Recent avenues in the photocatalytic splitting of water for eco-friendly hydrogen production
Bibliographic record
Abstract
Fossil fuel-driven carbon emissions are destabilizing the global climate. The COP28 conference, recently held in Dubai, UAE, under the UNCCC, marked a pivotal moment by signaling the “beginning of the end” for fossil fuels, advocating for a swift and equitable transition with significant emission reductions and increased financial support. Photocatalysts offer immense potential for sustainable applications such as hydrogen production and organic pollutant degradation. However, challenges persist, including limited visible-light absorption due to large bandgaps, rapid recombination of charge carriers, susceptibility to corrosion, lack of selectivity, and partial catalytic activity for specific reactions. This review examines the use of various photocatalysts for hydrogen production via water splitting. It discusses the reaction mechanisms involved and the different types of photocatalysts, including metal oxides, carbon-based materials, semiconductors, and metal-organic frameworks (MOFs). Recent advancements in photocatalyst technology have focused on strategies such as bandgap engineering, co-catalyst deposition, surface modification, heterojunction formation, and co-catalyst engineering. These approaches aim to improve photocatalytic performance by enhancing activity, broadening the absorption range, and increasing charge separation efficiency. Techniques like doping with foreign elements, modifying surface morphology, creating heterojunctions with other semiconductors, and adjusting bandgaps have shown promise in addressing these challenges. Moreover, studies have highlighted the influence of factors such as doping, crystal structure, particle size, and surface morphology on photocatalytic efficiency. These innovations collectively improve the effectiveness, selectivity, and stability of photocatalysts, positioning them as strong candidates for sustainable energy solutions and environmental remediation. Finally, this study outlines challenges, recent progress, and offers insights into future directions for enhancing photocatalyst efficiency to address global energy and environmental needs. • Photocatalysts show promise for eco-friendly hydrogen production from water splitting. • Challenges include wide bandgap and rapid charge carrier recombination. • Strategies like surface modification enhance photocatalytic activity and efficiency. • Incorporation of sacrificial agents improves hydrogen generation outcomes. • Recent advancements focus on optimizing catalyst design and light absorption.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".