The effects of deposited layer thickness on the material and geometrical properties of L-DED processed AISI D2 tool steel
Bibliographic record
Abstract
This research focuses on the influences of the deposited layer thickness upon the material characteristics, dimensional accuracy, and also the surface roughness of AISI D2 tool steel processed by laser directed energy deposition (L-DED); while layer thickness was varied, the remaining L-DED system parameters were retained at fixed values. After laser deposition, the D2 specimens were assessed without applying any subsequent machining steps. Sample dimensional accuracy was assessed through both manual measurement and computational methods, with the latter using confocal laser scanning microscopy (CLSM). It was shown that increasing the layer thickness decreases the extent of sample overbuilding. The use of lower layer thicknesses reduced the top surface roughness. However, a monotonic effect was not observed for side surface roughness in relation to the deposited layer thickness. In addition, the microstructures of the L-DED samples were evaluated using a combination of scanning electron microscopy (SEM) with associated energy dispersive X-ray spectroscopy (EDS), and X-ray diffraction (XRD). It is shown that a dendritic morphology is formed for the L-DED processed samples, with a columnar grain structure. Furthermore, the primary crystalline phase generated with the dendritic structure was found to be austenite. The indentation hardness values for the L-DED fabricated parts were noted to be larger for thinner deposited layer thicknesses.
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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".