Harnessing coal and coal waste for environmental conservation: A review of photocatalytic materials
Bibliographic record
Abstract
Fossil fuels, especially coal, have played a pivotal role in driving technological and economic advancements over the past century, though accompanied by numerous environmental challenges. Rapid progress in green and sustainable energy sources, including tidal, wind, and solar energy, coupled with growing environmental concerns, the conventional coal industry is experiencing a sustained decline in both size and financial viability. This situation necessitates the urgent adoption of advanced approaches to coal utilization. Beyond serving as an energy source, coal and its by-products, known as coal waste, can serve as valuable resources for the development of advanced materials, including photocatalysts. The advancement of photocatalytic materials derived from coal and coal waste can capitalize on these natural carbon and mineral sources, providing a viable solution to numerous environmental challenges. Currently, research in this domain remains in its early stages, with existing studies primarily focusing on specific types of photocatalysts or particular aspects of the fabrication process. Therefore, available coal-based and coal waste-based photocatalytic materials were systematically examined and categorized into six types according to their composition and dimensional/structural characteristics. Each type of photocatalytic material was introduced, along with common fabrication and characterization technologies. Representative works were discussed in detail to highlight the unique features of different types of coal-based and coal waste-based photocatalytic materials. Furthermore, the promising applications of these materials in environmental protection and pollution treatment were summarized, while also addressing the challenges and prospects in this research field. This review comprehensively overviews the fundamental knowledge and recent advancements in photocatalytic materials derived from coal and coal waste, with the goal of catalyzing the development of next generation photocatalysts and contributing to the transformation of the conventional coal industry.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".