Studies of the Photoprotection of Radiata Pine Wood Using Photocatalytic Nanoparticles
Bibliographic record
Abstract
In this work, TiO2 and ZnO nanoparticles of different sizes and crystallographic configuration were used to protect wood surfaces against UV radiation. The sizes and levels of photoactivity of the nanoparticles were measured in vitro by transmittance electron microscopy and electron paramagnetic resonance spectroscopy, and then they were impregnated into radiata pine samples. The production of aromatic radicals, absorbance of UV and visible light, and chemical and color changes of treated and untreated wood surfaces were assessed after UV irradiation. Results show that nanoparticles that were less photoactive were better at reducing the production of organic radicals and the chemical and color changes on wood surfaces subjected to UV. Similarly, smaller nanoparticles (40 nm) were better at reducing photochemical reactions than larger (100 nm) nanoparticles. In terms of the crystallographic configuration of nanoparticles, differences in the production of phenoxy radicals were verified only for short-term exposure. Previous research revealed that certain levels of photoactivity in TiO2 nanoparticles may contribute to decreases in the photodegradation of wood surfaces possibly by an electron sink mechanism. Our observations indicate that this is unlikely to occur in the presence of highly photoactive nanoparticles.
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".