MULTI-PHASE NANOSTRUCTURED 60Si2Mn DISC SPRING BY A NOVEL AUSTEMPERING PROCESS
Bibliographic record
Abstract
A disc spring, also known as a Belleville spring, is a conical shell which can be loaded along its axis either statically or dynamically.It can generate a high force in a very short spring length with minimal movement when compressed.A novel multi-step austempering heat treatment process is developed to improve both the hardness and strength of a conventional 60Si2Mn disc spring.In this case, the disc spring is austenitized at 900°C for 0.5 h, control-quenched to a temperature below Ms (the starting temperature of martensite transformation) for a very short time, subsequently heated to the Ms point and holding for a specific time, and finally air cooled to the room temperature.It is found that the resulting multiphase microstructure consists mainly of prior lenticular martensite formed during controlled quenching (PM), needle bainitic ferrite (BF), and high carbon enriched retained austenite (RA).Further observation shows that a nanostructured (BF+RA)nano phase including lath BF and film RA with a width of about 100 nm nucleates around the PM.Such a microstructure results in uniform compression behavior, and significantly higher strength and hardness than for a conventional 60Si2Mn disc spring.This controlled multi-step austempering process is a promising solution for enhancing the disc spring properties for those applications involving higher loading and fatigue conditions.
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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 | 0.000 | 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".