Ordered Meso‐ and Macroporous Binary and Mixed Metal Oxides
Bibliographic record
Abstract
Abstract A critical review is provided of the principles guiding the synthesis of meso‐ and macroporous metal oxides on multiple length scales in the presence of surfactant mesophases and colloidal arrays of monodisperse spheres, and correlations between the synthesis conditions and the properties of the resulting meso‐ and macroporous oxides, such as thermal stability, pore structure, elemental and nanophase compositions of the inorganic wall, etc. The thermal stability of mesostructured metal‐oxide phases, in particular, is discussed in terms of charge‐matching at the organic–inorganic interface, the strength of interactions between inorganic species and surfactant headgroups, the flexibility of the M–O–M bond angles in the constituent metal oxides, the Tammann temperature of the metal oxide, and the occurrence of redox reactions in the metal‐oxide wall. The ordered meso‐ and macroporous transition‐metal‐oxide phases are highly promising for a range of potential applications in separations, chemical sensing, heterogeneous catalysis, microelectronics, and photonics as, respectively, insulating layers of low‐dielectric‐constant and photonic‐bandgap materials. Furthermore, the functionalization of the internal pore surfaces in these materials and deposition of functional nanoparticles within the pores offer numerous new possibilities for molecular engineering of catalytic and other advanced nanostructured materials displaying quantum‐confinement effects. The emerging catalytic applications of these novel metal‐oxide phases are discussed in particular detail. (© Wiley‐VCH Verlag GmbH & Co. KGaA, 69451 Weinheim, Germany, 2005)
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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".