Characteristics, emissions, capture, storage, and utilization of carbon dioxide: A comprehensive review of challenges and technologies for greenhouse gas mitigation
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
The capture, storage, and utilization of carbon dioxide (CO 2 ) are pivotal in combating climate change and mitigating greenhouse gas (GHG) emissions. This review offers a comprehensive and critically focused analysis of post-capture CO 2 handling methods, including storage, adsorption, and utilization, with a particular emphasis on emerging and innovative technologies. Distinctively, this study highlights advanced CO 2 conversion pathways—such as photocatalytic and photoelectrochemical reduction, membrane-based separations, and mineralization—by analyzing their mechanisms, energy demands, techno-economic feasibility, and integration potential with renewable energy sources. The review further explores the role of natural systems, especially microalgae and porous materials, in CO 2 bio-fixation and adsorption under industrial conditions. Unlike conventional reviews, this work provides an in-depth comparative assessment of major capture methods (e.g., cryogenic separation, chemical absorption, and mixed-matrix membranes), emphasizing recent advancements and material innovations that enhance selectivity, thermal stability, and operational efficiency. By integrating perspectives from material science, process engineering, and environmental policy, this review presents a novel synthesis of current challenges and future opportunities in circular carbon management. These insights aim to support the development of scalable, cost-effective, and sustainable CO 2 mitigation strategies for industrial deployment.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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