Thermodynamics of <scp>CO<sub>2</sub></scp> adsorption on cellulose‐derived biochar prepared in ionic liquid
Bibliographic record
Abstract
Abstract This work focused on thermodynamic analysis of carbon dioxide (CO2) adsorption on a promising biochar as a CO2 adsorbent. The biochar was prepared by catalytic pyrolysis of cellulose material in ionic liquid at moderate temperature. The adsorption characteristics, such as adsorption capacity, interfacial potential, Gibbs free energy change, enthalpy change, entropy change, and internal energy change, influenced by adsorption temperature and gas pressure, were systematically investigated. The results indicated that CO2 adsorption on cellulose‐derived biochar was a spontaneous, physical, exothermic, and entropic decrement process, accompanied by adsorption capacity of 5.2 mmol/g and interfacial potential of −18.2 J/g at 273 K and 100 kPa. The process could be well described by adsorption potential theory. Then a quasi‐Gaussian distribution of site energy was verified for CO2 adsorption. The interfacial potential was found to be a monotropic function of the amount of CO2 adsorbed, and the latter was actually a differential of the former via adsorption potential. The positive temperature effect and negative pressure effect on negative Gibbs free energy change indicated that reducing adsorption temperature and increasing gas pressure were beneficial to CO2 uptake, accompanied by the increase of adsorption capacity and the reduction of interfacial energy, entropy, enthalpy, and internal energy. The strongest temperature effects on entropy change, enthalpy change, and internal energy change existed at given pressure or temperature. The pressure effect was stronger and more sensitive to pressure at lower adsorption pressure. More interestingly, the peak pressure or peak temperature with the strongest pressure effect possibly existed during CO2 adsorption.
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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 | 0.000 |
| 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) | 0.001 | 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".