Osmotic Virial Coefficients of Hydroxyethyl Starch from Aqueous Hydroxyethyl Starch–Sodium Chloride Vapor Pressure Osmometry
Bibliographic record
Abstract
Hydroxyethyl starch (HES) is an important industrial additive in the paper, textile, food, and cosmetic industries and has been shown to be an effective cryoprotectant for red blood cells; however, little is known about its thermodynamic solution properties. In many applications, in particular those in biology, HES is used in an aqueous solution with sodium chloride (NaCl). The osmotic virial solution thermodynamics approach accurately captures the dependence of osmolality on molality for many types of solutes in aqueous systems, including electrolytes, sugars, alcohols, proteins, and starches. Elliott et al. proposed mixing rules for the osmotic virial equation to be used for osmolality of multisolute aqueous solutions [Elliott, J. A. W.; et al. J. Phys. Chem. B 2007, 111, 1775-1785] and recently applied this approach to the fitting of one set of aqueous HES-NaCl solution data reported by Jochem and Körber [Cryobiology 1987, 24, 513-536], indicating that the HES osmotic virial coefficients are dependent on HES-to-NaCl mass ratios. The current study reports new aqueous HES-NaCl vapor pressure osmometry data which are analyzed using the osmotic virial equation. HES modifications were measured after dialysis (membrane cut off: 10,000 g/mol) and freeze-drying using vapor pressure osmometry at different mass ratios of HES to NaCl for HES up to 50% and NaCl up to 25% with three different HES modifications (weight average molecular weights [g/mol]/degree of substitution: 40,000/0.5; 200,000/0.5; 450,000/0.7). Equations were then fit to the data to provide a model for HES osmotic virial coefficient dependence on mass ratio of HES to NaCl. The osmolality data of the three HES modifications were accurately described over a broad range of HES-to-NaCl mass ratios using only four parameters, illustrating the power of the osmotic virial approach in analyzing complex data sets. As expected, the second osmotic virial coefficients increase with molecular weight of the HES and increase with HES-to-NaCl mass ratio.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".