Transient Liquid-Phase Sintering of Copper-Nickel Powders: In Situ Neutron Diffraction
Bibliographic record
Abstract
Transient liquid-phase sintering (TLPS) is a unique powder metallurgy (PM) processing technique typically used to form near-net-shape parts1 and more recently, as in this study, as a means of developing liquid-rich low-temperature solders2,3 and brazing filler materials4 that exhibit variable melting point (VMP) characteristics. In TLPS, starting mixtures normally consist of a low-melting-point additive powder and a higher-melting-point base-metal powder. The transient liquid phase that forms during heat-up past the additive’s melting point aids in rapid densification of the mixture.1,5–8 This liquid alloys with the basemetal powder during sintering and can lead to complete isothermal, or diffusional, solidification and a shift in melting point for the bulk powder mixture.4 In order to achieve the maximum melting-point shift for VMP brazing applications the isothermally solidified phase should have a completely homogenized composition. The consequence of diffusional solidification and incomplete homogenization was previously studied4 via differential scanning calorimetry (DSC). DSC results for nickel and copper powder mixtures (65 w/o Cu) showed quantitatively that a hold time of 150 min at 1,140°C enabled complete isothermal solidification of the copper-rich liquid during TLPS. Upon reheating, the TLP-sintered specimens exhibited a measurable melting-point increase, and an enhanced melting range due to incomplete homogenization of the isothermally solidified microstructure. Metallographic characterization of the post-sintered DSC specimens revealed that significant compositional gradients remained between the nickel-rich particle cores and the surrounding copper-rich solid-solution regions, even after holding for 150 min at 1,140°C.4
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) | 0.000 | 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".