Constructing 1D/2D heterojunction photocatalyst from FeSe <sub>2</sub> nanorods and MoSe <sub>2</sub> nanoplates with high photocatalytic and photoelectrochemical performance
Bibliographic record
Abstract
Although the traditional metal oxide catalyst has high activity and strong degradation ability, the forbidden bandgap is generally larger, and the utilization rate of sunlight is much low. Moreover, the high internal resistance inhibits carrier transfer, so the photoelectrochemical performance needs to be improved. Selenides with narrow bandgap and low internal resistance are promising candidates for photocatalysts. A new type of 1D/2D selenide heterojunction was constructed by compositing MoSe2 and FeSe2, two kinds of narrow bandgap metal selenides. In this 1D/2D heterojunction, MoSe2 presents a three-dimensional network structure, which can effectively collect and transport optical carriers, and it is an ideal heterostructure as a substrate loaded with 1D FeSe2 nanorods. Moreover, this heterojunction has good light absorption characteristics and can achieve full spectrum absorption of ultraviolet and visible light. This FeSe2/MoSe2 composite has photocatalytic performance more than 3.4 times that of MoSe2, and its photoelectrochemical performance is more than 2 times. The experimental results show that FeSe2/MoSe2 is an ideal composite system with great potential in photocatalysis.
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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 | 0.001 | 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 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".