On the Nature of the Brønsted Acidic Groups on Native and Functionalized Mesoporous Siliceous SBA-15 as Studied by Benzylamine Adsorption from Solution
Bibliographic record
Abstract
The concentration and Brønsted acidity of surface silanol groups on mesoporous silica (SBA-15) has been studied by following the adsorption of benzylamine, BA, from water as a function of pH. The adsorbed amount of BA from water was compared to the maximum amount of BA that could be adsorbed from cyclohexane. Furthermore, the surface concentration and acidity of carboxylic acid functions on surface-functionalized SBA-15 was also studied, which allowed the relative surface concentration of remaining silanols to be obtained. Two types of silanols can be identified, where about 1/5 of the silanols have a pKa </= 2 and the remaining 4/5 of the silanols have a pKa of about 8.2. According to the literature, these two types of silanols can be identified as Q3 and Q2 silanols, respectively, of which the Q3 silanols are more acidic. For the surface-functionalized materials, pKa values close to their respective intrinsic values are found for the carboxylic acid functions. However, irrespective of the method of surface functionalization, 50% or more of the accessible surface groups are silanols. The results thus suggest that the effective charge density is largely controlled by the (de)protonation of the silanol groups even for surface-functionalized mesoporous silica, which render the surface chemistry of the surface-functionalized silicas to be radically different from what simple schematic representations would suggest. The results are suggested to be of importance for reaching a predictive level of understanding for the behavior of mesoporous silica in a range of applications, as many of the foreseen applications for mesoporous silica involves water as the medium.
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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 | 0.000 |
| 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) | 0.001 | 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".