Maximizing Porosity and Water Sorption in Covalent Organic Frameworks via β‐Ketoenamine Linkages
Bibliographic record
Abstract
Abstract Controlling the crystallinity and porosity of 2D covalent organic frameworks (2D COFs) is crucial for their applications in science and technology. Herein, the construction of 2D COFs, COF‐TP‐X, is reported using a multicomponent reaction strategy that introduces β‐ketoenamine linkages into isostructural imine‐linked COFs. This approach yields materials with exceptional crystallinity, stability, and tunable hydrophilicity. The integration of β‐ketoenamine linkages promotes intralayer planarity via NH⋯O hydrogen bonds and enhances π‐electronic conjugation within and between layers. By partially substituting (43 mol%) 1,3,5‐triformylbenzene with 1,3,5‐triformylphloroglucinol, an outstanding gravimetric surface area of 1,984 m2 g−1 and a pore volume of 0.8 cm3 g−1 are achieved—a remarkable two‐fold increase compared to mono‐linker counterparts. Moreover, COF‐TP‐X exhibits an exceptional water uptake capacity of 0.70 g g−1 (70 wt.%) and superior hydrolytic stability, as confirmed by over 200 cycles of water adsorption–desorption experiments. Furthermore, molecular simulations reveal the significant role of electrostatic interactions between β‐ketoenamine linkages in enhancing interlayer stacking and crystallinity. The findings provide key insights into COF design via a mixed‐linker strategy, representing a significant advancement in developing COFs with superior performance and paving the way for their industrial applications.
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 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 | 0.000 | 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) | 0.000 | 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 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".