Hydrogen‐Bonded Organic Frameworks Based on Endless‐Stacked Amides for Iodine Capture and Detection
Bibliographic record
Abstract
Abstract Recently, hydrogen‐bonded organic frameworks (HOFs) have emerged as a rapidly advancing class of porous materials with significant potential for applications in the absorption and detection of various chemicals. Here, the unique ability of amide groups to form endless‐stacking H‐bonds is implemented in the design of HOFs. Starting from benzene‐1,3,5‐tricarboxamide and amide‐containing tribenzocyclynes as foundational building blocks, a diverse range of HOFs featuring 1D, 2D, or 3D hydrogen‐bonded frameworks has been synthesized. Among those, all three porous HOFs, HOF_B‐Hex, HOF_T‐Pr and HOF_T‐Hex exhibited permanent porosity, thereby demonstrating the effectiveness of amide‐based HOFs strategy. Notably, HOF_T‐Hex stands out with a 42% pore volume and an impressive iodine capture efficiency of 6.4 g g−1. The iodine capture capacity is influenced not only by pore volume but also by the presence of accessible π‐electrons within the material (i.e., electrons not engaged in a π–π stacking interaction. Furthermore, some of these HOFs exhibited fluorescent responses to iodine positioning them as highly promising materials for both the capture and sensing of iodine.
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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 | 0.000 | 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".