Exploring extreme thermodynamics in nanoliter volumes through stimulated Brillouin-Mandelstam scattering
Bibliographic record
Abstract
Abstract Examining the physical properties of materials - particularly of toxic liquids - under a wide range of thermodynamic states is a challenging problem due to the extreme conditions the material has to be exposed to. Such temperature and pressure regimes, which result in a change of refractive index and sound velocity can be accessed by optoacoustic interactions such as Brillouin-Mandelstam scattering. Here we experimentally demonstrate Brillouin-Mandelstam measurements of nanoliter volumes of liquids in extreme thermodynamic regimes. We use a fully-sealed liquid-core optical fiber containing carbon disulfide; within this waveguide, which exhibits tight optoacoustic confinement and a high Brillouin gain of 32.2 ± 0.8 1/(Wm), we are able to conduct spatially resolved measurements of the Brillouin frequency shift. Knowledge of the local Brillouin response enables us to control the temperature and pressure independently over a wide range. We observe and measure the material properties of the liquid core at very large positive pressures (above 1000 bar), substantial negative pressures (below -300 bar) and we explore the isobaric and isochoric regimes. The extensive thermodynamic control allows the tunability of the Brillouin frequency shift of more than 40% using only minute volumes of liquid. This work opens the way for future studies of liquids under a variety of conventionally hard-to-reach conditions.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".