Experimental Determination of Single CdSe Nanowire Absorption Cross Sections through Photothermal Imaging
Bibliographic record
Abstract
Absorption cross sections ((sigma)abs) of single branched CdSe nanowires (NWs) have been measured by photothermal heterodyne imaging (PHI). Specifically, PHI signals from isolated gold nanoparticles (NPs) with known cross sections were compared to those of individual CdSe NWs excited at 532 nm. This allowed us to determine average NW absorption cross sections at 532 nm of (sigma)abs = (3.17 +/- 0.44) x 10(-11) cm2/microm (standard error reported). This agrees well with a theoretical value obtained using a classical electromagnetic analysis ((sigma)abs = 5.00 x 10(-11) cm2/microm) and also with prior ensemble estimates. Furthermore, NWs exhibit significant absorption polarization sensitivities consistent with prior NW excitation polarization anisotropy measurements. This has enabled additional estimates of the absorption cross section parallel ((sigma)abs) and perpendicular ((sigma)abs(perpendicular) to the NW growth axis, as well as the corresponding NW absorption anisotropy ((rho)abs). Resulting values of (sigma)abs = (5.6 +/- 1.1) x 10(-11) cm2/microm, (sigma)abs(perpendicular) = (1.26 +/- 0.21) x 10(-11) cm2/microm, and (rho)abs = 0.63+/- 0.04 (standard errors reported) are again in good agreement with theoretical predictions. These measurements all indicate sizable NW absorption cross sections and ultimately suggest the possibility of future direct single NW absorption studies.
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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 | 0.001 |
| 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 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".