Tunable Polymeric Sorbent Materials for Fractionation of Model Naphthenates
Bibliographic record
Abstract
The sorption properties are reported for several examples of single-component carboxylic acids representing naphthenic acids (NAs) with β-cyclodextrin (β-CD) based polyurethane sorbents. Seven single-component examples of NAs were chosen with variable z values, carbon number, and chemical structure as follows: 2-hexyldecanoic acid (z = 0 and C = 16; S1), n-caprylic acid (z = 0 and C = 8; S2), trans-4-pentylcyclohexanecarboxylic acid (z = -2 and C = 12; S3), 4-methylcyclohexanecarboxylic acid (z = -2 and C = 8; S4), dicyclohexylacetic acid (z = -4; C = 14; S5), 4-pentylbicyclo[2.2.2]octane-1-carboxylic acid (z = -4; C = 14; S6), and lithocholic acid (z = -6; C = 24; S7). The copolymer sorbents were synthesized at three relative β-CD:diisocyanate mole ratios (i.e., 1:1, 1:2, and 1:3) using 4,4'-dicyclohexylmethane diisocyanate (CDI) and 4,4'-diphenylmethane diisocyanate (MDI). The sorption properties of the copolymer sorbents were characterized using equilibrium sorption isotherms in aqueous solution at pH 9.00 with electrospray ionization mass spectrometry. The equilibrium fraction of the unbound carboxylate anions was monitored in the aqueous phase. The sorption properties of the copolymer sorbents (i.e., Qm) were obtained from the Sips isotherm model. The Qm values generally decrease as the number of accessible β-CD inclusion sites in the copolymer framework decreases. The chemical structure of the adsorbates played an important role in their relative uptake, as evidenced by the adsorbate lipophilic surface area (LSA) and the involvement of hydrophobic effects. The copolymers exhibit molecular selective sorption of the single-component carboxylates in mixtures which suggests their application as sorbents for fractionation of mixtures of NAs. By comparison, granular activated carbon (GAC) and chitosan sorbents did not exhibit any significant molecular selective sorption relative to the copolymer materials; however, evidence of variable sorption capacity was observed among the sorbents investigated.
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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) | 0.001 | 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".