Rapid, Mild, and Catalytic Synthesis of 2D and 3D COFs with Promising Supercapacitor Applications
Bibliographic record
Abstract
An approach based on Keggin heteropoly acids (HPAs) has been presented for the mild and fast synthesis of five different structures of imine and azine-linked two-dimensional (2D) and three-dimensional (3D) covalent organic frameworks (COFs). Traditionally, these crystalline materials have been synthesized via the Schiff base polycondensation reaction between different aldehydes and amines under harsh conditions and in the presence of acetic acid. Herein, two different Keggin-type heteropolyacids (HPAs) have been exploited as catalysts which are both Bronsted and Lewis acids to speed up the synthesis of 2D and 3D COFs and improve their materials quality. The catalyst led to the preparation of the imine and azine-linked COFs with high crystallinity and porosity under mild conditions and short reaction time. According to the results, the amine building blocks with two amine functional groups formed the COFs with higher crystallinity, porosity, and yield compared to amine with three functional groups and nonplanar structures. On this basis, under mild reaction conditions, a 2D COF named TAPA-TPT was successfully prepared with high crystallinity and good porosity. The developed TAPA-TPT COF exhibits a very good performance when used in supercapacitor applications. This COF showed excellent specific capacitance of 205 F g –1 at a current density of 0.5 A g –1, which is a very attractive value for supercapacitors. This study provides a synthetic approach that can lead to large-scale production of COF materials for energy harvesting.
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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 | 0.000 | 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 | 0.001 | 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 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".