The impacts of post‐processing treatments done under reactive and non‐reactive atmospheres on the densification of binder jetting parts
Bibliographic record
Abstract
Abstract At the intersection between chemical and materials engineering, binder jetting is an additive manufacturing technique that foregoes many of the limitations of the conventional metal 3D printing technique. Binder composition and thermal post‐processing influence final part quality. Herein, three different atmospheres, ranging from reactive (air) to non‐reactive (vacuum, argon), are studied to determine their effect on the quality of binder jetting printed parts after thermal treatments, namely debinding and sintering. These parts were printed using SS316L powder. Samples debound in air were negatively affected as they presented high porosities and low densities, averaging 6.80 (±0.4) g/cm 3 , whereas samples debound and sintered under vacuum demonstrated the best outcome with low porosities and high densities, averaging 7.65 (±0.1) g/cm 3 . This study highlights how oxide formation during debinding causes ferrite phase formation during sintering and how it affects atomic diffusion in the samples during both thermal treatments. This research also demonstrates the respective effects of these on the densification and porosity of 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".