Alternative catalytic strategies for direct CO2 valorization from flue gas emissions
Bibliographic record
Abstract
Abstract: The increase on the world’s population and energy demand has led to significant climate change as a result of the large emissions of greenhouse gases (GHG) from an energy matrix heavily relied on fossil-based fuels. In 2021, carbon dioxide (CO2) concentration in the atmosphere reached 414.7 ppm, with up to 90% of anthropogenic CO2 coming from the burning of fossil fuels. In the context of the Paris Agreement 2015, Canada has committed to a GHG emissions reduction target of 40–45% below 2005 levels by 2030, but this ambitious target will only be achieved through the development of novel alternative technologies that allow the transition to a low-carbon energy matrix. Flue gases (FG) are gaseous products of combustion carrying significant amounts of CO2 and other GHG emissions, such as nitrogen (NOx) and sulfur (SO2) oxides. The valorization of FG is an interesting pathway towards GHG reduction, since the recovered CO2 can be used to produce low-carbon energy vectors of industrial interest, avoiding further fossil exploitation. However, the valorization of FG still requires several FG cleaning and CO2 purification steps, which increase the costs associated with the process. The present project proposed investigating the feasibility of alternative catalytic strategies for the direct valorization of real FG streams as an option to traditional carbon capture and utilization (CCU) technologies that require CO2 purification. In the first part of this work, the feasibility of direct FG conversion was investigated with classical alumina-supported catalysts to produce syngas, an industrially relevant building block. The operating conditions were optimized to validate the process. In the second part of this work, hydroxyapatite (HAP) was proposed as an alternative catalyst support for CO2 methanation process, as an alternative for classical metal oxides. The process operating conditions were optimized, and the performance of the HAP-supported catalyst was validated at semi-pilot scale. Finally, in the third part of this work, the optimized HAP-supported nickel catalyst was pelletized by extrusion process and validated for direct FG methanation on lab- and semi-pilot scale. Overall, the results presented in this work can pave the way for the development of an efficient process for direct upgrading flue gas streams into industrially relevant low-carbon energy vectors.
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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 | 0.000 | 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) | 0.000 | 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".