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Record W4391450518 · doi:10.3390/met14020175

Effect of Alloying and Microalloying Elements on Carbides of High-Speed Steel: An Overview

2024· article· en· W4391450518 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

VenueMetals · 2024
Typearticle
Languageen
FieldMaterials Science
TopicMetal Alloys Wear and Properties
Canadian institutionsUniversity of Windsor
FundersNational Natural Science Foundation of China
KeywordsHigh-speed steelCarbideMetallurgyMaterials science

Abstract

fetched live from OpenAlex

In high-speed steel, carbides are essential phase constituents, which have a direct impact on engineering performance and qualities of high-speed steel. The formation, morphology, and distribution of carbides are dictated by alloying elements. In this paper, various types of carbides in high-speed steel are presented. The effects of different alloying elements such as C, W, Mo, Cr, and V on the formation of carbides in high-speed steel are discussed. Research progresses on carbide improvement by microalloying elements such as N, B, Mg, and rare earth (RE) elements are reviewed. It is reported that Cr promotes the precipitation of M2C, N enhances the formation of fibrous M2C, Mg effectively shatters the large-size carbide grid, Nb refines granular carbide MC, and rare earth elements encourage the formation of M6C, resulting in irregular M2C lamellae. The incorporation of microalloying elements improves the distribution and size of carbides and also refines the solidification structure of high-speed steel.

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)0.002
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 score0.012
Threshold uncertainty score0.374

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.051
GPT teacher head0.321
Teacher spread0.270 · 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