Simultaneously Solving the Photovoltage and Photocurrent at Semiconductor–Liquid Interfaces
Bibliographic record
Abstract
In this work, we present a general theoretical and numerical approach for simultaneously solving the photovoltage and photocurrent at semiconductor–liquid interfaces. Our methodology extends drift-diffusion methods developed for metal–semiconductor Schottky contacts in the device physics community into the domain of semiconductor–liquid “pseudo-Schottky” contacts. This model is applied to the study of photoelectrochemical anodes, utilized in the oxidative splitting of water. To capture both the photovoltage and photocurrent at semiconductor–liquid interfaces, we show that it is necessary to solve both the electron and hole current continuity equations simultaneously. The electron continuity equation is needed to primarily capture the photovoltage formation at photoanodes, whereas the hole continuity equation must be solved to obtain the photocurrent. Both continuity equations are solved through coupled recombination and generation terms. Moreover, to capture charge transfer at the semiconductor–liquid interface, floating (Neumann) boundary conditions are applied to the electron and hole continuity equations. As a model system, we have studied the illuminated hematite photoanode, where it is shown that our approach can capture band flattening during the formation of a photovoltage, as well as the photocurrent onset and saturation. Finally, the utility of this methodology is demonstrated by correlating our theoretical calculations with photocurrent measurements reported in the literature. In general, this work is intended to expand the scope of photocatalytic device design tools and thereby aid the optimization of solar fuel generation.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".