Design Strategy for the Controlled Generation of Cationic Frameworks and Ensuing Anion-Exchange Capabilities
Bibliographic record
Abstract
Cationic frameworks are an emerging class of exceptional solid adsorbents capable of encapsulating highly toxic and persistent anionic pollutants. The controlled generation of cationic frameworks, however, lags behind the abundant design strategies devised to control the structures and topologies of neutral frameworks. In this regard, we report a rational approach that allows the conversion of the synthetic approach toward constructing a neutral framework into one allowing for the synthesis of a cationic one without incurring any changes to the overall topology or the selected metal ion. We demonstrate that the replacement of a functional group on an organic linker that promotes a similar coordination mode, but bearing one less negative charge, can yield the systematic generation of cationic frameworks. Moreover, we confirm the cationic nature of the metal-organic frameworks through preliminary anion-exchange experiments and propose a method to retain permanent porosity in cationic frameworks through the use of strongly binding anions. Altogether, these results show great promise for the construction of tunable nanoporous frameworks capable of carrying out anion-exchange processes.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".