Aggregation‐Induced Quenching of Carbon Dots for Detection of Nitric oxide
Bibliographic record
Abstract
Abstract This study reports the synthesis of three types of carbon dots (CDs) prepared using citric acid as a carbon source and three different biomolecules (L‐serine, L‐threonine, and adenine) individually as an amine source. The obtained nanomaterials were characterized by powder XRD, TEM, FTIR, 13 C NMR, distortionless enhancement by polarization transfer using a 135‐degree decoupler pulse (DEPT 135), dynamic light scattering (DLS), and Small‐Angle X‐ray Scattering (SAXS) techniques. After ensuring the formation of desired structures, prepared CDs were used for exploring the detection capabilities of different reactive nitrogen species and reactive oxygen species. Following the screening of their detection capabilities specifically for nitric oxide, different sensing parameters viz the limit of detection, quenching constant, and interferences were evaluated. Among the synthesized CDs, the lowest detection limit of 0.1 μM was determined for the serine‐derived dots while 0.12 and 0.19 μM was obtained for adenine and threonine‐derived dots, respectively. Eventually, a possible sensing mechanism for the detection of NO by the prepared nanomaterials is proposed.
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 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 | 0.000 | 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 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".