Cu–Ce Dual–Atom Sites Embedded in Zeolites Boost Resistance to Impurity Interference for Environmental Catalysis
Bibliographic record
Abstract
Abstract Biodiesel, a carbon‐neutral alternative to fossil fuels, plays a vital role in decarbonizing transportation, with global production exceeding 40 million tons annually. However, its widespread use introduces elevated phosphorus and metal cations into vehicle exhaust, severely deactivating Cu‐SSZ‐13 catalysts for NO X reduction through pore blockage, framework degradation, and Cu sites loss. We present a Cu–Ce dual‐atom catalyst embedded in SSZ‐13 that maintains high performance in ammonia‐selective catalytic reduction under phosphorus‐rich conditions. Ce species, precisely positioned in eight‐membered rings, displace P‐sensitive [ZCu 2+ OH] + sites, enriching the catalyst with P‐tolerant Z 2 Cu 2 ⁺ species in six‐membered rings. Concurrent Ce─P interactions restore the electronic environment of Cu sites, enhancing NH 3 /NO adsorption and redox cycling. This design sustains 90% NO X conversion and 100% N 2 selectivity at 210 °C, even after phosphorus exposure. The strategy is broadly applicable to impurity‐sensitive environmental reactions, including NH 3 oxidation and the coupled removal of NO X with VOCs, offering a practical pathway to durable, poison‐resistant catalysts for clean and sustainable mobility.
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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".