Canola meal‐derived biochar for highly efficient dye removal and the impact of compression treatment on porous structure
Bibliographic record
Abstract
Abstract BACKGROUND This study reported a canola meal‐based biochar adsorbent for highly efficient organic dyes removal. SEM, BET, Zeta‐potential and XPS etc. were employed to characterize the micro‐structure and chemical composition of the biochar, demonstrating the impact of compression treatment on its inner pore structure. RESULTS KOH‐activated carbonized canola meal‐compressed (KCCM‐C) showed a high specific surface area of up to 2135 m 2 g −1 with an average pore size of 2.65 nm, which exhibited excellent adsorption capacity for both positively and negatively charged dyes with maximum values of 985 mg g −1 and 813 mg g −1 for methylene blue (MB) and methyl orange (MO) respectively, exceeding majority of the biochar adsorbents reported so far. The dye adsorption behavior was dominated by monolayer coverage with both physical adsorption and chemisorption. Langmuir isotherm model fitted well with the adsorption data, and the adsorption kinetic followed the pseudo‐second‐order model. Negative Gibbs free energy and positive enthalpy change indicated that the adsorption was a spontaneous endothermic process. XPS analysis indicated that the amino groups of proteins inside the canola meal as the active sites were oxidated by KOH prior to other components, while the compact structure of compressed canola meal was more conducive to the formation of uniform meso‐pores inside canola meal‐derived biochar improving its adsorption performance. CONCLUSIONS This high‐quality porous biochar, directly synthesized from the compressed canola meal, simplifies the grinding process and presents a valuable opportunity for the value‐added application of canola meal. © 2023 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".