Molecular Tectonics. Porous Hydrogen-Bonded Networks Built from Derivatives of 9,9‘-Spirobifluorene
Bibliographic record
Abstract
Molecules with multiple sites that induce strong directional association tend to form open networks with significant volumes available for the inclusion of guests. Such molecules can be conveniently synthesized by grafting diverse sticky sites onto geometrically suitable cores. The characteristic inability of 9,9'-spirobifluorene to form close-packed crystals suggests that it should serve as a particularly effective core for the elaboration of molecules designed to form highly porous networks. To test this hypothesis, various new tetrasubstituted 9,9'-spirobifluorenes with hydrogen-bonding sites at the 3,3',6,6'-positions or 2,2',7,7'-positions were synthesized by multistep routes. Four of these compounds were crystallized, and their structures were determined by X-ray crystallography. In all cases, the compounds form extensively hydrogen-bonded networks with high porosity. In particular, 43% of the volume of crystals of 3,3',6,6'-tetrahydroxy-9,9'-spirobifluorene (28) is available for the inclusion of guests, whereas the porosity is only 28% in crystals of tetrakis(4-hydroxyphenyl)methane, a close model that lacks the spirobifluorene core. Similarly, the porosities found in crystals of 2,2',7,7'-tetra(acetamido)-9,9'-spirobifluorene (33) and 2,2',7,7'-tetrasubstituted tetrakis(diaminotriazine) 39 are 33% and 60%, respectively. Moreover, the porosity of crystals of 2,2',7,7'-tetrasubstituted tetrakis(triaminotriazine) 40 is 75%, the highest value yet observed in crystals built from small molecules. These observations demonstrate that a particularly effective strategy for engineering molecules able to form highly porous networks is to graft multiple sticky sites onto spirobifluorenes or other cores intrinsically resistant to close 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".