Carbon mineralization with concurrent critical metal recovery from olivine
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
Carbon dioxide utilization for enhanced metal recovery (EMR) during mineralization has been recently developed as part of CCUS (carbon capture, utilization, and storage). This paper describes fundamental studies on integrating CO 2 mineralization and concurrent selective metal extraction from natural olivine. Nearly 90% of nickel and cobalt extraction and mineral carbonation efficiency are achieved in a highly selective, single-step process. Direct aqueous mineral carbonation releases Ni 2+ and Co 2+ into aqueous solution for subsequent recovery, while Mg 2+ and Fe 2+ simultaneously convert to stable mineral carbonates for permanent CO 2 storage. This integrated process can be completed in neutral aqueous solution. Introduction of a metal-complexing ligand during mineral carbonation aids the highly selective extraction of Ni and Co over Fe and Mg. The ligand must have higher stability for Ni-/Co- complex ions compared with the Fe(II)-/Mg- complex ions and divalent metal carbonates. This single-step process with a suitable metal-complexing ligand is robust and utilizes carbonation processes under various kinetic regimes. This fundamental study provides a framework for further development and successful application of direct aqueous mineral carbonation with concurrent EMR. The enhanced metal extraction and CO 2 mineralization process may have implications for the clean energy transition, CO 2 storage and utilization, and development of new critical metal resources.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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