Unraveling the Photocatalytic Performance of La<sub>2</sub>O<sub>3</sub> Nanoparticles for the Degradation of Six Organic Dyes
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Lanthanum oxide (La 2 O 3 ) nanoparticles stand out as promising photocatalysts due to their remarkable stability and photocatalytic properties. In this study, La 2 O 3 nanoparticles were synthesized via a hydrothermal method and explored how varying calcination time (3 and 5 h) influences their structural, morphological, optical, and catalytic properties. X-ray diffraction (XRD) confirmed stable hexagonal structure, with crystallite sizes increasing from 32.79 to 45.49 nm, while UV–vis absorption studies revealed that increasing calcination time led to a gradual decrease in bandgap energy from 4.6 to 4.4 eV, making the material more effective at utilizing light for pollutant degradation. When tested against a range of organic dyes, La 2 O 3 nanoparticles calcinated for 5 h exhibited the highest degradation efficiencies, due to their improved crystallinity and enhanced charge carrier movement. The photocatalytic process followed first-order kinetics, and recyclability tests showed that the nanoparticles retained their efficiency over multiple cycles. Radical scavenger tests confirmed that hydroxyl radicals ( • OH) and superoxide radicals ( • O 2 – ) were the dominant reactive species involved in dye degradation, affirming the key mechanism behind the observed photocatalytic performance. These results highlight how fine-tuning calcination time can significantly enhance La 2 O 3 ’s potential, making it an eco-friendly solution for wastewater treatment.
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".