Recent Advances in Adsorption and Separation of Methane and Carbon Dioxide Greenhouse Gases Using Metal–Organic Framework-Based Composites
Bibliographic record
Abstract
The development of materials and methods efficient for carbon capturing, methane storage, and selective separation of CO2 and CH4 from gas mixtures is a crucial approach to addressing the problems of these two greenhouse gases. In this regard, metal organic framework (MOF)-based composite materials are recognized as a promising class of materials, which could combine the advantages of MOFs and the other constituents to reduce their current drawbacks in the adsorption/separation systems. In this context, a series of MOF composites recently developed for CO2 and CH4 adsorption and their selective separation from gas mixtures are presented and discussed: MOF/carbon-based materials, MOF/Si-based composites, MOF mixed-matrix membranes, MOF/MOF, and MOF/metal oxide structures. Here, with an emphasis on the most recent signs of progress, we hope to shed a light on the MOF composites and assist future research to promote the performance of current composites and develop new MOF hybrid structures considering the proposed challenges.
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.
How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".