Molecular Tectonics. Porous Hydrogen-Bonded Networks Built from Derivatives of 2,2‘,7,7‘-Tetraphenyl-9,9‘-spirobi[9<i>H</i>-fluorene]
Bibliographic record
Abstract
The cruciform shape of spirobifluorene disfavors close molecular packing, and more complex derivatives with multiple sites of hydrogen bonding are known to associate to form highly porous networks with significant space for the inclusion of guests. In principle, the porosity can be increased by introducing spacers between the spirobifluorene core and the peripheral sites of association. To test this strategy, compounds 2 − 3 with multiple diaminotriazine groups attached to a tetraphenylspirobifluorene core were synthesized, and their behavior was compared with that of a model ( 4 ) lacking the phenyl spacers. As expected, extended spirobifluorenes 2 − 3 crystallized to produce open networks held together by hydrogen bonding of diaminotriazine groups; however, the porosities of these networks were lower (53% and 44%, respectively) than that of the network built from model 4 (60%). The decreased porosity arises largely because the added phenyl spacers change the relative contributions of hydrogen bonding and aromatic interactions to the overall lattice energy of the crystals. It becomes advantageous to optimize aromatic interactions at the expense of hydrogen bonds, and crystallization therefore favors networks that permit closer molecular packing.
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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".