Room Temperature Magnesite Precipitation
Bibliographic record
Abstract
Magnesite (MgCO 3 ) is one of the most stable sinks for carbon dioxide (CO 2 ) and is therefore of great interest for long-term carbon storage. Although magnesite is the thermodynamically stable form of magnesium carbonate, the kinetic inhibition of low-temperature precipitation has hindered the development of carbon sequestration strategies that can be economically conducted under ambient temperature. Here, we document the precipitation of magnesite from waters (magnesite saturation index = 1.45) in batch reactors at room temperature with the aid of carboxylated polystyrene microspheres over the course of 70 days. Microspheres provide surfaces with a high density of carboxyl groups that act to bind and dehydrate Mg 2+ ions in solution, thereby minimizing the kinetic barrier and facilitating magnesite formation. Magnesite crystals are observed on sphere surfaces and their organic matrixes. Mineral identification was confirmed by X-ray diffraction and selected area electron diffraction of a thin section obtained by focused ion beam milling. We demonstrate that kinetic barriers to magnesite formation can be overcome at ambient conditions. Incorporating surfaces with high carboxyl site densities into ex situ mineral carbonation processes and the use of such ligands for deep geologic CO 2 storage may offer novel and economically viable strategies for permanent carbon storage.
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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 | 0.000 | 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) | 0.002 | 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, 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".