Crystalline Superlattices of Nanoscopic CdS Molecular Clusters: An X-ray Crystallography and<sup>111</sup>Cd SSNMR Spectroscopy Study
Bibliographic record
Abstract
Systematic 111 Cd solid-state (SS) NMR experiments were performed to correlate X-ray crystallographic data with SSNMR parameters for a set of CdS-based materials, varying from molecular crystals of small complexes [Cd(SPh) 4 ] 2– and [Cd 4 (SPh) 10 ] 2– to superlattices of large monodisperse clusters [Cd 54 S 32 (SPh) 48 ( dmf ) 4 ] 4– and 1.9 nm CdS. Methodical data analysis allowed for assigning individual resonances or resonance groups to particular types of cadmium sites residing in different chemical and/or crystallographic environments. For large CdS frameworks, 111 Cd resonances were found to form three groups. This result is noteworthy, since for related systems with size polydispersity and variations in composition, such as CdS or CdSe nanoparticles protected with an organic ligand shell, typically only two groups of resonances were observed. The generalized information obtained in this work can be used for the interpretation of 111/113 Cd SSNMR data for large CdS clusters and nanoparticles, for which crystal structure analysis remains inaccessible. Comparison of the powder X-ray diffraction patterns for freshly prepared and dried superlattices of large CdS clusters revealed an interesting superstructure rearrangement that was not observed for the smaller frameworks.
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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".