Effect of Heat Treatment on the Microstructure and Mechanical Properties of 18Ni-300 Maraging Steel Produced by Additive–Subtractive Hybrid Manufacturing
Bibliographic record
Abstract
The present work investigates the effectiveness of two heat treatment cycles-solution treatment + aging (STA) and direct aging (DA)-on optimizing the microstructure and enhancing the mechanical properties of 18Ni-300 maraging steel (300 MS) produced by additive-subtractive hybrid manufacturing (ASHM). The STA treatment led to a fully martensitic microstructure with minor remnants of the cellular substructures associated with the solidification conditions in ASHM. DA resulted in some reverted austenite and partial dissolution of the cellular morphologies into shorter fragments. Despite the contrasting microstructures, the tensile strength and the macro- and micro-hardness were comparable between STA and DA conditions. By contrast, the potential for improving the ductility was higher with the DA heat treatment. This is attributed to the higher reverted austenite content in the samples treated by DA, i.e., up to a maximum of 13.4% compared to less than 3.0% in the STA samples. For the DA sample with the highest reverted austenite content of 13.4%, the highest local and global fracture strain values of 30.1 and 5.9 ± 0.6% were measured, while the respective values were 23.4 and 4.4 ± 0.1% for the corresponding STA sample. This work suggests that DA of 300 MS produced by ASHM is sufficient to achieve comparable hardness and tensile strength to STA, whilst maintaining reasonable ductility. Avoiding the solution treatment cycle, with its appreciably higher temperatures, could benefit the dimensional stability and surface quality that are important for ASHM of 300 MS parts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".