Contribution of Different NbOx Species in the Hydrodeoxygenation of 2,5-Dimethyltetrahydrofuran to Hexane
Bibliographic record
Abstract
Hydrodeoxygenation (HDO) is significant for the upgrading of biomass, bio-oil, and biomass-derived compounds to fuels due to their abundant oxygen atoms. It is reported that Pd, Pt supported on Nb-based materials is excellent for the HDO reaction of raw biomass and biomass-derived compounds because NbOx species has a strong ability to activate C–O bonds in the previous studies. Here, we try to clarify which are the active NbOx centers, isolated, oligomer or low-coordinated species by using Pd/Nb-doped SBA-15 as the catalyst and 2,5-dimethyltetrahydrofuran (DMTHF) as the model compound. Nb-doped SBA-15 with tunable Nb content is prepared by glycerol-assisted one-pot hydrothermal method. These Nb-doped SBA-15 and Pd-loaded catalysts are characterized by XRD, N 2 sorption, TEM/SEM, diffuse reflectance ultraviolet–visible spectroscopy, and X-ray absorption near edge structure (XANES) spectroscopy. The performance of Pd/Nb-doped SBA-15 catalysts is found to be depended on the state of Nb species in SBA-15. The catalyst with low Nb loading possessing lower Nb coordination numbers can adsorb the oxygen atom of DMTHF and hence promote the cleavage of C–O bond of DMTHF. A higher turnover frequency of the catalysts based on Nb content and Lewis acid site can be obtained in catalysts with low Nb loading.
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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".