Photochemical Synthesis of Radiate Titanium Oxide Microrods Arrays Supporting Platinum Nanoparticles for Photoassisted Electrooxidation of Methanol
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Photoassisted catalysis is recently adopted to accelerate the kinetics of the methanol oxidation, which allows the photocatalysis and electrocatalysis simultaneously occur on the catalyst surface and even on interior region. The rational design of highly efficient photoassisted electrocatalysts is highly desirable, however, it is very challenging. In this study, architectures of radiate TiO 2 microrods arrays support Pt nanoparticles (Pt NPs/TiO 2 MRs) are developed, via the combination of first hydrothermal and subsequent photodeposition process. Benefited from the synergetic effect of photocatalytic acceleration and the radiate architectures, the mass activity of Pt NPs/TiO 2 MRs for methanol electrooxidation, under UV irradiation (wavelength: 365 nm), is 2.77 and 6.1 times as high as those of Pt NPs/TiO 2 MRs without irradiation and commercial Pt/C, respectively. Moreover, under UV irradiation, both the CO tolerance and durability of the Pt NPs/TiO 2 MRs catalysts are significantly improved. Notably, in both acidic and alkaline media, the Pt NPs/TiO 2 MRs catalysts show improved electrocatalytic performance for photoassisted electrooxidation of methanol. This study provides a building art toward 3D architectures of radiate semiconductor MRs arrays supporting metallic NPs, and offers an effective way to improve the electrochemical activity of methanol oxidation utilizing the synergistic combination of photocatalysis and electrocatalysis.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it