Role of Alkali Earth Metals in Tailoring Ni/CeO2 system for efficient Ammonia Decomposition
Bibliographic record
Abstract
The global energy transition towards sustainable sources has highlighted hydrogen as a promising clean energy carrier.However, hydrogen storage and transportation challenges have led to the exploration of ammonia (NH₃) as an ideal hydrogen carrier, with its high hydrogen content (17.6 wt%) and ease of liquefaction.This study investigates the role of alkali earth metal promoters (Mg, Ca, Sr, Ba) in enhancing catalytic performance for ammonia decomposition using nickel-based catalysts supported on CeO₂.A series of catalysts were synthesized with 10 wt% nickel loading and 2 wt% promoter on CeO₂ support, evaluated over a temperature range of 300-600°C, 6000 h -1 GHSV at atmospheric pressure.The 10Ni-2Ba/CeO₂ catalyst demonstrated the highest ammonia decomposition activity, with the performance order:Characterization techniques revealed that Sr and Ba promoters substantially improved catalyst performance, with Ba being the most effective.The enhanced performance is attributed to Ba's interaction with CeO₂, which improves electronic properties and promotes ammonia decomposition through increased surface basicity and nickel reducibility.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".