Development of Macroporous Titania Monoliths Using a Biocompatible Method. Part 1: Material Fabrication and Characterization
Bibliographic record
Abstract
Monolithic titania could offer significant potential as a support for bioaffinity chromatography because of its stability, unlike silica, to a wide range of pH conditions and its ability to selectively bind phosphorylated proteins and peptides. However, traditional routes to monolithic titania utilize harsh conditions incompatible with most biomolecules. To address this, titania monoliths were prepared in a biocompatible sol−gel process from Ti(O i Pr) 4 and glycerol. Varied porosities could be introduced by the additional use of high-molecular-weight poly(ethylene oxide) in the sol, which led to the formation of two phases prior to gelation. Morphologies, including bimodal meso- and macroporous structures, and the polymerization of either the dispersed or condensed phases could be controlled by the fraction and molecular weight of PEO in the sol. The roles of glycerol and PEO are to retard hydrolysis and condensation reactions so that phase separation of titanium-rich species precedes gelation processes. PEO also facilitates aggregation of growing TiO 2 oligomers and particles.
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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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".