Recovering of Carbon from Plastic Waste in Overheated Vapor Environment and its Structure/property investigation
Bibliographic record
Abstract
The novel two stage method of recovering nanoscale carbon in overheated vapor environment from plastic (PET) waste that includes low-temperature pyrolysis of waste at the initial stage and following high temperature (up to 900 0 C) thermal/chemical treatment in vapor environment was developed.The investigation showed that application of low temperature pyrolysis before second stage treatment in control environment (CO2 & Argon) allows essentially to reduce loses of char before second stage processing and increases output of nanoscale carbon after high temperature treatment in overheated water vapor environment.The vapor treatment at low temperatures (up to 700 0 C) activates the pyrolysis process and increases the primary reactions of hydrocarbon decomposition.Accordingly, the release of gases increases and the main part of which during the pyrolysis process is extracted as a liquid fractionpyrolytic oil and reminder amorphous coal containing different organic/inorganic impurities.After increasing of the temperature above 700 0 C with simultaneously feeding of vapor, the overheated water vapor increases the rates of side reactions and full decomposition pyrolytic reminders takes place.As a result, the loosening of the formed carbon aggregates occurs and formation of the highly dispersed, nanoscale carbons with essentially increased surface area there takes place.As investigation showed (including SEM observation) the characteristics of obtained nanoscale carbon changes in wide range depending from processing conditions (vapor temperature, vapor feeding rate, processing period etc.) and may reach to 1000 m 2 /g (BET surface area) and 98.7% (purity) respectively.
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) | 0.000 | 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; a candidate call from one teacher head, 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".