Lanthanide-Doped Upconversion Nanoparticles: Exploring A Treasure Trove of NIR-Mediated Emerging Applications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Lanthanide-doped upconversion nanoparticles (UCNPs) possess the remarkable ability to convert multiple near-infrared (NIR) photons into higher energy ultraviolet-visible (UV-vis) photons, making them a prime candidate for several advanced applications within the realm of nanotechnology. Compared to traditional organic fluorophores and quantum dots (QDs), UCNPs possess narrower emission bands (fwhm of 10-50 nm), large anti-Stokes shifts, low toxicity, high chemical stability, and resistance to photobleaching and blinking. In addition, unlike UV-vis excitation, NIR excitation is nondestructive at lower power intensities and has high tissue penetration depths (up to 2 mm) with low autofluorescence and scattering. Together, these properties make UCNPs exceedingly favored for advanced bioanalytical and theranostic applications, where these systems have been well-explored. UCNPs are also well-suited for bioimaging, optically modulating chemistries, forensic science, and other state-of-the-art research applications. In this review, an up-to-date account of emerging applications in UCNP research, beyond bioanalytical and theranostics, are presented including optogenetics, super-resolution imaging, encoded barcodes, fingerprinting, NIR vision, UCNP-assisted photochemical manipulations, optical tweezers, 3D printing, lasing, NIR-II imaging, UCNP-molecule nanohybrids, and UCNP-based persistent luminescent nanocrystals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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 it