Approaches for CO2 Capture and Sequestration Inspired by Biological Systems
Bibliographic record
Abstract
Abstract In this study, several process alternatives for the permanent sequestration of carbon dioxide (CO2) as solid carbonates are evaluated. Although the formation of mineral carbonates is thermodynamically favourable, it does not occur significantly due to kinetic limitations and the formation of products that hinder the evolution of the process. Several biological organisms, including corals, have developed different mechanisms for accelerating the process and managing undesirable products. In this report, we propose biomimicking approaches to precipitate solid carbonates while limiting the amount of energy required or using the produced by-products to generate valuable materials. A few processes alternatives are described and evaluated in this study. In all these explored cases CO2 mineralization requires divalent cations such as Ca++ or Mg++. These could be sourced from sea water or land based silicates containing these cations. Sea-water based source results in two attractive options, namely: 1. electrochemically assisted precipitation of carbonates with production of sales of Cl2 or HCl; 2. electrochemically assisted precipitation of carbonates and production of Vinyl Chloride Monomer (VCM) and polymerization into Polyvinyl Chloride (PVC), with sales of PVC; the land based source results in further in options 3, and 4: 3. electrochemically assisted precipitation of carbonates with in-situ mining of silicates; and 4. ammonia assisted precipitation of carbonates with in-situ mining of silicates. This study explores the technical feasibility of these options further.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".