Boosting the Photocatalytic Behavior of PbS/TiO2 Nanocomposites via the Pulsed Laser Deposition of PbS Nanoparticles onto TiO2 Nanotube Arrays Under Various Helium Background Pressures
Bibliographic record
Abstract
In this study, highly ordered titanium dioxide nanotubes (TiO2-NTs) have been synthesized using the electrochemical anodization procedure. Subsequently, the TiO2-NTs were successfully decorated with PbS nanoparticles (NPs) using the pulsed KrF-laser deposition (PLD) technique under vacuum and under different Helium background pressures (PHe) ranging from 50 to 400 mTorr. The prepared samples (PbS-NPs/TiO2-NTs) were characterized using scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), energy dispersive X-ray spectroscopy (EDX), and UV–Vis and photoluminescence spectroscopies. XRD analyses confirmed that all TiO2-NTs crystallized in the anatase phase, while the PbS-NPs crystallized in the cfc lattice. The average crystallite size of the (200) crystallites was found to increase from 21 to 33 nm when the pressure of helium (PHe) was raised from vacuum to 200 mTorr and then dropped back to ~22 nm at PHe = 400 mTorr. Interestingly, the photoluminescence intensity of the PbS-NPs/TiO2-NTs samples was found to start diminishing for PHe ≥ 200 mTorr, indicating a lesser recombination rate of the photogenerated carriers, which also corresponded to a better photocatalytic degradation of the Amido Black (AB) dye. Indeed, the PbS-NPs/TiO2-NTs samples processed at PHe = 200 and 300 mTorr were found to exhibit the highest photocatalytic degradation efficiency towards AB with a kinetic constant 130% higher than that of bare TiO2-NTs. The PbS-NPs/TiO2-NTs photocatalyst samples processed under PHe = 200 or 300 mTorr were shown to remove 98% of AB within 180 min under UV light illumination.
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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 | 0.000 | 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".