Investigation of the potential effect of encapsulated metal nanoparticles on enhancement of thermophilic anaerobic digestion
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<abstract><p>The present work investigates the enhancement effect of seven different catalysts made of Cu/SiO<sub>2</sub>, Pd/SiO<sub>2</sub>, Pt/SiO<sub>2</sub>, Ni/SiO<sub>2</sub>, Co/SiO<sub>2</sub>, Ag/SiO<sub>2</sub> and Fe/SiO<sub>2</sub> nanoparticles (NPs) on methane production during thermophilic anaerobic digestion. The tested NPs were synthesized by the sol-gel process and encapsulated in porous silica (SiO<sub>2</sub>) to prevent their coagulation and agglomeration. Transmission electron microscopy (TEM) pictures confirmed the specific morphologies of all seven catalysts.</p> <p>Then, these 7 NPs were tested first in batch experiments with acetate as a carbon substrate for bio-methane production. Ni/SiO<sub>2</sub> and Co/SiO<sub>2</sub> showed the best enhancement of methane production from acetate. From this part, both NPs were tested for bio-methane production on two different substrates: starch and glucose. With the starch substrate, the improvements of methane production were equal to 47% and 22%, respectively, for Ni- and Co/SiO<sub>2</sub> compared to control sample. In the last part of this work, the influences of NP concentration and thermal pre-treatment applied to the NPs on bio-methane production from glucose were investigated. The results showed that all forms of nickel and cobalt NPs enhance the methane production, and their effect increased with the increase of their concentrations. The best sample was the calcined nickel NPs at a concentration of 10<sup>–4</sup> mol L<sup>–1</sup>, leading to a methane production rate of 72.5% compared to the control.</p></abstract>
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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 | 0.001 |
| 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 it