Development in Photoelectrochemical Water Splitting Using Carbon-Based Materials: A Path to Sustainable Hydrogen Production
Bibliographic record
Abstract
Hydrogen production via water splitting is a crucial strategy for addressing the global energy crisis and promoting sustainable energy solutions. This review systematically examines water-splitting mechanisms, with a focus on photocatalytic and electrochemical methods. It provides in-depth discussions on charge transfer, reaction kinetics, and key processes such as the oxygen evolution reaction (OER) and hydrogen evolution reaction (HER). Various electrode synthesis techniques, including hydrothermal methods, chemical vapor deposition (CVD), pulsed laser deposition (PLD), and radio frequency sputtering (RF), are reviewed for their advantages and limitations. The role of carbon-based materials such as graphene, biochar, and graphitic carbon nitride (g-C3N4) in photocatalytic and photoelectrochemical (PEC) water splitting is also highlighted. Their exceptional conductivity, tunable band structures, and surface functionalities contribute to efficient charge separation and enhanced light absorption. Further, advancements in heterojunctions, doped systems, and hybrid composites are explored for their ability to improve photocatalytic and PEC performance by minimizing charge recombination, optimizing electronic structures, and increasing active sites for hydrogen and oxygen evolution reactions. Key challenges, including material stability, cost, scalability, and solar spectrum utilization, are critically analyzed, along with emerging strategies such as novel synthesis approaches and sustainable material development. By integrating water splitting mechanisms, electrode synthesis techniques, and advancements in carbon-based materials, this review provides a comprehensive perspective on sustainable hydrogen production, bridging previously isolated research domains.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".