Development of a frequency-modulated photoacoustic microscope system for thermal imaging using a picosecond laser
Bibliographic record
Abstract
This work uses a picosecond pulsed laser in frequency-domain photoacoustic microscopy (FDPAM) for thermal imaging of the sample. It uses the principle of the frequency-domain photoacoustic (PA) spectroscopy employed for trace gas detection relying on the thermal effect caused by the absorbance of the sequence of picosecond pulses. The thermal effect is modulated to a periodic thermal wave using a mechanical optical chopper. The PA signal caused by the thermal wave is measured by a PA sensor containing a microphone connected to a lock-in amplifier. The FDPAM uses a high repetitive (100 kHz, 500 ps) picosecond pulsed laser, a kHz frequency microphone, a chopper, and a lock-in amplifier. The system is tested using a USAF resolution chart. The system imaged a chrome metal strip of thickness 120 nm and width 3.1 µm of a USAF chart. The system exhibits a PA signal with a maximum amplitude of 2x10-4 V for a modulation frequency of 760 Hz. The signal is about four times lower than those obtained (8 x10-4) by a 532 nm CW laser of power 3 mW. The SNR of the system for the USAF chart is 5.5 dB. The system has a lateral resolution of 3.1 µm. The imaging resolution of the system can be improved by using an objective with a lower f-number.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".