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Record W3080867929 · doi:10.1038/s41598-020-71069-9

Chiral discrimination by recollision enhanced femtosecond laser mass spectrometry

2020· article· en· W3080867929 on OpenAlexafffund
Jean-Luc Bégin, Maye Alsaawy, V. R. Bhardwaj

Bibliographic record

VenueScientific Reports · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Matter Interactions and Applications
Canadian institutionsUniversity of Ottawa
FundersCanada Research Chairs
KeywordsIonizationFemtosecondCircular dichroismChirality (physics)DipoleLaserMass spectrometryMolecular physicsIonExcited stateEnantiomerChemical physicsPhysicsChemistryAtomic physicsOpticsCrystallographyStereochemistry

Abstract

fetched live from OpenAlex

Chiral molecules and their interactions are critical in a variety of chemical and biological processes. Circular dichroism (CD) is the most widely used optical technique to study chirality, often performed in a solution phase. However, CD has low-efficiency on the order of 0.01-1[Formula: see text]. Therefore, there is a growing need to develop high-efficiency chiroptical techniques, especially in gas-phase, to gain background-free in-depth insight into chiral interactions. By using mass spectrometry and strong-field ionization of limonene with elliptically polarized light, we demonstrate an efficient chiral discrimination method that produces a chiral signal of one to two orders of magnitude higher than the conventional CD. The chiral response exhibits a strong dependence on wavelength in the range of 1,300-2,400 nm, where the relative abundance of the ion yields alternates between the two enantiomers. The origin of enhanced enantio-sensitivity in intense laser fields is attributed to two mechanisms that rely on the recollision dynamics in a chiral system: (1) the excited ionic state dynamics mediated either by the laser field or by the recollision process, and (2) non-dipole effects that alter the electron's trajectories. Our results can serve as a benchmark for testing and developing theoretical tools involving non-dipole effects in strong-field ionization of molecules.

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 categoriesInsufficient 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 score0.150
Threshold uncertainty score0.997

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.011
GPT teacher head0.253
Teacher spread0.242 · 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

Citations16
Published2020
Admission routes2
Has abstractyes

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