Accelerating Mineral Carbonation Using Carbonic Anhydrase
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Carbonic anhydrase (CA) enzymes have gained considerable attention for their potential use in carbon dioxide (CO2) capture technologies because they are able to catalyze rapidly the interconversion of aqueous CO2 and bicarbonate. However, there are challenges for widespread implementation including the need to develop mineralization process routes for permanent carbon storage. Mineral carbonation of highly reactive feedstocks may be limited by the supply rate of CO2. This rate limitation can be directly addressed by incorporating enzyme-catalyzed CO2 hydration. This study examined the effects of bovine carbonic anhydrase (BCA) and CO2-rich gas streams on the carbonation rate of brucite [Mg(OH)2], a highly reactive mineral. Alkaline brucite slurries were amended with BCA and supplied with 10% CO2 gas while aqueous chemistry and solids were monitored throughout the experiments (hours to days). In comparison to controls, brucite carbonation using BCA was accelerated by up to 240%. Nesquehonite [MgCO3·3H2O] precipitation limited the accumulation of hydrated CO2 species, apparently preventing BCA from catalyzing the dehydration reaction. Geochemical models reproduce observed reaction progress in all experiments, revealing a linear correlation between CO2 uptake and carbonation rate. Data demonstrates that carbonation in BCA-amended reactors remained limited by CO2 supply, implying further acceleration is possible.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 it