Thermal Ammonia Decomposition for Hydrogen‐Rich Fuel Production and the Role of Waste Heat Recovery
Bibliographic record
Abstract
Hydrogen is an attractive future fuel with the potential to play a crucial role in reducing carbon dioxide emissions, but the major obstacles to implement hydrogen are associated with its storage, transportation, and safety. As a solution, ammonia has been recognized as a promising carbon‐free hydrogen carrier; however, due to the poor combustion performance of ammonia fuel, this review first outlines the significance of on‐site ammonia decomposition to generate CO x ‐free H 2 ‐rich fuel. Furthermore, to demonstrate the potential of this approach in different fields, the main focus of this review is on the pivotal role of integrating waste heat recovery and thermal ammonia decomposition across various industries including power plants, transportation, and industrial furnaces, enabling researchers to gain insights and benefit from the work of each other. As a means to enhance fuel saving and reduce greenhouse gas emissions, two significant methods including thermochemical recuperation and autothermal reforming are investigated considering the impact of several factors like exhaust gas species, temperature, and the performance parameters of the main fuel consumers. Finally, the paper provides vital recommendations for research directions in waste heat recovery‐based ammonia decomposition systems to promote sustainable and eco‐friendly solutions applicable to various industries. These include but are not limited to conducting life cycle analyses considering green ammonia, optimization of the independency level for the decomposition system, and integrating it with various components such as dual‐fuel engines, hydrogen purification, solar energy, and fuel cells.
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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 | 0.003 | 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) | 0.000 | 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".