Ultrahigh‐Selectivity Photocatalytic Upgrading of Bio‐Aldehydes/Diols to Monoalcohols Via In Situ Circumventing Coupling Co‐Products Over Janus Single‐Atom Pd/TiO <sub>2</sub>
Bibliographic record
Abstract
Abstract Photocatalytic transfer hydrogenation of biomass‐derived aldehydes to alcohols often results in unwanted coupling co‐products. Herein, an ultraselective hydrogen transfer system enabled by in situ oxidative C─C bond cleavage over a Janus single‐atom palladium on titanium dioxide (0.5Pd/TiO 2 ) photocatalyst is presented. The TiO 2 carrier promotes hydrogen‐donor activation, while Pd single atoms function as both electron and hydrogen transfer centers, enabling photocatalytic conversion of bio‐based furfural to furfuryl alcohol in >99% yield using ethanol as solvent/H‐donor at 25 °C. The control/in situ experiments and calculations reveal that ethanol on 0.5Pd/TiO 2 preferentially activates a co‐formed coupling by‐product to undergo C─C bond cleavage followed by proton‐coupled electron transfer, exclusively producing furfuryl alcohol. 0.5Pd/TiO 2 with good reusability is applicable to hydrogenative upgrading of various aldehydes/diols into corresponding monoalcohols with 81‒99% yields. This in situ Janus photocatalytic conversion strategy offers a new approach to eliminate side reactions in reductive upgrading of unsaturated organics/biomass with high selectivity.
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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".