Harmonizing Between Chemical Functionality and Surface Area of Porous Organic Polymeric Nanotraps for Tuning Carbon Dioxide Capture
Bibliographic record
Abstract
Abstract The energy sector has demonstrated significant enthusiasm for investigating post‐combustion CO2 capture, storage, and separation. However, the practical application of current porous adsorbents is impeded by challenges related to cost competitiveness, stability, and scalability. Intregation of heteroatoms in the porous organic polymers (POPs) dispense it more susceptible for CO2 adsorption to attenuate green house gases. In this regard, two hydroxy rich hypercrosslinked POPs, namely Ph/Tt‐POP have been developed by one‐pot condensation polymerization using a facile synthetic strategy. The high surface areas of both the Ph/Tt‐POP (1057 and 893 m2g−1, respectively), and the heteroatom functionality in the POP framework instigated us to explore our material for CO2 adsorption study. The CO2 uptake capacities in Ph/Tt‐POP are found to be 2.45 and 2.2 mmol g−1, at 273 K respectively. Further, in‐situ static 13C NMR experiment shows that CO2 molecules in Tt‐POP appear to be less mobile than those in Ph‐POP which probably due to the presence of triazine functional groups along with high abundant −OH groups in the Tt‐POP framework. An in‐depth study of the CO2 adsorption mechanism by density functional theory (DFT) calculations also shows that CO2 adsorption at the cages formed by two benzyl rings represents the most stable interaction and CO2 molecule is more favorably adsorbed on the Ph‐POP with the more negative interaction energies values compared to that of Tt‐POP. Further, Non‐covalent interaction (NCI) plot reveals that CO2 molecules adsorb more on the Ph‐POP than Tt‐POP, which can be explain by hydrogen bond formation in case of Tt‐POP repeating units turning aside CO2 molecule to interact with the Ph component. Overall, our present study reflects the comprising effects of surface area of the solid adsorbents as well as their functionality can be beneficial for developing efficient hypercrosslinked porous polymers as solid CO2 adsorbent.
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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".