Surface Properties of Molds for Powder Injection Molding and Their Effect on Feedstock Moldability and Mold Adhesion
Bibliographic record
Abstract
Abstract The surface energy of various mold materials for low-pressure powder injection molding was evaluated using values of contact angles (Owens-Wendt method), and correlated with the feedstock moldability and mold adhesion. The surface tension of the binder used to formulate a metallic-based feedstock was also measured in the molten state at a typical injection temperature using the pendant drop technique. Real-scale injection tests were performed into metallic and polymeric mold cavities to assess the feedstock moldability and its adhesion with the mold surfaces that were compared with theoretical predictions obtained from the surface energies values. The results confirmed that the adhesion was significantly affected by the interfacial energy between the mold and the binder - in this case, the metallic mold exhibited low adhesion as compared to the polymeric mold. It was finally demonstrated that the adhesion phenomenon is only related to the surface properties of the mold (i.e., they are not related to the solidification rate) - in this case, a gold-coated polymeric mold produced the moldability of a polymeric mold and the adhesion properties of a metallic mold, which translated into a high moldability potential, with no resulting adhesion of the feedstock with the mold.
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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 | 0.001 |
| 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".