PRED treatment mediated stable and efficient water oxidation performance of the Fe<sub>2</sub>O<sub>3</sub> nano-coral structure
Bibliographic record
Abstract
Herein, we demonstrate that an electrochemical surface treatment of Fe foil with simple pulse reverse electrodeposition (PRED) prior to thermal oxidation can substantially enhance the photoelectrochemical (PEC) stability and water splitting performance of Fe2O3/Fe photoanodes. Comprehensive structural (XRD, FESEM, and HRTEM), compositional (XPS depth profiling), and electrochemical (EIS and Mott-Schottky) analyses were performed to understand the effect of PRED treatment on the PEC performance of fabricated photoanodes. It is revealed that air-exposed Fe foil is prone to formation of a loosely bound surface oxide layer that, upon annealing at 800 °C, results in an unstable Fe2O3 nano-flake (2-3 μm long) morphology. In contrast, when such Fe foil is pre-treated with PRED to etch the loosely bound oxide layer, adherent inverse-opal-like nano-coral structures (60-100 nm thin) are formed. In addition to stability improvement, PRED-treatment also assists in exposing the photocatalytically active high index [104] facet sites of hematite. Thin hematite nano-coral structures with high index [104] facet sites significantly improved the separation of photo-generated charge carriers and oxygen evolution kinetics, resulting in performance enhancement with excellent photocurrent stability for extended duration in a 1 M NaOH solution under one sun illumination. The net photocurrent density for nano-coral morphology was 0.813 mA cm(-2) at 1.23 V vs. RHE, which is the highest reported value for pristine hematite photoanodes fabricated from Fe foil.
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How this classification was reachedexpand
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 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".