Acoustic and photoacoustic characterization of micron-sized perfluorocarbon emulsions
Bibliographic record
Abstract
<p> Perfluorocarbon droplets containing nanoparticles (NPs) have recently been investigated as theranostic and dual-mode contrast agents. These droplets can be vaporized via laser irradiation or used as photoacoustic contrast agents below the vaporization threshold. This study investigates the photoacoustic mechanism of NP-loaded droplets using photoacoustic frequencies between 100 and 1000 MHz, where distinct spectral features are observed that are related to the droplet composition. The measured photoacoustic spectrum from NP-loaded perfluorocarbon droplets was compared to a theoretical model that assumes a homogenous liquid. Good agreement in the location of the spectral features was observed, which suggests the NPs act primarily as optical absorbers to induce thermal expansion of the droplet as a single homogenous object. The NP size and composition do not affect the photoacoustic spectrum; therefore, the photoacoustic signal can be maximized by optimizing the NP optical absorbing properties. To confirm the theoretical parameters in the model, photoacoustic, ultrasonic, and optical methods were used to estimate the droplet diameter. Photoacoustic and ultrasonic methods agreed to within 1.4%, while the optical measurement was 8.5% higher; this difference decreased with increasing droplet size. The small discrepancy may be attributed to the difficulty in observing the small droplets through the partially translucent phantom. </p>
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".