Comparison of Oil-Seed Shell Biomass-Based Biochar for the Removal of Anionic Dyes—Characterization and Adsorption Efficiency Studies
Bibliographic record
Abstract
This research investigated the synthesis of biochar through the direct pyrolysis of pre-roasted sunflower seed shells (SFS) and peanut shells (PNS) and compared their application for the effective removal of textile dyes from wastewater. Biochar prepared at 900 °C (SFS900 and PNS900) showed the highest adsorption capacity, which can be attributed to the presence of higher nitrogen content and graphite-like structures. CHNS analysis revealed that PNS900 exhibited an 11.4% higher carbon content than SFS900, which enhanced the environmental stability of PNS biochar. Fourier-transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) analyses of the produced biochar indicated the degradation of cellulosic and lignin moieties. X-ray photoelectron spectroscopy (XPS) revealed a 13.8% and 22.6% increase in C-C/C=C mass concentrations in the SFS900 and PNS900, respectively, and could be attributed to the condensation of polyaromatic structures. Batch experiments for dye removal demonstrated that irrespective of dye species, PNS900 exhibited superior dye removal efficiency compared to SFS900 at similar dosages. In addition to H-bonding and electrostatic interactions, the presence of pyridinic-N and graphitic-N can play a vital role in enhancing Lewis acid-base and π-π EDA interactions. The results can provide valuable insights into the biochar-dye interaction mechanisms.
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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".