Enhanced photoactivity towards bismuth vanadate water splitting through tantalum doping: An experimental and density functional theory study
Bibliographic record
Abstract
The activation of hole trap states in bismuth vanadate (BiVO 4 ) is considered an effective strategy to enhance the photoelectrochemical (PEC) water-splitting activity. Herein, we propose a theoretical and experimental study of tantalum (Ta) doping to BiVO 4 leading to the introduction of hole trap states for the enhanced PEC activity. The doping of Ta is found to alter the structural and chemical surroundings via displacement of vanadium (V) atoms that cause distortions in the lattice via the formation of hole trap states. A significant enhancement of photocurrent to ∼4.2 mA cm −2 was recorded attributing to the effective charge separation of efficiency of ∼96.7 %. Furthermore, the doping of Ta in the BiVO 4 lattice offers improved charge transport in bulk and decreased charge transfer resistance at the electrolyte interface. The Ta-doped BiVO 4 displays the effective production of hydrogen (H 2 ) and oxygen (O 2 ) under AM 1.5 G illumination with a faradaic efficiency of 90 %. Moreover, the density functional theory (DFT) study confirms the decrease in optical band gap and the activation of hole trap states below the conduction band (CB) with a contribution of Ta towards both valence and CB that increases the charge separation and majority charge carrier density, respectively. The findings of this work propose that the displacement of V sites with Ta atoms in BiVO 4 photoanodes is an efficient approach for enhanced PEC activity.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".