Pyrolyzed biomass-derived nanoparticles: a review of surface chemistry, contaminant mobility, and future research avenues to fill the gaps
Bibliographic record
Abstract
Nanoparticles are abundant in the subsurface, soil, streams, and water bodies, and are often a critical control on elemental speciation, transport and cycling in the natural environment. This review provides an overview of pyrolyzed biomass-derived nanoparticles (PBNPs), their surface properties and reactivity towards aqueous species. We focus specifically on biochar-derived nanoparticles and activated carbon-derived nanoparticles which fall under our classification of PBNPs. Activated carbon-iron (nano)composites are included in some instances where there are significant gaps in literature because of their environmental relevance. Increased use of activated carbon, along with a resurgence in the manufacture and application of biochar for water treatment and soil amendment, has generated significant concerns about the mobility and toxicity of PBNPs derived from the bulk material in environmental applications. Recent examples are discussed to highlight current progress in understanding the influence of PBNPs on contaminant transport, followed by a critical discussion of gaps and future research directions.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".