Emerging Trends in Sustainable CO<sub>2</sub>‐Management Materials
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
Abstract With the rising level of atmospheric CO 2 worsening climate change, a promising global movement toward carbon neutrality is forming. Sustainable CO 2 management based on carbon capture and utilization (CCU) has garnered considerable interest due to its critical role in resolving emission‐control and energy‐supply challenges. Here, a comprehensive review is presented that summarizes the state‐of‐the‐art progress in developing promising materials for sustainable CO 2 management in terms of not only capture, catalytic conversion (thermochemistry, electrochemistry, photochemistry, and possible combinations), and direct utilization, but also emerging integrated capture and in situ conversion as well as artificial‐intelligence‐driven smart material study. In particular, insights that span multiple scopes of material research are offered, ranging from mechanistic comprehension of reactions, rational design and precise manipulation of key materials (e.g., carbon nanomaterials, metal–organic frameworks, covalent organic frameworks, zeolites, ionic liquids), to industrial implementation. This review concludes with a summary and new perspectives, especially from multiple aspects of society, which summarizes major difficulties and future potential for implementing advanced materials and technologies in sustainable CO 2 management. This work may serve as a guideline and road map for developing CCU material systems, benefiting both scientists and engineers working in this growing and potentially game‐changing area.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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