COF and MOF Hybrids: Advanced Materials for Wastewater Treatment
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 Recent advances in ordered porous materials, including metal‐organic (MOF) and covalent organic frameworks (COF), are set to revolutionize the strategies used for wastewater treatment. This is attributed to the large surface area, high crystallinity, structural tunability, thermal and chemical stability, and well‐defined structures of MOF and COF. Despite the distinctive properties exhibited by the single system (either MOF or COF), the combination of COF and MOF, as a hybrid construct, offers a remarkable opportunity to achieve superior functionality and performance. The favorable features of COF–MOF hybrids in different wastewater treatment sectors have opened new venues for effective environmental remediation. This review presents the state‐of‐the‐art design, synthesis, and application of COF–MOF hybrids. The synthesis principles, including MOF‐first, COF‐first, and post‐synthetic linkage of pre‐synthesized COFs and MOFs are summarized. The potential of these novel materials is evaluated by considering contaminant sensing, adsorptive removal, and catalytic photodegradation.The conclusion is drawn by assessing the existing hurdles and potential opportunities in the development of COF‐MOF hybrids as an innovative yet viable approach for addressing wastewater treatment.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it