FERMANAL AUSTENITIC STEELS)

2013· article· es· W2099811340 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.

Bibliographic record

VenueEIA University Library (EIA University) · 2013
Typearticle
Languagees
FieldEngineering
TopicHigh-Temperature Coating Behaviors
Canadian institutionsSNC-Lavalin (Canada)
Fundersnot available
KeywordsMetallurgyCorrosionMaterials scienceAusteniteMicrostructure

Abstract

fetched live from OpenAlex

Se obtuvieron aleaciones austeníticas del sistema Fe-Mn-Al, en el intervalo Fe-(4,9~11,0 wt% de Al)- (17,49~34,3 wt% de Mn)-(0,43~1,25 wt% de C), las cuales fueron fundidas en un horno de inducción a partir de materiales de alta pureza. Las aleaciones se evaluaron con respecto a fenómenos de corrosión, erosión en medio húmedo y corrosión-erosión, a un ángulo de impacto de 90º. Para la evaluación de la corrosión se empleó una solución compuesta por 0,5 M de NaCl y partículas de sílice con tamaño entre 210 y 300 µm, con el fin de analizar el efecto del contenido de manganeso y aluminio en la resistencia a la erosión y a la corrosión-erosión de estas aleaciones. Para la caracterización de la respuesta corrosiva se usó la técnica con curvas de polarización potenciodin·micas y la extrapolación de Tafel, la caracterización microestructural mediante microscopia electrónica de barrido (MEB) y los productos de corrosión a través de difracción de rayos X (DRX). Abstract: We obtained austenitic alloys of the Fe-Mn-Al, Fe in the range (4.9~11.0 wt% Al) - (17.49~34.3 wt% Mn) - (0, 43 ~ 1.25 wt% C), which were melted in an induction furnace from high purity materials. The alloys were evaluated with respect to corrosion, wet erosion and corrosion-erosion at an impact angle of 90°. For the evaluation of corrosion a solution composed of 0.5 M NaCl and silica particles with size between 210 to 300 microns was used in order to analyze the effect of aluminum and manganese content in the resistance to erosion and corrosion-erosion of these alloys. To characterize the corrosion, response technique was used by potentiodynamic polarization curves and using the same technique as Tafel extrapolation, the microstructural characterization by scanning electron microscopy (SEM), and the composition of corrosion products were analyzed using diffraction of X-rays (XRD).

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.530
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0000.005
Open science0.0020.001
Research integrity0.0010.002
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 head0.006
GPT teacher head0.165
Teacher spread0.159 · 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