Laser selective cutting of biological tissues by impulsive heat deposition through ultrafast vibrational excitations
Bibliographic record
Abstract
Mechanical and thermodynamic responses of biomaterials after impulsive heat deposition through vibrational excitations (IHDVE) are investigated and discussed. Specifically, we demonstrate highly efficient ablation of healthy tooth enamel using 55 ps infrared laser pulses tuned to the vibrational transition of interstitial water and hydroxyapatite around 2.95 microm. The peak intensity at 13 GW/cm(2) was well below the plasma generation threshold and the applied fluence 0.75 J/cm(2) was significantly smaller than the typical ablation thresholds observed with nanosecond and microsecond pulses from Er:YAG lasers operating at the same wavelength. The ablation was performed without adding any superficial water layer at the enamel surface. The total energy deposited per ablated volume was several times smaller than previously reported for non-resonant ultrafast plasma driven ablation with similar pulse durations. No micro-cracking of the ablated surface was observed with a scanning electron microscope. The highly efficient ablation is attributed to an enhanced photomechanical effect due to ultrafast vibrational relaxation into heat and the scattering of powerful ultrafast acoustic transients with random phases off the mesoscopic heterogeneous tissue structures.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".