Band Diagram Insights into the Kinetic and Thermodynamic Engineering of Tandem Photocatalytic Cells
Bibliographic record
Abstract
In this work, we theoretically investigate the impact of kinetic and thermodynamic properties on the performance of photocatalytic cells operating in an unassisted tandem configuration, including electron affinity and ionization energies, recombination rates, and reaction rates. To this end, we present general rules and metrics for identifying and isolating the origin of an observed shift in the onset potential at either the photoanode or the photocathode of these devices. The correlation between kinetic and thermodynamic shifts in the onset potential is demonstrated through the use of band diagrams and key comparable features within readily accessible characterization tools: current–voltage plots are taken both under illumination and in the dark and further coupled with Mott–Schottky plots. To illustrate this conceptual framework, a model system comprised of a p-type doped BiVO 4 photocathode and an n-type doped BiVO 4 photoanode is employed. By varying each of the aforementioned kinetic and thermodynamic parameters in isolation, the manner in which these various mechanisms shift the onset potential is demonstrated. This work intends to showcase how kinetic and thermodynamic effects are distinctly manifested in these commonly used characterization tools and further proposes thermodynamic band-edge engineering as a potentially useful and largely unexplored avenue for possibly improving tandem cell performance, in addition to the conventional approach of optimizing kinetics.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".