Replication data for: "In Situ Monitoring of Mechanochemical Covalent Organic Framework Formation Reveals Templating Effect of Liquid Additive"
Bibliographic record
Abstract
Covalent organic frameworks (COFs) have emerged as a new class of molecularly precise, porous functional materials characterized by broad structural and chemical versatility, with a diverse range of applications. Despite their increasing popularity, fundamental aspects of COF formation are poorly understood, lacking profound experimental insights into their assembly. Here, we use a combination of in situ X-ray powder diffraction and Raman spectroscopy to elucidate the reaction mechanism of mechanochemical synthesis of imine COFs, leading to the observation of key reaction intermediates that offer direct experimental evidence of framework templating through liquid additives. Moreover, the solid-state catalyst scandium triflate is instrumental in directing the reaction kinetics and mechanism, yielding COFs with crystallinity and porosity on par with solvothermal products. This work provides the first experimental evidence of solvent-based COF templating, and is a significant advance in mechanistic understanding of mechanochemistry as a green route for COF synthesis. This dataset contains all data from analytical measurements including FT-IR spectra, raw XRD patterns, 1H and 13C ssNMR and lNMR spectra, N2 sorption isotherms, pore-size distributions, BET plots, calculated NMR chemical shifts, CIFs of the journal article mentioned under the related publication. Open *.cif and *.xyz files with a visualization software (see http://ww1.iucr.org/iucr-top/cif/), *.raw files with WinXPOW, *.sp files with PerkinElmer Spectrum software, *.mnova files with MestReNova, *.fq/.gr/iq/sq files with a text editor, .qps with ASiQwin, and *.pro files with TOPAS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.652 | 0.400 |
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".