High-flux rattan biochar microreactor for efficient peroxymonosulfate activation via component-regulated structure engineering
Bibliographic record
Abstract
Agroforestry waste-derived biochar has attracted wide interest in environmental remediation owing to its resource abundance and structural advantages. However, pristine biochar powders usually exhibit low catalytic activity and encounter challenges in separation and recovery, which limit their large-scale application. Here, we developed a rattan-derived biochar microreactor with a robust monolithic structure and abundant active sites using a facile component-regulation strategy. By tuning the inherent cellulose and lignin composition, we tailored hierarchically porous channels with high surface area, abundant defect-related catalytic sites, and desirable electrical conductivity. Taking peroxymonosulfate (PMS) activation as a model process, the continuous-flow biochar microreactor achieved efficient degradation of tetracycline (TC), methylene blue (MB), and rhodamine B (RhB), with an ultrahigh flux of 2.3 × 10 4 L/(m 2 ·h) driven by gravity. Coupling with deep mechanism investigation and density functional theory (DFT) simulation, the favorable carbon configurations (e.g., graphitic structures and boundary-like defects) triggered a desirable non-radical dominated pathway in PMS activation, contributing to the impressive catalytic performance. This work not only expands horizons for high value-added utilization of biomass waste but also provides a practical paradigm for designing high-performance biochar microreactors for environmental remediation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".