Food Contact Materials: An Analysis of Water Absorption in Nylon 12 3D Printed Parts Using SLS After VaporFuse Surface Treatment
Bibliographic record
Abstract
Abstract Selective laser sintering (SLS) is a typical method of 3D printing in an industrial environment. It is often used to print different materials, such as metals, ceramics, and plastics. Nylon 12 is the most common plastic and material processed by SLS technology. In the present paper, the water absorption and wettability of Nylon 12 in additive manufacturing (AM) products are explored. The research for obtaining inert, non-absorbent and non-corrosive surfaces, and globally more effective materials to reduce the proliferation of microorganisms is becoming a necessity for the development of novel food contact materials. Surface treatments aim at improving the porosity and general roughness of the material and are expected to improve its hydrophobicity. The wetting state between Nylon 12 and water was studied by measuring the contact angles as primary data. The measurement of absorbed water (ASTM 570) is thus used as an indicator of material quality to prevent bacterial growth and degradation of the material mechanical properties. Therefore, water absorption tests were performed with SLS printed plates with and without surface treatment. Plates with surface treatment showed a mass increase of 0.35 ± 0.04% while those without surface treatment showed a mass increase of 0.76 ± 0.08%.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 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".