The Impact of Different Alkali Metal Ions on Photoluminescence Properties of Ca<sub>10</sub>M(PO<sub>4</sub>)<sub>7</sub>:Eu<sup>2+</sup> (M: Li, Na, K)
Bibliographic record
Abstract
A series of novel luminescent materials Ca10M(PO4)7:Eu2+(M: Li, Na, K) were synthesized by the solid-state reaction. The previous literatures indicate that the doped different alkali metal ions can only lead to regular shift of the emission and excitation spectra. Howerver, in this paper, we found the result that these three kinds of phosphors showed huge differences between the emission spectra intensity as well as the positions of the excitation and emission spectra peaks. No any regulars can be found. In order to explore it, crystal structure, the performance of photoluminescence spectra and CIE coordinates have been systematically investigated and discussed. In Ca10Li (PO4)7, Ca10Na (PO4)7and Ca10K(PO4)7host lattices, the positions of the cations are different, leading to three different crystal structures. Besides, the coordination conditions of the luminescent centers Eu2+ions are also changed by the incorporation of the alkali metal ions. Thus the enormous disparity on the luminescence intensity as well as the excitation and emission peak positions may be ascribed to these three quite different crystal fields and different coordination numbers of the luminescent central ion in the Ca10M(PO4)7:Eu2+(M: Li, Na, K) phosphors.
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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".