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Record W6981460356

Electron detachment and fragmentation of laser-excited rotationally hot Al<sub>4</sub><sup>−</sup>

2015· article· en· W6981460356 on OpenAlexaff

Bibliographic record

VenueMax Planck Digital Library · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicByzantine Studies and History
Canadian institutionsInstitute of Particle Physics
Fundersnot available
KeywordsFragmentation (computing)IonizationIonElectronElectron ionizationAdiabatic processElectron capturePhoton energy
DOInot available

Abstract

fetched live from OpenAlex

Absolute photoabsorption cross sections of negatively charged tetra-atomic aluminum clusters have been measured for photon energies between 1.8 and 2.7 eV. The experiment used the depletion technique in combination with an electrostatic ion-beam trap, in which Al4−ions produced in a sputter ion source were stored for 90 ms before being subjected to a short laser pulse. Moreover, the competition between one-atom fragmentation and electron emission of the laser-excited Al4− has been measured. These measurements show that fragmentation dominates electron emission at all photon energies below the electron attachment energy of ∼2.2 eV, even though the fragmentation energy is expected to be 10%–20% higher than the electron attachment energy. These findings, when taken together with the delayed-electron and fragmentation yields observed in a previous measurement [O. Aviv et al., Phys. Rev. A 83, 023201 (2011)], can be well explained within the statistical phase-space theory for unimolecular decays assuming the Al4− ions to be rotationally hot. The analysis permits the determination of the adiabatic electron detachment energy of Al4− to be Ead=(2.18±0.02) eV and the one-atom fragmentation energy to be D0=(2.34±0.05) eV. Moreover, two direct s-wave ionization channels are observed with threshold energies of (2.18±0.02) eV and (2.45±0.02) eV.

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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.013
GPT teacher head0.190
Teacher spread0.176 · 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
Published2015
Admission routes1
Has abstractyes

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