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Real-Time Electron Solvation Induced by Bursts of Laser-Accelerated Protons in Liquid Water

2021· preprint· en· W3177751816 on OpenAlexfundno aff
Alexander Prasselsperger, M. Coughlan, N. Breslin, M. Yeung, Christine Arthur, H. Donnelly, S. White, Masoud Afshari, Martin Speicher, Rong Yang, Balder Villagomez‐Bernabe, F. J. Currell, J. Schreiber, B. Dromey

Bibliographic record

VenuePhysical Review Letters · 2021
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicLaser-Plasma Interactions and Diagnostics
Canadian institutionsnot available
FundersLudwig-Maximilians-Universität MünchenQueen's UniversityEngineering and Physical Sciences Research CouncilDeutsche Forschungsgemeinschaft
KeywordsSolvationProtonSolvated electronRadiolysisPicosecondElectronAtomic physicsChemical physicsLiquid waterLaserChemistryPhysicsNuclear physicsIonIrradiationOpticsThermodynamics

Abstract

fetched live from OpenAlex

Understanding the mechanisms of proton energy deposition in matter and subsequent damage formation is fundamental to radiation science. Here we exploit the picosecond (10^{-12} s) resolution of laser-driven accelerators to track ultrafast solvation dynamics for electrons due to proton radiolysis in liquid water (H_{2}O). Comparing these results with modeling that assumes initial conditions similar to those found in photolysis reveals that solvation time due to protons is extended by >20 ps. Supported by magnetohydrodynamic theory this indicates a highly dynamic phase in the immediate aftermath of the proton interaction that is not accounted for in current models.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.300
Teacher spread0.283 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2021
Admission routes1
Has abstractyes

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