Do Polysaccharides Such as Dextran and Their Monomers Really Increase the Surface Tension of Water?
Bibliographic record
Abstract
It has been reported in the literature that sugars such as dextrose and sucrose increase the surface tension of water. The effect was interpreted as a depletion of the solute molecules from the water-air interface. This paper presents accurate measurements of the surface tension of different concentrations of dextrose solution as well as its polymer (i.e., dextran). An automated drop shape technique called axisymmetric drop shape analysis (ADSA) was used for the surface tension determination. The surface tension measurement is presented as a function of a shape parameter, P(s), which has been used to quantify the range of the applicability of ADSA. The results of the above study show that dextrose solutions decrease the surface tension of water in contradiction to the results obtained from the weight drop method in the literature. The surface tension decreases continuously with increasing concentration. A similar effect was observed for the dextran solutions. To verify that the setup and the methodology are capable of accurately measuring increases in surface tension, a similar experiment was conducted with a sodium chloride solution with a concentration of 1 M. It is well-known that electrolyte solutions, e.g., sodium chloride, increase the surface tension of water. The results obtained from ADSA verify that the sodium chloride increases the surface tension of water by 1.6 mJ/m(2). It is concluded that dextrose and dextran decrease the surface tension of water. Thus, there is no evidence of depletion. To identify the sources of discrepancy between the results of ADSA and those reported in the literature, the experiments were repeated for different concentrations and the rate of drop formation using the drop weight method. It was found that the rate of drop formation is most likely the source of error in the results reported in the literature.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".