Gum Arabic-stabilized upconverting nanoparticles for printing applications
Bibliographic record
Abstract
Upconverting nanoparticles (UCNPs) have been proposed for a variety of applications ranging from biomedical probes to luminescent sensors and security tags. Yet, bringing UCNPs into real-life, technologically relevant products requires implementation into industry-friendly processes. The need for stable dispersions, clean films or dry powders challenges users who look for a way to use UCNPs. In this work, an ink formulation was developed that offers a straightforward way to print UCNPs on glass and metallic substrates. The use of Gum Arabic as biocompatible emulsifier allowed to implement the NaGdF4:Er,Yb/NaGdF4 core/shell UCNPs into water-based ink formulations without the need of complex surface chemistry. The formulation, based on water, glycerin, and propanediol, exhibited good stability and applicability for printing with a commercial aerosol jet printer. Bright upconversion emission was retained upon printing, and the obtained UCNP films were used in proof-of-concept luminescent thermal sensing.
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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) | 0.001 | 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) | 0.002 | 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".