Studies of Laser Ablation of Liquid Water Under Conditions of Impulsive Heat Deposition Through Vibrational Excitations (IHDVE)
Bibliographic record
Abstract
A new laser ablation mechanism of liquid water based on recent insights into its hydrogen bond dynamics has been studied and several applications of the ablation demonstrated. The mechanism, termed as Impulsive Heat Deposition through Vibrational Excitations (IHDVE), is based on the ability of the hydrogen bond network of water to rapidly thermalize vibrational O-H stretch excitations on a time scale of several picoseconds even for excitation intensities that are large enough to bring excited volumes far into the supercritical region. In this way, by using vibrationally resonant picosecond infrared laser pulses with sufficient energy, it is possible to drive ultrafast phase transitions in the excited water volume leading to a rapid and efficient ablation process of water and water rich targets with minimum perturbation of solute molecules of interest. The physics behind the IHDVE ablation process is outlined and the benefits of the IHDVE ablation are demonstrated for two important applications of tissue cutting and mass spectrometry of biomolecules. Finally, the development of two high power infrared laser systems suitable for the practical implementation of IHDVE is presented.
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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 | 0.000 |
| 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".