Liquid-Phase Exfoliation of Biochars in Green Solvents and Correlation with Solvent Parameters
Bibliographic record
Abstract
Liquid-phase exfoliation (LPE) is a process frequently used to overcome the interactions between layers in layered materials to produce small sheets of material, with remarkable properties and high value applications. Materials are prepared via direct or indirect sonication in a solvent that must be able to effectively disperse and stabilize the sheets produced. Unfortunately, the preferred solvents for exfoliation processes are often toxic and possess several health risks. In this work, we show that LPE in greener solvents can be used to access nanostructures of biochar and further improve the applications of this renewable and bio-based material. Herein, pristine and oxidized biochars prepared from hardwood and softwood biomass waste (e.g. sludge, bark, and sawdust) are exfoliated in a range of solvents to allow the identification of benign alternatives that could afford highly concentrated dispersions. The majority of biochar nanostructures produced after exfoliation are stacked nanosheets containing between 2-8 layers (average 15 nm thickness). Correlations between effective LPE of biochar in solvents and different solvent parameters, including Kamlet-Taft, were established and allowed greener solvents to be used. Surface modification of biochars (e.g. via oxidation) has potential to increase their dispersibility in more benign solvents. LPE of oxidized biochars is more efficient in hydrogen-bond accepting solvents due to the increased concentration of carboxylic acid and alcohol functional groups on the surface of particles, when compared to non- functionalized biochars. Dispersions containing 0.20-0.75 mg/mL exfoliated oxidized biochar were obtained in solvents such as polyethylene glycols, glycerol formal and e-caprolactone. Moreover, LPE of pristine biochars in dimethyl carbonate, ethyl acetate, and solketal gave similar yields to more commonly used solvent for this process, N-methyl-2-pyrrolidone (NMP) a known reprotoxic molecule.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".