Pore size regulation of <scp>ZIFs</scp> for adsorptive separation of branched chain and aromatic amino acids
Bibliographic record
Abstract
Abstract This research endeavour aims to investigate the adsorptive separation of the branched chain (BCAA) and aromatic amino acids (AAA). Based on the different molecular sizes of BCAA and AAA, zeolitic imidazolate frameworks (ZIFs) with different pore structures were prepared by regulating the size of imidazole ligands. The structure and pore shape were characterized by Fourier transform infrared spectroscopy (FT‐IR), x‐ray diffraction (XRD), scanning electron microscope (SEM), and BET surface area (BET). The results indicated the successful synthesis of ZIF‐[Co(mIm) 2 ], ZIF‐[Co(eIm) 2 ], and ZIF‐[Co(pIm) 2 ] with pore size distribution of 7.821, 6.943, and 9.394 Å, and particle size of these ZIFs was approximately 4 μm. ZIF‐[Co(eIm) 2 ] was chosen as the optimal ZIFs for the separation of BCAA and AAA. The adsorption experiment was evaluated in the respective single and binary systems. The corresponding data in a single system demonstrated that ZIF‐[Co(eIm) 2 ] showed good adsorption performance for BCAA and poor for AAA. Furthermore, the adsorption behaviour under experimental conditions conformed well to the pseudo‐second‐order kinetic model and Langmuir isotherm. ZIF‐[Co(eIm) 2 ] had great separation ability for BCAA/AAA in their binary system. Finally, regeneration studies further manifested that ZIF‐[Co(eIm) 2 ] exhibited fine reusability performance with adsorption efficiencies still higher than 70% after five cycles. This study exhibits a novel path for the design of adsorbents for efficient separation of BCAA/AAA.
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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) | 0.000 | 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 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".