Synthesis of Black TiO<i><sub>x</sub></i> Nanoparticles by Mg Reduction of TiO<sub>2</sub> Nanocrystals and their Application for Solar Water Evaporation
Bibliographic record
Abstract
TiOx (x < 2) nanoparticles with tunable colors from white to gray to blue–gray to black are synthesized by magnesium (Mg) reduction of white P25 TiO2 nanocrystals followed by removal of excess Mg with aqueous HCl and distilled water. Increasing amounts of Mg smoothly decrease the oxygen content in TiOx which is responsible for the gradual increase in light absorption and concomitant darkening of its color from white to black with decreasing values of x. The as‐synthesized TiOx nanoparticles are spin‐coated onto the surface of a stainless steel mesh followed by surface superhydrophobization in order to test their performance as a solar water evaporator. Results from the tests show that the black TiOx efficiently generates water vapor with a solar thermal conversion efficiency as high as 50% under solar‐simulated light irradiance at an intensity of 1000 W m–2 (1 Sun). Moreover, TiOx nanoparticles have inherent advantages over other materials used for solar water desalination, such as their tunable light absorption, low‐cost, low‐toxicity, superhydrophobicity, and chemical stability.
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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".