Enhancing CO2 adsorption performance of cold oxygen plasma-treated almond shell-derived activated carbons through ionic liquid incorporation
Bibliographic record
Abstract
To enhance the CO 2 adsorption of almond shell-derived activated carbon (AC) samples treated with cold oxygen plasma, the samples were impregnated with cholinium-amino acid ionic liquids ([Cho][AA] ILs) using the vacuum-assisted impregnation method. The physicochemical and textural properties of the resulting composites (ILs@AC) were characterized using various techniques, including Fourier-transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), scanning electron microscopy (SEM) coupled with energy-dispersive X-ray (EDX) spectroscopy, and Brunauer-Emmett-Teller (BET) surface area measurement. The CO 2 adsorption performance of the samples was evaluated using a quartz crystal microbalance (QCM) over a temperature range of 288.15–308.15 K and gas pressures up to 1 bar. The IL@AC composite materials exhibited notably improved CO 2 adsorption capacities compared to pristine AC. The CO 2 adsorption isotherms onto the IL@AC composite samples closely conformed to the Langmuir isotherm model, indicating the dominant involvement of strong intermolecular interactions, particularly driven by amine functionalities. Meanwhile, the results revealed that [Cho][His]@AC showed lowered CO 2 adsorption capacity compared to [Cho][Pro]@AC and [Cho][Gln]@AC. Among the studied ionic liquids, [Cho][Pro]@AC showed the highest absorption capacity (2.332 mmol·g −1 at 288 K and 1 bar). This was due to the obstruction of internal pores within the AC structure caused by excessive amine incorporation into its porous framework. In the meantime, for a deeper insight into the impregnation process of ILs onto the AC surfaces and their potential interactions with CO 2 molecules, we conducted density-functional theory (DFT) calculations using the ωB97XD/6-31 + G(d,p) method. The calculated interaction energies, ranging from − 1.19 to − 1.44 eV, along with calculated quantum chemical descriptors, indicated a notable stabilization of IL species on the AC surfaces, with high affinity toward CO 2 molecules. • We prepared activated carbon from almond shells treated by cold oxygen plasma. • To improve CO 2 adsorption capacities AC, ILs were immobilized onto AC surfaces. • IL@AC samples were characterized using FT-IR, TGA, SEM, EDX, and BET techniques. • The CO 2 adsorption process in the IL@AC is exothermic. • DFT calculations were conducted for impregnation of ILs onto AC surfaces and their potential interactions with CO 2 .
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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".