Process for Converting Carbon Dioxide to Graphite Using Active Metal Liquid and Its Application for Green Hydrogen Production via Methane-Steam-Reforming Reaction
Bibliographic record
Abstract
About 60% of global warming effects are attributed to carbon dioxide emission. The global annual carbon dioxide discharge is around 40 billion tons per year, primarily from burning fossil fuels. Any methods for carbon dioxide capture and reduction could not be a thorough approach if carbon dioxide is not converted to a stable and useful substance. To deal with the enormous amount of discharged carbon dioxide, a new process to split carbon dioxide and convert it to graphite using active metal liquid such as liquid magnesium is presented. As the graphite produced is a critical mineral/material with extensive applications and demands (e.g., as raw material of graphene and diamond production), this carbon dioxide reduction technology can be economically viable. Combined with this carbon dioxide conversion method, the steam-methane-reforming (SMR) process, which accounts for 95% hydrogen production, will become a greener or totally green hydrogen production technology if clean energy is employed to maintain and initiate the processes involved. The entire process is commercializable for hydrogen production, carbon dioxide reduction/carbon fixing, and graphite production with the combination of chemical engineering and metallurgy technologies. There are no technological barriers for the presented process as all the chemical engineering and metallurgy sub-processes involved are proven and feasible. If hydrogen is adopted as the major fuel in the future, the problems arisen from carbon dioxide emission could be largely solved.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".