General Synthesis of Discrete Mesoporous Carbon Microspheres through a Confined Self-Assembly Process in Inverse Opals
Bibliographic record
Abstract
A general confined coassembly process has been demonstrated to produce discrete uniform mesoporous carbon microspheres with 0.8-1 μm particle size using 3-D-ordered macroporous silica as the template. The obtained mesoporous carbon microspheres (MC-MSs) have uniform and discrete spherical morphology, variable symmetry (hexagonal p6mm or cubic Im3m) of mesostructures, high specific surface areas (500-1100 m(2)/g), large pore volumes (0.6-2.0 cm(3)/g), and highly accessible large mesopores (7-10.3 nm). The particle size of the carbon microspheres can be easily tuned by simply using templates with different macropore sizes. It was found that the smaller MC-MSs (330 nm) with higher surface-to-volume ratio tend to shape into an integral monolithic MC-MS matrix and larger MC-MSs (>800 nm) with lower surface-to-volume ratio to discrete spherical morphology. This feature is attributed to the difference in shrinkage behavior of mesoporous carbon spheres confined in the macropores caused by the interaction between the silica wall and carbon microspheres. Adsorption experiments indicate that the cobalt-based nanoparticle-incorporated mesoporous carbon microspheres exhibit excellent size selectivity for protein adsorption in a complex solution and good magnetic separability for easy recycling.
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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) | 0.001 | 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 | 0.001 |
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".