Conversion of Waste Corn Biomass to Activated Bio-Char for Applications in Wastewater Treatment
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Bibliographic record
Abstract
This study proposes the conversion of waste corn grains contaminated by deoxynivalenol (also known as vomitoxin), a mycotoxin produced by plant pathogens, into a value-added product. Batches of 500 g of contaminated corn grains were pyrolyzed in a batch reactor by thermal treatment at temperatures up to 500°C with a 15°C/min heating rate and generating condensable vapors, gases and solid bio-char. The bio-char produced was subsequently activated in a furnace at 900°C, using CO 2 as an activation agent, at different residence times. The effect of activation residence time on the characteristics of the activated bio-char, varying it from 0.5 to 3 h, was investigated. Characterization tests included BET surface area, SEM, TG-FTIR, pH, and XRD on both bio-char and activated bio-char. BET results illustrated a significant increase of the surface area from 63 to 419 m 2 g −1 and pore volume from 0.04 to 0.23 cm 3 g −1 by increasing the activation time from 0.5 to 3 h. SEM images visually confirmed a considerable increase in pore development. The pH significantly increased from 6 to 10 after activation, due to the elimination of acidic functional groups. The proximate analysis showed the stable carbon of the activated char reaching approximately 90 wt%, making it promising for catalyst/adsorbent applications. The adsorption performance of activated bio-char was tested by utilizing three different model molecules with different characteristics: methylene blue, methyl orange, and ibuprofen. Among all activated bio-char samples, activated bio-char with 3 h activation time showed the highest adsorption capacity, with a total adsorption (25 mg/g of activated bio-char) of methylene blue after 5 min. The results showed that the adsorption capacity of the activated bio-char was similar to that of valuable commercial activated carbon.
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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) | 0.001 | 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