Laser sintering of PA12 particles studied by in-situ optical, thermal and X-ray characterization
Bibliographic record
Abstract
The microstructure of products manufactured by selective laser sintering (SLS) is known to be highly dependent on various process and material parameters. The latter thus also affect the final part properties. While most work has focused on ex-situ characterization of the printed parts, little is known about the time-dependent microstructure development during sintering. In this work, we present direct observations of the microstructural evolution during laser sintering of polyamide 12 (PA12) particle doublets by in-situ synchrotron wide angle X-ray diffraction (WAXD), using our in-house developed laser sintering setup. Simultaneously, the neck growth between the particles and the temperature are captured via optical and infrared microscopy. We show that isothermal crystallization experiments under quiescent conditions are not sufficient to describe crystallization in a non-isothermal process like SLS. The enhanced crystallization kinetics in small particles suggests that both temperature and flow play a role. This finding was corroborated by the critical Weissenberg numbers estimated from rheological reptation and Rouse time scales. Furthermore, a microstructure survey has been carried out by microtoming thin slices of the sintered doublets. Both optical and atomic force microscopy reveal significant differences in the crystalline structure of the laser-affected zone as compared to the un-sintered region.
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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".