Quantifying the photothermal conversion efficiency of plasmonic nanoparticles by means of terahertz radiation
Bibliographic record
Abstract
The accurate determination of the photothermal response of nanomaterials represents an essential aspect in many fields, such as nanomedicine. Specifically, photothermal cancer therapies rely on the precise knowledge of the light-to-heat transfer properties of plasmonic nanoparticles to achieve the desired temperature-induced effects in biological tissues. In this work, we present a novel method for the quantification of the photothermal effect exhibited by nanoparticles in aqueous dispersions. By combining the spatial and temporal thermal dynamics acquired at terahertz frequencies, the photothermal conversion efficiency associated with the geometry of the plasmonic nanoparticles can be retrieved in a noncontact and noninvasive manner. The proposed technique can be extended to the characterization of all those nanomaterials which feature a temperature-dependent variation of the refractive index in the terahertz regime.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".