Kinetic and Thermodynamic Engineering of Photocatalytic Behaviour for Unassisted Water Splitting
Bibliographic record
Abstract
As the world moves towards intermittent renewable sources of energy and the use of solar power increases, there is a increasing need for large-scale energy storage.One such technology is photoelectrochemical (PEC) cells that store solar energy in the form of chemical fuels by utilizing semiconductor photoelectrodes that generate charge carriers which participate in redox reactions in the electrolyte.These devices suffer from poor efficiency and there is a lack of understanding as to which factors increase performance and how these factors manifest in measurable parameters such as the onset potential.In this work, semi-analytical modelling is used to theoretically investigate the effect of kinetic factors, thermodynamic factors, and pH on the performance of PEC cells in a tandem configuration (where both the photoanode and photocathode are photoactive).The performance of these cells is characterized by the photocurrent that is generated when the system in unassisted, with no applied bias.A model system based on BiVO 4 is used in all analyses.In terms of kinetic factors, carrier lifetimes and carrier transfer rates are investigated to understand how decreasing recombination rates and increasing carrier transfer from the semiconductor into the electrolyte influences unassisted operation.For thermodynamic factors, band edge engineering of the conduction band minimum (electron affinity) of photoanodes and valence band maximum (ionization energy) of photocathodes is investigated.Finally, the effect of electrolyte pH on performance is studied.Through this work, it is established that in addition to traditional approaches of optimizing carrier lifetime and carrier transfer, thermodynamic band edge engineering is a new avenue for experimental exploration as it does indeed provide increased performance.Further, altering pH does not improve tandem PEC cell performance.In line with these results, a method using dark and light photocurrent-voltage curves along with Mott-Schottky plots to determine which aforementioned factor is causing a perceived onset shift is presented.i Firstly, I would like to extend my heartfelt gratitude to my supervisor, Professor Kirk H.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".