Hydrothermal Synthesis and Characterization of Ni-Al Montmorillonite-Like Phyllosilicates
Bibliographic record
Abstract
This work describes the first hydrothermal synthesis in fluoride medium of Ni-Al montmorillonite-like phyllosilicates, in which the only metallic elements in the octahedral sheet are Ni and Al. X-ray diffraction, chemical analysis, thermogravimetric and differential thermal analysis, scanning electron microscopy and transmission electron microscopy confirm that the synthesized samples are montmorillonite-like phyllosilicates having the expected chemical composition. The specific surface areas of the samples are relatively large (>100 m2 g−1) compared to naturally occurring montmorillonites. 29Si and 27Al nuclear magnetic resonance (NMR) indicate substitutions of Al for Si in the tetrahedral sheet. 19F NMR and Ni K-edge extended X-ray absorption fine structure (EXAFS) local probes highlight a clustering of the metal elements and of the vacancies in the octahedral sheet of the samples. These Ni-Al phyllosilicates exhibit a higher local order than in previously synthesized Zn-Al phyllosilicates. Unlike natural montmorillonites, where the distribution of transition metal cations ensures a charge equilibrium allowing a stability of the framework, synthetic montmorillonites entail clustering and instability of the lattice when the content of divalent element in the octahedral sheet exceeds ca. 20%. Synthesis of Ni-Al montmorillonite-like phyllosilicates, was successfully achieved for the first time. These new synthetic materials may find potential applications as catalysts or as materials with magnetic, optical or staining properties.
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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".