On the Formation of Intermetallics during the Furnace Brazing of Pure Titanium to 304 Stainless Steel Using Ag (30–50%)–Cu Filler Metals
Bibliographic record
Abstract
In the present work, the effect of brazing parameters on the properties of the brazed joint of pure titanium and 304 stainless steel (304SS) was investigated. Three different Ag–Cu filler metals were used, while the temperature and time of brazing were in the range of 800–950°C and 5–45 minutes, respectively. The microstructural observations show that, depending on the brazing conditions, different intermetallic phases such as CuTi2, CuTi, Cu3Ti4, and FeTi were formed at the phases interface. Based on the microstructural observations, a model was developed to characterize the formation of phases at the interfaces and brazed joint. The results show that, while some phases may form during the brazing process, the others can form during the cooling cycle after brazing. The results of the mechanical tests indicate that the microstructure of joint has a considerable effect on the shear strength of the brazed samples. It was observed that, when brittle intermetallic phases are finely dispersed at the interface, the strength was lower comparing to the conditions under which the intermetallic phases had a coarse dispersion in the brazed joint.
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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".