Effect of pretreatment type on the physico-chemical properties of activated carbons derived from an invasive weed Prosopis juliflora: potential applications
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Bibliographic record
Abstract
Abstract This study investigates the effects of various pretreatment methods on the physico-chemical properties of activated carbons produced from the biochar of an invasive weed species, Prosopis juliflora . Utilizing a thermochemical conversion technique such as pyrolysis, followed by chemical and physical activation processes, we aimed to assess the functional characteristics of the resulting biochar for potential industrial applications. The pretreatments involved acidic (H 2 SO 4 , H 3 PO 4 , and ZnCl 2 ), basic (KOH and NH 4 OH) and oxidizing agents (H 2 O 2 ), and physical methods like air activation. Comprehensive characterization techniques, namely BET analysis, x-ray Photoelectron Spectroscopy (XPS), Ultimate Analysis, and pH pzc , were utilized to assess the influence of activation conditions. Principal component analysis was employed to elucidate the relationships between different activation methods and the physico-chemical properties of the activated carbons. Results from this study revealed that the choice of activation agent significantly influences the material’s structure and chemistry. The activation process of activated carbon (AC) is significantly influenced by temperature and the agent used. KOH-AC exhibited bulk oxygen content (5.96%) with a high bulk carbon content (91.73%), while Air-AC has a comparatively high bulk oxygen content (40.71%). The XPS data shows variations in carbon content and oxygen functional groups, influenced by the activation agent and temperature used during the process. The ranking of surface oxygen content was Air-AC (39.93%) > H 2 O 2 -AC (22.77%) > NH 4 OH-AC (17.61%). This study highlights the potential of Prosopis juliflora -derived biochar in diverse applications by tailoring its physico-chemical properties through specific activation processes, thereby also contributing to the upcycling of this invasive species.
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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 | 0.001 | 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 it