Asymmetric Multipole Plasmon-Mediated Catalysis Shifts the Product Selectivity of CO<sub>2</sub> Photoreduction toward C<sub>2+</sub> Products
Bibliographic record
Abstract
Cu/TiO 2 is a well-known photocatalyst for the photocatalytic transformation of CO 2 into methane. The formation of C 2+ products such as ethane and ethanol rather than methane is more interesting due to their higher energy density and economic value, but the formation of C–C bonds is currently a major challenge in CO 2 photoreduction. In this context, we report the dominant formation of a C 2 product, namely, ethane, from the gas-phase photoreduction of CO 2 using TiO 2 nanotube arrays (TNTAs) decorated with large-sized (80–200 nm) Ag and Cu nanoparticles without the use of a sacrificial agent or hole scavenger. Isotope-labeled mass spectrometry was used to verify the origin and identity of the reaction products. Under 2 h AM1.5G 1-sun illumination, the total rate of hydrocarbon production (methane + ethane) was highest for AgCu-TNTA with a total C x H 2 x +2 rate of 23.88 μmol g –1 h –1 . Under identical conditions, the C x H 2 x +2 production rates for Ag-TNTA and Cu-TNTA were 6.54 and 1.39 μmol g –1 h –1, respectively. The ethane selectivity was the highest for AgCu-TNTA with 60.7%, while the ethane selectivity was found to be 15.9 and 10% for the Ag-TNTA and Cu-TNTA, respectively. Adjacent adsorption sites in our photocatalyst develop an asymmetric charge distribution due to quadrupole resonances in large metal nanoparticles and multipole resonances in Ag–Cu heterodimers. Such an asymmetric charge distribution decreases adsorbate–adsorbate repulsion and facilitates C–C coupling of reaction intermediates, which otherwise occurs poorly in TNTAs decorated with small metal nanoparticles.
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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".