The Fluoride Host: Nucleation, Growth, and Upconversion of Lanthanide‐Doped Nanoparticles
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
The rapid ascent of nanoscience has garnered significant attention in recent years. Much of the interest generated has dealt with the integration of nanoparticles in various applications ranging from automotive and textiles to bioimaging and nanomedicine. In order for the realization of this potential, their synthesis and chemistry need to be thoroughly understood. One particularly interesting class of nanoparticles comprises a lanthanide‐doped inorganic matrix. Due to their physicochemical and optical properties, these lanthanide‐doped nanoparticles are undergoing widespread investigation in many fields, particularly for in vitro and in vivo imaging, as well as theranostics. They offer significant advantages in biological applications, particularly the extension of the system applicability to deep tissue regions of the body, a reduced scattering of the excitation wavelength, reduction of autofluorescence, and decrease in thermal loading and photodamage to the system under study. Specifically, lanthanide‐doped fluoride hosts are being propelled to the forefront of the current research efforts as they offer several advantages relative to other studied upconverting host materials. This review will take an in‐depth look at lanthanide‐doped upconverting fluoride nanoparticles with a particular emphasis on the synthesis, nucleation, and growth mechanisms and, finally, the potential to tailor particle properties.
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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 it