Roadmap on solar water splitting: current status and future prospects
Bibliographic record
Abstract
Abstract Artificial photosynthesis via solar water splitting provides a promising approach to storing solar energy in the form of hydrogen on a global scale. However, an efficient and cost-effective solar hydrogen production system that can compete with traditional methods using fossil fuels is yet to be developed. A photoelectrochemical (PEC) tandem cell consisting of a p-type photocathode and an n-type photoanode, with the photovoltage provided by the two photoelectrodes, is an attractive route to achieve highly efficient unassisted water splitting at a low cost. In this article, we provide an overview of recent developments of semiconductor materials, including metal oxides, nitrides, chalcogenides, Si, III–V compounds and organics, either as photocathodes or photoanodes for water reduction and oxidation, respectively. In addition, recent efforts in constructing a PEC tandem system for unassisted water splitting are outlined. The importance of developing a single-photon photocathode and photoanode that can deliver high photocurrent in the low bias region for efficient PEC tandem system is highlighted. Finally, we discuss the future development of photoelectrode materials, and viable solutions to realize highly efficient PEC water splitting device for practical applications.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.021 | 0.004 |
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".