Exploring the Synergistic Properties of ZnGa<sub>2</sub>O<sub>4</sub>:Cr<sup>3+</sup> and Calcium Phosphate: Longer-Lasting Persistent Luminescent Nanocomposite Using Adenosine Triphosphate As a Phosphorus Source
Bibliographic record
Abstract
Near-infrared persistent luminescence (PersL) nanoparticles are an emerging type of biomaterial that can continuously emit tissue-penetrable light. Surface functionalization techniques to improve the biological suitability of the phosphor often lead to a noticeable decrease in the luminescence capabilities of the material. In this work, Cr 3+ -doped ZnGa 2 O 4 (CZGO) nanoparticles are incorporated into an amorphous calcium phosphate (ACP) matrix to form a nanocomposite. Utilizing adenosine triphosphate (ATP) as an organic phosphorus source, the luminescence of the CZGO@ACP composite is much brighter and longer-lasting compared to bare CZGO. We found that these improved optical properties were present only when an organic phosphorus source (instead of the conventional inorganic phosphate salt, (NH 4 ) 2 HPO 4 ) was used as the ACP precursor. The chemical structure of the composite synthesized using ATP was comparatively studied with that synthesized using (NH 4 ) 2 HPO 4 . We use X-ray absorption fine structure to unravel the unique interaction between CZGO and ATP. Lastly, in vitro cytocompatibility and antibacterial tests were also performed to assess the biocompatibility of this nanocomposite.
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.
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) | 0.000 | 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 | 0.000 |
| 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 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".