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Record W3208506532 · doi:10.3390/coatings11111285

Friction and Wear Behaviors of Fe-19Cr-15Mn-0.66N Steel at High Temperature

2021· article· en· W3208506532 on OpenAlexaff
Shaolong Sheng, Huiling Zhou, Xiaojing Wang, Yanxin Qiao, Hongtao Yuan, Jian Chen, Lanlan Yang, Dongpeng Wang, Zhenguang Liu, Jiasheng Zou, Zhibin Zheng, Jingyong Li

Bibliographic record

VenueCoatings · 2021
Typearticle
Languageen
FieldMaterials Science
TopicMetal Alloys Wear and Properties
Canadian institutionsWestern University
Fundersnot available
KeywordsTribometerMaterials scienceScanning electron microscopeX-ray photoelectron spectroscopyAbrasiveOxideHardening (computing)Composite materialSofteningFriction coefficientMetallurgyTribologyWork hardeningPenetration (warfare)Layer (electronics)MicrostructureChemical engineering

Abstract

fetched live from OpenAlex

The friction and wear behaviors of Fe-19Cr-15Mn-0.66N steel were investigated under applied loads of 5 N and 15 N at the wear-testing temperatures of 300 °C and 500 °C using a ball-on-disc tribometer. The wear tracks were evaluated by scanning electron microscopy (SEM) and laser scanning confocal microscopy (LSCM) to reveal the variation in morphologies. Energy-dispersive X-ray spectroscopy (EDS) and X-ray photoelectron spectroscopy (XPS) were used to determine the components of oxide layers formed on wear surfaces. The results demonstrated that the oxide layers are favorable for obtaining a low friction coefficient under all conditions. The average friction coefficient decreased with increasing load at 300 °C, while it increased with the increase in applied load at 500 °C. At 300 °C, severe abrasive wear characterized by grooves resulted in a high friction coefficient with 5 N applied, whereas the formation of a denser oxide layer consisting of Cr2O3, FeCr2O4, Fe2O3, etc., and the increased hardness caused by work hardening led to a decrease in friction characterized by mild adhesive wear. At 500 °C, the transformation of Fe2O3 to the relatively softer Fe3O4 and the high production of lubricating Mn2O3 resulted in a minimum average friction coefficient (0.34) when 5 N was applied. However, the softening caused by high temperature weakened the hardening effect, and thus the friction coefficient increased with 15 N applied at 500 °C.

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 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 score0.006
Threshold uncertainty score0.824

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.013
GPT teacher head0.221
Teacher spread0.208 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations21
Published2021
Admission routes1
Has abstractyes

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