Novelty Au Nanoparticles with Different Nano Sizes as an Acidity Sensor
Bibliographic record
Abstract
The amazing wide range, applications of gold nanoparticles corresponding to excellent optical and electronic properties enhance utilization of Au NP as PH sensor. Gold nanoparticles were synthesized in simple and rapid Turkevich method to accomplish optical sensing technologies covalent or non-covalent, bonds formation causes, aggregation of the nanoparticles in the target substance. Au nanoparticles characterization was studied using XRD, UV-spectroscopy and SEM. XRD indicate polycrystalline. Nanoparticles with two different sizes according to reducing agent amount to obtain 20 30 nm. Optical energy gap was calculated for both particle size to find it (2.13) eV for 30nm particle size and (2.33) eV for 20nm.Scanning Electron Microscope showed spherical shape particles. PH test were performed to investigate efficiency of Au Np’s for PH sensor and that is found to be excellent results for both sizes with more efficiency for 30 nm due to its rough surface. Which is a fantastic tool and measurement device to test the pH of soil, food, and other puncture-worthy applications.
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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) | 0.000 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".