Effect of B <sub>2</sub> O <sub>3</sub> /SiO <sub>2</sub> molar ratio and B <sub>2</sub> O <sub>3</sub> content on viscosity and structure of B <sub>2</sub> O <sub>3</sub> –SiO <sub>2</sub> –Al <sub>2</sub> O <sub>3</sub> –Na <sub>2</sub> O–TiO <sub>2</sub> glass lubricant
Bibliographic record
Abstract
Abstract Glass lubricant with a suitable viscosity is essential for producing high‐quality titanium products by the hot extrusion process. In this study, a novel lubricant of B 2 O 3 –SiO 2 –Al 2 O 3 –Na 2 O–TiO 2 (BSANT) glass was proposed, where the effects of B 2 O 3 /SiO 2 molar ratio (B/Si) and B 2 O 3 content on viscosity and structure were investigated. The results showed that the BSANT glass viscosity was gradually decreased, and the viscous activation energy was decreased by 20.24% with an increased B/Si ratio from 0.415 to 0.719. This was attributed to the decreased amounts of Q 3 , [BO 4 ], [AlO 4 ], and bridging oxygen (BO) in the network structure, which in turn resulted in a decreased network degree of polymerization. When B 2 O 3 content was increased from 18.70 to 33.12 mol.%, the melt viscosity value at 950 ℃ was decreased by 64.51%, and the viscous activation energy was reduced by 15.82%. Boron anomalies were also observed in glass melts with the B 2 O 3 content from 28.28 to 33.12 mol.%. The mechanisms responsible for this phenomenon were thoroughly discussed in the study. Additionally, a comparison and discussion of the applications of glass lubricants in metal hot working were presented. A glass lubricant with a specific composition was recommended for use in hot extrusion process within the temperature range of 950–1100°C due to its relatively stable viscosity properties.
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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 | 0.017 | 0.005 |
| Meta-epidemiology (narrow) | 0.016 | 0.015 |
| Meta-epidemiology (broad) | 0.020 | 0.014 |
| Bibliometrics | 0.006 | 0.016 |
| Science and technology studies | 0.010 | 0.016 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.014 | 0.010 |
| Research integrity | 0.007 | 0.019 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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; both teacher heads agree on what is shown here.
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".