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Record W2003377478 · doi:10.1039/c000359j

Vibrationally excited ultrafast thermodynamic phase transitions at the water/air interface

2010· article· en· W2003377478 on OpenAlexaff
Krešimir Franjić, R. J. Dwayne Miller

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpectroscopy and Quantum Chemical Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsExcited stateFluenceLaserNanosecondPicosecondAdiabatic processMaterials sciencePhase (matter)Ultrashort pulseMolecular physicsChemistryAtomic physicsOpticsThermodynamicsPhysics

Abstract

fetched live from OpenAlex

The extraordinary ability of the hydrogen-bond network of water in the condensed phase to thermalize vibrational excitations within several picoseconds, even under supercritical conditions, offers the possibility of creating highly excited thermodynamic states at water surfaces on ultrafast time scales using vibrationally resonant short infrared laser pulses. We experimentally and numerically studied such states created by depositing ~100 ps long pulses tuned to the 3400 cm(-1) O–H stretch vibration at the water/air interface using time-resolved dark-field imaging and time-resolved optical reflectivity. The results are reasonably well described by using a hydrodynamic ablation model under the assumption of impulsive heat deposition. The large thermoelastic stress amplitudes on the order of 1 GPa created within 100 ps by depositing laser pulses with ~1 J cm(-2) fluence were inferred from the numerical simulations. Stresses of this magnitude drive the excited water layer into a very fast expansion resulting in rapid adiabatic cooling and thorough vaporization within a few nanoseconds. The spatial and temporal lengths scales of the ablation plume are nearly ideal for ejecting molecules into the gas phase with minimum perturbation for applications ranging from mass spectrometry and laser surgery to the development of extremely high pressure molecular beams.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.006
GPT teacher head0.260
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations64
Published2010
Admission routes1
Has abstractyes

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