Bibliographic record
Abstract
The remarkable optomagnetic properties of the rare-earths (RE) make RE-based materials ideal for biomedical applications, including diagnostic (e.g., imaging, nanothermometry) and therapeutic (e.g., drug delivery, photodynamic therapy) approaches. This is due the unique electronic properties of the f-elements allowing for upconversion and near-infrared emission under near-infrared excitation as well as high magnetic moments. Yet, challenges remain; low emission intensity and efficiency of small nanoparticles (NPs), and reliable, fast synthesis routes. As material chemists, we tackle these challenges with new designs of RE-NPs by chemically controlled synthesis, application-oriented surface chemistry, and understanding of structure-property-relationships. Sodium rare-earth fluorides (NaREF 4 ) are our favorite materials, and we developed a fast and reliable microwave-assisted synthesis approach allowing crystalline phase and size control in the sub 15nm realm. Such control is crucial for the understanding of fundamental structure-property relationships and to optimize their optical and magnetic properties, when aiming for the design of next-generation optical probes or contrast agents for magnetic resonance imaging. For instance, NaGdF 4 NPs are gaining interest as alternative MRI contrast agent, while co-doping with RE 3+ ions renders them excellent candidates for photoluminescent optical probes. The hexagonal crystalline phase of NaGdF 4 is known as the more efficient host material for upconversion emission, yet interestingly, it was found that its cubic counterpart shows superior performance as MRI contrast agent. Having a fast and reliable synthesis route towards NaREF 4 NPs on hand, we now explore various nanoparticle architectures and compositions with the goal to optimize their optomagnetic properties, ultimately resulting in the design of biocompatible multimodal bioprobes. This presentation will shed light on recent results and remaining challenges in the field of RE-based nanostructures with respect to their microwave-assisted synthesis as well as structural and optomagnetic properties, seeking biomedical application, while also touching on hyperspectral imaging as an emerging analytical tool offering spatio-spectral information about RE-based materials.
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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 | 0.000 | 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 | 0.001 | 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) | 0.002 | 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".