Carbonate Inhibition in Au-Cu/γ-Al2O3 Catalysts for CO Oxidation
Bibliographic record
Abstract
Incorporating Cu into gold-based catalysts effectively reduced nanoparticle sintering and free carbonate accumulation, promoting long-term preservation of catalytic surface area over time. This study explores the catalytic activity of monometallic Au and bimetallic AuCu catalysts with varying Au:Cu atomic ratios (1:0.5, 1:1, and 1:1.5) that were synthesized on γ-Al2O3 via sequential deposition–precipitation with urea. The catalysts were pretreated in either air or H2 and evaluated for CO oxidation activity and stability. A comprehensive characterization (EDS, BET, TEM, H2-TPR, O2-TPO, XPS, DRIFTS, and UV–Vis) was used to investigate particle size, metal oxidation states, and redox properties. Among all materials, the AuCu 1:1 catalyst exhibited the highest low-temperature CO conversion (>90% at 0 °C) and improved stability during 24 h tests, reflecting minimal nanoparticle sintering as confirmed by TEM analysis. In situ DRIFTS revealed that the presence of Cu+ and Cu2+ minimizes the accumulation of free carbonates (one of the main deactivation pathways in Au/γ-Al2O3) while promoting the formation of reactive intermediates that facilitate CO2 production. Notably, air pretreatment at moderate temperature proved as effective as H2 pretreatment in activating both monometallic and bimetallic catalysts. These findings highlight the role of Cu as a structural and electronic promoter of gold, offering practical guidelines for designing durable, cost-effective catalysts for low-temperature CO oxidation on non-reducible supports.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".