Enhanced photocatalytic degradation of methylene blue dye using TiO<sub>2</sub> nanoparticles obtained via chemical and green synthesis: a comparative analysis
Bibliographic record
Abstract
Abstract The study compares TiO2 NPs synthesized via conventional chemical methods using Titanium Tetra Isopropoxide (TTIP) precursor versus an eco-friendly green synthesis approach using Moringa oleifera seed (MOS) extracts. Two standard fabrication routes-sol-gel and hydrothermal were employed for both chemical synthesis (CS) and green synthesis (GS) processes. The as-formed TiO2 nanoparticles from all four synthesis conditions (CS-sol gel, CS-hydrothermal, GS-sol gel, GS-hydrothermal) exhibited a spherical shape and pure rutile crystal structure with slight variations in mean diameter based on the synthesis technique. Optical absorptions showed bandgap energies ranging from 3.14–3.28 eV and 2.24–2.59 eV for CS- and GS-TiO2 systems respectively. The lower bandgap energy of green synthesized TiO2 suggests higher visible light absorption, confirmed through diffuse reflectance spectroscopy where GS-TiO2 NPs had higher base absorbance levels. The synthesized TiO2 NPs were employed as catalysts for methylene blue (MB) dye degradation under UV and sunlight irradiation. Intriguingly, the results indicated that the degradation of MB dye under sunlight irradiation demonstrated superior efficiency compared to UV irradiation. In conclusion, the green-synthesized TiO2 NPs showcased excellent optical properties and demonstrated enhanced photocatalytic performance in the degradation of MB dye, with an efficiency approaching 64 %.
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) | 0.001 | 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".