Temperature-Dependent Fracture Toughness Evaluation of WC-10Co4Cr Coating/1018 Low Carbon Steel Substrate System
Bibliographic record
Abstract
The temperature-dependent fracture toughness of WC-10Co4Cr coating/1018 low carbon steel substrate, which is a brittle coating/ductile substrate system, is evaluated at microscopic level with two types of models developed in terms of the Arrhenius-type equation and rate controlling theory, utilizing indentation test data, in this research.One is based on the crystal structures of individual phases in the composite coating, the other considers the microcrack formation in the coating/substrate system under indentation loading.Using the crystal-structure-based model, the slip systems of the hard hexagonal -WC phase and soft FCC -Co phase are analyzed.The fracture toughness of the two-phase composite coating is obtained by integrating the fracture toughness of -WC phase and -Co phase using either the basic mixture method or the unconstrained mixture method.The estimated fracture toughness using this type of model is independent of indentation load.For the microcrack-formation-based models, numerous microcracks are generated from each corner of indentation impression and merge together to form radial cracks due to the tension of residual stresses in the coating/substrate system under indentation, and the radial cracks extend along the indentation diagonals under the residual stresses.The dislocation movement of atoms can be associated with the microcrack formation in the indentation process thus the fracture toughness of the composite coating/substrate system is evaluated.Due to the effect of ductile substrate on brittle coating, two approaches are used to investigate the indentation pressure imposed on the system, one expresses the indentation pressure as the applied load
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".