Carbon mineralization at low temperature: prospects and challenges
Bibliographic record
Abstract
Global warming and climate change has been linked to green house gas emissions into the atmosphere with an overwhelming scientific evidence supported by a variety of field measurements over a period of time. CO2 has been identified as a major contributor to global warming because of its high concentration in the atmosphere. The bulk of the recent CO2 increase in concentration in the atmosphere has been attributed to industrial activities, primarily power generation using fossil fuels. The international scientific community, through the IPCC, concluded that action needs to be taken urgently to mitigate carbon emissions before the point of no return in carbon dioxide concentration in the atmosphere is reached. In that respect, carbon capture and storage (CCS) was deemed to be the most effective solution to deal with large quantities of CO2 emitted. However, recent studies have shown that whilst this may be true where adequate geological storage site are available both in capacity and quality, many parts of the world simply are not blessed with this natural facility. It is imperative to seek alternatives to underground storage. This is even more important at the present time given that no real progress was made to manage carbon emissions on a large scale despite some CCS pilot studies conducted in Algeria, Norway, Canada, Australia and USA. Our work focused on an alternative to CCS, namely carbon mineralization. This is a special form of carbon conversion that does not have the same disadvantage of energy intensity as catalytic conversion of carbon back into fuel or hydrocarbon feedstock. Our approach is based on a relatively low temperature mineralization exploiting salt in reject brines, thus potentially solving two environmental problems in one single solution. Our work is both experimental and computational and has shown that good salt and carbon conversion at around 30 C is feasible. However, computational simulation work using Excel has shown that this method cannot convert all captured CO2 because of the potentially huge amounts to be captured. Nevertheless, this method is an alternative and helps solve two environmental problems in the Arabian Gulf.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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".