Spectroscopic and Thermodynamic Study of Biopolymer Adsorption Phenomena in Heterogeneous Solid–Liquid Systems
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Bibliographic record
Abstract
Molecular selective adsorption processes at the solid surface of biopolymers in mixed solvent systems are poorly understood due to manifold interactions. However, the ability to achieve adsorptive fractionation of liquid mixtures is posited to relate to the role of specific solid-liquid interactions at the adsorbent interface. The hydration of solid biopolymers (amylose, amylopectin, cellulose) in binary aqueous systems is partly governed by the relative solvent binding affinities with the biopolymer surface sites, in accordance with the role of textural and surface chemical properties. While molecular models that account for the surface area and solvent effects provide reliable estimates of hydration energy and binding affinity parameters, spectroscopic and thermal methods offer a facile alternative experimental approach to account for detailed aspects of solvation phenomena at biopolymer interfaces that involve solid-liquid adsorption. In this report, thermal and spectroscopic methods were used to understand the interaction of starch- and cellulose-based materials in water-ethanol (W-E) binary mixtures. Batch adsorption studies in binary W-E mixtures reveal the selective solvent uptake properties by the biomaterials, in agreement with their solvent swelling in pure water or ethanol. The nature, stability of the bound water, and the thermodynamic properties of the biopolymers in variable hydration states were probed via differential scanning calorimetry and Raman spectroscopy. The trends in biopolymer-solvent interactions are corroborated by dye adsorption and scanning electron microscopy, indicating that biopolymer adsorption properties in W-E mixtures strongly depend on the surface area, pore structure, and accessibility of the polar surface groups of the biopolymer systems, in agreement with the solvent-selective uptake results reported herein.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it