Glucose photorefinery for sustainable hydrogen and value-added chemicals coproduction
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
As a naturally occurring and stable energy supply, biomass will be the leading renewable energy in the future, and its high-value application will help promote the realization of carbon neutrality. Glucose, as the basic unit of lignocellulosic biomass, has been widely investigated as the feedstock to produce various value-added chemicals. Compared to the traditional glucose valorization platforms, such as thermal catalysis and biological fermentation, solar-driven photocatalysis holds the advantages in mild reaction conditions and controllable reaction kinetics, and it is emerging as a sustainable and efficient technology for glucose conversion. With the rational design of the photocatalysts, glucose could be selectively converted into specified chemicals via oriented bond cleavage along with the sustainable generation of hydrogen at the same time, which is the so-called glucose photorefinery process. This present review introduces the general principles and latest progress in glucose photorefinery. The rational design of bifunctional photocatalysts to achieve extended light absorption, efficient charge separation, and favorable surface reaction is also introduced. The oriented breakage of the chemical bonds in glucose molecules to produce different chemicals on different active sites is highlighted. Finally, challenges and perspectives on glucose photorefinery to achieve further efficiency and more fruitful reaction pathways are proposed. This present review is believed to provide guidance for the biomass valorization by mild photocatalysis to simultaneously produce sustainable fuels and chemicals with the rational design of dually functional photocatalysts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it