Crystallographic and Compositional Dependence of Thermodynamic Stability of [Co(II), Cu(II), and Zn(II)] in 2-Methylimidazole-Containing Zeolitic Imidazolate Frameworks
Bibliographic record
Abstract
We report the first systematic study experimentally investigating the effect of changes to the divalent metal node on the thermodynamic stability of three-dimensional (3D) and two-dimensional (2D) zeolitic imidazolate frameworks (ZIFs) based on 2-methylimidazolate linkers. In particular, the comparison of enthalpies of formation for materials based on cobalt, copper, and zinc suggests that the use of nodes with larger ionic radius metals leads to the stabilization of the porous sodalite topology with respect to the corresponding higher-density diamondoid ( dia )-topology polymorphs. The stabilizing effect of metals is dependent on the framework topology and dimensionality. With previous works pointing to solvent-mediated transformation of 2D ZIF-L structures to their 3D analogues in the sodalite topology, thermodynamic measurements show that contrary to popular belief, the 2D frameworks are energetically stable, thus shedding light on the energetic landscape of these materials. Additionally, the calorimetric data confirm that a change in the dimensionality (3D → 2D) and the presence of structural water within the framework can stabilize structures by as much as 40 kJ·mol –1, making the formation of zinc-based ZIF-L material under such conditions thermodynamically preferred to the formation of both ZIF-8 and its dense, dia -topology polymorph.
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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 | 0.001 |
| 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".