Molding Properties of Inconel 718 Feedstocks Used in Low-Pressure Powder Injection Molding
Bibliographic record
Abstract
The impact of binders and temperature on the rheological properties of feedstocks used in low-pressure powder injection molding was investigated. Experiments were conducted on different feedstock formulations obtained by mixing Inconel 718 powder with wax-based binder systems. The shear rate sensitivity index and the activation energy were used to study the degree of dependence of shear rate and temperature on the viscosity of the feedstocks. The injection performance of feedstocks was then evaluated using an analytical moldability model. The results indicated that the viscosity profiles of feedstocks depend significantly on the binder constituents, and the secondary binder constituents play an important role in the rheological behavior (pseudoplastic or near-Newtonian) exhibited by the feedstock formulations. Viscosity values as low as 0.06 to 2.9 Pa·s were measured at high shear rates and high temperatures. The results indicate that a feedstock containing a surfactant agent exhibits the best moldability characteristics.
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 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 | 0.001 | 0.001 |
| 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".