Dual Beam Light Profile Microscopy: A New Technique for Optical Absorption Depth Profilometry
Bibliographic record
Abstract
Light profile microscopy (LPM) is a recently developed technique of optical inspection that is used to record micrometer-scale images of thin-film cross-sections on a direct basis. In single beam mode, LPM provides image contrast based on luminescence, elastic, and/or inelastic scatter. However, LPM may also be used to depth profile the optical absorption coefficient of a thin film based on a method of dual beam irradiation presented in this work. The method uses a pair of collimated laser beams to consecutively irradiate a film from two opposing directions along the depth axis. An average profile of the beam's light intensity variation through the material is recovered for each direction and used to compute a depth-dependent differential absorbance profile. This latter quantity is shown from theory to be related to the film's depth-dependent optical absorption coefficient through a simple linear model that may be inverted by standard methods of numerical linear algebra. The inverse problem is relatively well posed, showing good immunity to data errors. This profilometry method is experimentally applied to a set of well-characterized materials with known absorption properties over a scale of tens of micrometers, and the reconstructed absorption profiles were found to be highly consistent with the reference data.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".