Hyperspectral Imaging as a Tool to Study Optical Anisotropy in Lanthanide-Based Molecular Single Crystals
Bibliographic record
Abstract
In this work, we describe a protocol for a novel application of hyperspectral imaging (HSI) in the analysis of luminescent lanthanide (Ln3+)-based molecular single crystals. As representative example, we chose a single crystal of the heterodinuclear Ln-based complex [TbEu(bpm)(tfaa)6] (bpm=2,2’-bipyrimidine, tfaa– =1,1,1-trifluoroacetylacetonate) exhibiting bright visible emission under UV excitation. HSI is an emerging technique that combines 2-dimensional spatial imaging of a luminescent structure with spectral information from each pixel of the obtained image. Specifically, HSI on single crystals of the [Tb-Eu] complex provided local spectral information unveiling variation of the luminescence intensity at different points along the studied crystals. These changes were attributed to the optical anisotropy present in the crystal, which results from the different molecular packing of Ln3+ ions in each one of the directions of the crystal structure. The HSI herein described is an example of the suitability of such technique for spectro-spatial investigations of molecular materials. Yet, importantly, this protocol can be easily extended for other types of luminescent materials (such as micron-sized molecular crystals, inorganic microparticles, nanoparticles in biological tissues, or labelled cells, among others), opening many possibilities for deeper investigation of structure-property relationships. Ultimately, such investigations will provide knowledge to be leveraged into the engineering of advanced materials for a wide range of applications from bioimaging to technological applications, such as waveguides or optoelectronic devices.
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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 | 0.001 |
| 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".