Improving process sustainability in bio-oil transforming for biofuels and platform chemicals production: Valorization of the carbon residue
Bibliographic record
Abstract
This work introduces a zero-waste approach to process biomass-derived raw bio-oil by addressing the valorization of the carbon residue that inevitably deposits, reducing the bio-oil conversion efficiency and leading to reactor-clogging issues. The study explores the feasibility of producing value-added porous material for removing pollutants from industrial wastewaters. An activated carbon with a specific surface area of 1070 m2 g−1 and a micropore volume of 0.41 mL g−1 was successfully produced through a simple thermochemical method involving pyrolysis, alkaline treatment, and carbonization. The impact that the activation method has on the nature, structure, and adsorption capacity of the material was assessed using methylene blue (MB) and hexavalent chromium (Cr-VI) as probe molecules. The activated carbon exhibited remarkable adsorption efficiency, achieving a removal ratio of 98 % for MB and 47 % for Cr-VI. Recyclability tests demonstrated a slight loss of adsorption capacity over multiple cycles. Kinetic studies, employing Surface Reaction Models and Mass Transfer Modeling, provide insights into adsorption rate-limiting steps. Chemisorption was identified as the most limiting stage, with physisorption and liquid film diffusion playing roles, particularly at short solid–liquid contact times. For longer contact times, intraparticle pore diffusion becomes the rate-controlling step due to the highly microporous nature of the activated carbon.
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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 | 0.000 | 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".