Metal Halide Perovskite and Perovskite-like Materials through the Lens of Ultra-wideline <sup>35/37</sup> Cl NMR Spectroscopy
Bibliographic record
Abstract
With their exceptional optoelectronic features, metal halide perovskites (MHPs) are pushing the next wave of energy-related materials research. Heretofore, most solid-state nuclear magnetic resonance (NMR) investigations have focused on readily accessible nuclei. In contrast, the halogen environments have been avoided due to their challenging quadrupolar nature. Here, we report a rapid 35/37 Cl NMR strategy for MHPs, halide double perovskites (HDPs), and perovskite-inspired (PI) materials embracing ultra-wideline acquisition approaches at moderate and ultrahigh magnetic fields. The observed quadrupolar NMR parameters ( C Q and η), supported by GIPAW–DFT computations, provide an analytical fingerprint revealing distinct features for chemically unique Cl environments sensitive to ion mixing, dimensionality, cell volume, and Cl coordinating polyhedra. Moreover, we report resolution between two nearly identical and two distinct Cl environments of 3D and 2D Cs-based lead halide perovskites, respectively. These results reveal a strategy for a routine and robust spectroscopic approach to analyze local Cl chemical environments in metal halide perovskites that can be extended broadly to other halogen-containing semiconductors.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".