Inside-Out/Outside-In Tunability in Nanosized Lanthanide-Based Molecular Cluster-Aggregates: Modulating the Luminescence Thermometry Performance via Composition Control
Bibliographic record
Abstract
Modulating the optical property of a material via structural modification is a powerful tool for obtaining the desired optical output. If a material can be tuned inside (core) and outside (outer shell), then the degree of control is greater toward application. Herein, we present a lanthanide-based nanosized molecular cluster aggregate (MCA) that allows fine-tuning of the inner core via composition control akin to nanoparticles. At the same time, the tunable outer shell enables light-harvesting properties similar to molecular systems. As such {Eu4Tb16}, {Eu3Gd5Tb12}, {Eu2Gd10Tb8}, and {Eu1Gd15Tb4} compositions were synthesized, and their photophysical properties were investigated in solution and in the solid state. Controlling the composition and spacing of the emitter ions with the optically silent GdIII ions results in a decrease in the TbIII → EuIII energy-transfer process efficiency. Consequently, ratiometric luminescence thermometry performance is fine-tuned to reach a maximum relative sensitivity of 4.17% °C–1 at 36 °C for the {Eu4Tb16} MCA. This study demonstrates that the optical properties are intrinsic to individual MCA species rather than a collective intermolecular effect. The color change observed close to room temperature for {Eu2Gd10Tb8} suggests potential applications such as multistage anticounterfeiting technology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".