Recent Progress in MOF‐Aerogel Fabrication and Applications
Bibliographic record
Abstract
Recent advancements in metal-organic frameworks (MOFs) underscore their significant potential in chemical and materials research, owing to their remarkable properties and diverse structures. Despite challenges like intrinsic brittleness, powdered crystalline nature, and limited stability impeding direct applications, MOF-based aerogels have shown superior performance in various areas, particularly in water treatment and contaminant removal. This review highlights the latest progress in MOF-based aerogels, with a focus on hybrid systems incorporating materials like graphene, carbon nanotube, silica, and cellulose in MOF aerogels, which enhance their functional properties. The manifold advantages of MOF-based aerogels in energy storage, adsorption, and catalysis are discussed, with an emphasizing on their improved stability, processability, and ease of handling. This review aims to unlock the potential of MOF-based aerogels and their real-world applications. Aerogels are expected to reshape the technological landscape of MOFs through enhanced stability, adaptability, and efficiency.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".