From Plastic to Fuel - New Challenges
Bibliographic record
Abstract
The increased demand for energy sources is the driving force to convert organic compounds into alternative fuels. Plastic waste disposal affects the environment, since they are not easily recycled and, during the recycling process, they can produce waste ash, heavy metals, or potentially harmful gas emissions. In the plant design for plastic converting into fuel, the chemical reactor is one of the advanced equipment in the field of chemical and process engineering. This study emphasizes the feasibility of pyrolysis process for valorisation plastics by producing energy-efficient products. In this respect, samples of polypropylene, polyethylene and polystyrene were used as models and subjected to pyrolysis processes at 450 �C, in the presence of two types of mesoporous silica materials, MCM-41 and SBA-15, using a modern developed reactor. The use of mesoporous materials increased the calorific value of the obtained oil and gas, thus improving the economic potential of the process end products. This study dealt with the extraction of oil from plastics termed as plastic pyrolysis oil (PPO) and plastics pyrolysis gas (PPG), with a composition rich in different types of hydrocarbons and they can be marketed at much cheaper rates compared to that present in the market.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.004 | 0.010 |
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".