A pore‐scale investigation for recovering adsorptive capacity of activated carbon fibre felt using electrothermal desorption combined with ozonization in‐situ degradation method
Bibliographic record
Abstract
Abstract Porous activated carbon fibre (ACF) materials, as a recycled absorbent, have been widely applied in the harmless disposal of volatile organic chemicals (VOCs). In order to reduce the energy consumption of cyclic regeneration process and avoid second pollution of high concentration VOCs, there is an urgent need to develop a synergistic regeneration method to recover the adsorptive capacity of ACF and achieve the in‐situ degradation of VOCs simultaneously. Due to the outstanding oxidation performance of ozone, ozonization was used to degrade VOCs adsorbed by absorbent materials and has a potential advantage in combination with the traditional electrothermal desorption technology. In this work, a three‐dimensional pore‐scale lattice Boltzmann method (LBM) is established to solve the convective heat and mass transfer processes considering the desorption and ozonization effects. Using this numerical model, a pore‐scale simulation is performed to investigate the reactive and desorptive transport behaviours in the reconstructed pore structure of ACF felt, which is regenerated using the electrothermal desorption process combined with the ozonization degradation method. The simulation works reveal the effects of key operation parameters on the desorption and degradation mechanisms into the pores of ACF felt during this combined regeneration process. The numerical results show that the flow velocity of carrier gas plays an important role on the performance of the combined regeneration process. The approach of reducing the carrier gas velocity would obviously improve the degradation ratio of VOC and the efficiency of the combined regeneration process.
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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".