Synthesis of Hierarchical Porous Silica by Sol‐Gel of Sodium Silicate and Nanoemulsion Templating: Effective Combination Conditions
Bibliographic record
Abstract
Abstract Hierarchical porous materials have attracted a considerable attention owing to the increased interest in their applications. Hierarchical Porous Silica (HPS) was synthesized by combining the sol‐gel of sodium silicate (SS) and oil in water nanoemulsion (O/W‐NE) templating. The oil droplets of NE acted as pore forming agent and the sol‐gel built the silica framework. The O/W‐NE was prepared by a low energy method, i. e., the phase inversion composition (PIC) method. The influence of pH of SS and NE on HPS was studied. The volume of ammonia, used to induce gelling, was studied as a factor influencing the HPS. The calcined samples were characterized by scanning electron microscope (SEM), transmission electron microscope (TEM), FTIR, N 2 adsorption and small‐angel X‐ray scattering (SAXS). The results show that the microstructure is highly affected by pH and can be; macropores inserted in a dense matrix; a blend of a dense and a porous structure; or fully hierarchical porous silica. HPS has a specific surface area of 240 m 2 /g and a large pore volume (1.5 cm 3 /g) and a surface roughness of 2.95.
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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 | 0.000 | 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) | 0.000 | 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".