Synthesis and Formation of Silica Aerogel Particles By a Novel Sol−Gel Route in Supercritical Carbon Dioxide
Bibliographic record
Abstract
A new method to obtain silica aerogel particles using acetic acid as the condensation agent for silicon alkoxides in supercritical carbon dioxide (scCO 2 ) is proposed. The objective of this study was to determine the mechanism of silica aerogel formation in scCO 2 using in situ analysis techniques. The synthesis and formation of silica aerogel particles was carried out by a modified sol−gel route, based on the hydroxylation and condensation of silicon alkoxides in scCO 2; both submicron and micron-size aerogel spheres were obtained. By means of in situ Fourier Transform infrared spectroscopy (FTIR), the activity of acetic, formic, benzoic, and chloroacetic acids were studied for the condensation of tetraethyl orthosilicate (TEOS). Formic and acetic acid gave slower rates than benzoic and chloroacetic acids. Increasing the concentration of acid and addition of extra water led to an acceleration of the reaction. The reactions were also studied as a function of temperature and pressure. Higher rates of reaction were obtained at higher temperatures and lower pressures. Results from particle formation studies indicated that by slowing the rate of reaction, precipitation and agglomeration of particles could be minimized. A submicron particle size range was obtained by depressurization of the sol−gel solution inside the reaction vessel, while the rapid expansion of supercritical solutions (RESS) process was found to yield particles in the size range of approximately 100 nm.
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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) | 0.000 | 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 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".