MACROPOROUS POLYETHYLENIMINE GEL-COATED ON ACRYLONITRILE-DIVINYLBENZENE COPOLYMER: A GRANULAR SORBENT OF HIGH CAPACITY AND FAST KINETICS
Bibliographic record
Abstract
Gel coating of polyethylenimine (PEI) resin was performed on macroporous polyacrylonitrile (PAN) granules by a Cu(II)-mediated chemical process, which can be easily extended to any type of PAN substrate, including fibers, fabrics, and films. The process, named CR Process of Gel Coating, has been modified in the present work for imparting a high degree of macroporosity to the gel coat to enhance the sorption kinetics and to improve resistance to organic fouling. The process produces a thin, firm coating of PEI that is cross-linked with glutaraldehyde and rendered macroporous by acid decomposition of pre-deposited CaCO3 on a PAN substrate that has been chemically modified a priori by limited hydrolysis with NaO-HH2O2. Designated as HYPAN(Na+). [PEI.XG], the gel-coated granular, macroporous sorbent affords nearly full attainment of the theoretical proton capacity of the coated resin and exhibits significantly faster attainment of equilibrium sorption than does the conventional bead-form ion exchanger. p-Toluenesulfonic acid (PTSA) and CuSO4 were used as test sorbates for comparing the performance of the gel-coated sorbent with Reillex 425, a commercial poly(4-vinylpyridine) (PVP) resin. In sorbate solutions of relatively low concentration (<2 mmol/L), the gel-coated sorbent had 2 to 3 times higher sorption of PTSA and Cu(II) than did the PVP resin beads. Large differences were also observed in sorption rates of gel-coated beads and conventional whole-resin beads. Thus, under similar conditions, the initial rate of attainment of equilibrium sorption on HYPAN(Na+).[PEI.XG] was nearly twice that on PVP in both PTSA and CuSO4 solutions. Application of the shell-core model equation to the initial sorption rate data yields for the gel-coated particles diffusivity values that are 2 to 3 times higher than those obtained for PVP resin beads. *On leave from Indian Institute of Science, Bangalore, India.
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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 | 0.001 |
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".