Graphene Oxide−Periodic Mesoporous Silica Sandwich Nanocomposites with Vertically Oriented Channels
Bibliographic record
Abstract
This paper describes the synthesis and characterization of single-layer graphene oxide-periodic mesoporous silica sandwich nanocomposites. Through a comprehensive exploration of the synthesis conditions, it has proven possible to create the first example of a graphene oxide-periodic mesoporous silica nanocomposite in which hexagonal symmetry PMS film grows on both sides of the graphene oxide sheets with the mesoporous channels vertically aligned with respect to the graphene oxide surface. The formation of this novel architecture is found to be very sensitive to pH, the ratio of surfactant template to graphene oxide, the amount of silica precursor, and the temperature of the synthesis. On the basis of the collected data of a multi-technique analysis, it is proposed that the mode of formation of the nanocomposite involves the co-assembly of silicate-surfactant admicelles on opposite sides of graphene oxide platelets acting thereby as a template for growth of vertical mesopores off the platelet surface. These composites showed semiconductive behavior with electrical conductivity sensitively responding to analyte vapor exposure. The discovery of graphene oxide-periodic mesoporous silica sandwich nanocomposites will provide new opportunities for research that exploits the synergism of the graphene oxide and periodic mesoporous silica parts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".