The catalytic effect of boron substitution in MCM-41-type molecular sieves
Bibliographic record
Abstract
A series of B-MCM-41 samples has been synthesized with a wide range of boron content (SiO2:B2O3 ratio from 20 to 200), using ethyl silicate ester-40 (ES-40) as the silica source and characterized by XRD, BET, FT-IR, 11B-MAS NMR, SEM, pyridine adsorption, TPDA, and chemical analysis. The interplanar d100 spacing varies from 40 to 45 Å, depending on the Si:B ratio. On calcination, a significant amount of four-coordinated boron is converted into less stable three-coordinated boron, and some boron is removed from the framework. The degree of deboronation increases with an increase of boron content of the sample. The B substitution in the MCM-41 framework results in only weak and mild acid sites. The isomerization of 1-hexene is found to be influenced by the boron content in the framework. The isomerization leads to both a hydrogen shift and skeletal rearrangement. The selectivity ratios of cis-2-hexene to trans-2-hexene and 2-hexene to 3-hexene were found to decrease with an increase of temperature and a decrease of the SiO2:B2O3 ratio of the catalysts. Skeletal isomerization starts at 250 °C, forming secondary products, and increases with an increase of temperature and an increase of boron content of the catalysts. Key words: ES-40, B-MCM-41, deboronation, catalyst characterization, XRD, BET, FT-IR, 11B-MAS NMR, SEM, 1-hexene isomerization, 2-hexene.
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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 | 0.000 |
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".