Bismuth Atom Tailoring of Indium Oxide Surface Frustrated Lewis Pairs Boosts Heterogeneous CO2 Photocatalytic Hydrogenation
Bibliographic record
Abstract
Abstract The surface frustrated Lewis pairs (SFLPs) on defect-laden metal oxides provide catalytic sites to activate H2 and CO2 molecules and enable efficient gas-phase CO2 photocatalysis. Lattice engineering of metal oxides provides a useful strategy to tailor the reactivity of SFLPs. Herein a one-step solvothermal synthesis is developed that enables isomorphic replacement of In3+ ions in UV-absorbing In2O3 by single-site Bi3+ ions to generate a new class of full-spectrum UV-Vis-NIR absorbing BixIn2-xO3 materials. Through compositional tuning, these materials prove to be three orders of magnitude more photoactive for the reverse water gas shift reaction (i.e., CO2 + H2 CO + H2O) than In2O3 itself, while also exhibiting notable photoactivity towards methanol production from carbon dioxide (i.e., CO2 + 3H2 CH3OH + H2O). The defective form of In2O3 containing oxygen vacancy sites can create SFLPs involving In3+ nearby the oxygen vacancy, which function as Lewis acidic sites, while lattice oxide O2- act as Lewis basic sites. In this study, it is discovered that the reactivity of these SFLPs can be further enhanced by single-site Bi3+ ion isomorphic substitution of Lewis acidic site In3+, thereby enhancing the propensity to activate CO2 molecules. In addition, the increased solar absorption efficiency and efficient charge separation and transfer of BixIn2-xO3 also contribute to the improved photocatalytic performance. These traits lead to enhanced binding and activation of CO2, exemplifying the opportunities that exist for atom-scale engineering in heterogeneous CO2 photocatalysis, another step towards the vision of the solar CO2 refinery.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".