Rheological and microrheological measurements of soft condensed matter
Bibliographic record
Abstract
Introduction Fluids deform irreversibly under shear; in other words, they flow. In contrast, solids deform elastically when subjected to a small shearing force and recover their original shape when the force is removed. The behavior of what is termed soft matter is somewhere in between. Soft matter systems are typically viscoelastic, that is they display a combination of viscous (fluid-like) and elastic (solid-like) behavior. Measuring the flow behavior and the mechanical response to deformation of viscoelastic materials provides us with information that can be interpreted in terms of their small-scale structure and dynamics. The mechanical properties of soft materials depend on the length scale probed by the measurements due to the fact that the materials are structured on length scales intermediate between the atomic and bulk scales [1]. For example, a colloidal suspension has structure on the scale of the spacing between the colloidal particles; a concentrated polymer system, on the scale of the entanglements between large molecules. As a result, their bulk properties can be quite different from properties on length scales smaller than or comparable to the structural scale. Making measurements on both macroscopic and microscopic length scales can help us to develop a better understanding of the relationship between microstructure and bulk properties in soft materials. Following a brief introduction to viscoelasticity, this chapter will focus on two methods of measuring the viscoelastic properties of soft matter. On the macroscopic scale, rotational shear rheometry provides a well-established set of techniques for determining the mechanical properties of complex fluids.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".