A review on conversion of carbon dioxide ( <scp> CO <sub>2</sub> </scp> ) to methanol and methane by photocatalytic reactors: a comparative analysis with algae‐based <scp> CO <sub>2</sub> </scp> sequestration
Bibliographic record
Abstract
Abstract Carbon dioxide (CO 2 ) emission due to urbanization and industrialization are the key factors behind global warming and climate changes. United Nations in 2018, stated that, due to CO 2 emissions, earth's temperature would increase 1.5 °C between 2032 and 2050. Variation in climatic conditions will definitely have a huge impact on human health and ecosystem. To mimic the CO 2 emission, various countries have put forward laws and policies. This review focuses primarily on the biological and photocatalytic reduction of CO 2 to valuable products like chemicals and fuels. This review provides valuable information on the reduction of CO 2 to valuable products and benefits the researchers, academics, and industrial personnel on resource recovery concepts. Photo reactor design and operating conditions define the level of CO 2 conversion efficiency. Algae‐based CO 2 utilization and recovery of products from algae biomass are explored for biofuel production process. However, the storage capacity of products, bulk processing of CO 2 are needed in future research perspectives. Overall, this study strongly contributes towards achieving sustainable development goals (SDGs). © 2025 Society of Chemical Industry (SCI).
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How this classification was reachedexpand
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".