<i>De Novo</i> Structure Determination of Covalent Organic Frameworks by NMR Crystallography
Bibliographic record
Abstract
Further advancement in the research area of covalent organic frameworks (COFs) is in urgent need of structural information with high accuracy. The bottleneck in characterization is the lack of effective strategies to resolve the complex features (e.g., the stacking sequence) of hierarchical structures. Herein, we establish an NMR crystallographic protocol to systematically and precisely measure multinuclear distances through advanced dipolar recoupling techniques, such as rotational echo double resonance (REDOR), double quantum–single quantum (DQ–SQ), and rotational echo adiabatic passage double resonance (REAPDOR) experiments. For the first time, we obtained the atomic distances of 1 H– 1 H, 1 H– 19 F, and 13 C– 19 F within the monolayer, two adjacent layers, and three consecutive layers of a two-dimensional (2D) COF, TPPA-F 4 . Based on these key parameters with an accuracy of 0.10 Å, the structural features of TPPA-F 4 COF, including the covalent connection, intralayer conformation, interlayer distance, the direction and distances of the layer offsets, and stacking mode, have been de novo determined in detail. Moreover, the generality of this NMR crystallographic approach was verified by solving the crystal structure of a selective deuterium-labeled TPPA- d 4 COF via 1 H– 2 H distance measurements. We expect that the NMR crystallographic protocol paves new ways not only for the structural determination of complex 3D COFs but also for the investigation of the crystallization process and dynamic behaviors of COFs with high spatiotemporal resolution. In addition, the selective deuteration strategy developed herein enabled the first NMR measurement of 1 H– 2 H distances in materials research, which may find broad applications for the characterization of weak interactions in solids.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".