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Record W2076371629 · doi:10.1063/1.3429884

Theory of the optical spatial separation of racemic mixtures of chiral molecules

2010· article· en· W2076371629 on OpenAlexafffund
Xuan Li, Moshe Shapiro

Bibliographic record

VenueThe Journal of Chemical Physics · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicCold Atom Physics and Bose-Einstein Condensates
Canadian institutionsUniversity of British Columbia
FundersUniversity of British Columbia
KeywordsRacemic mixtureEnantiomerDipoleLaserMoleculeAdiabatic processMolecular physicsQuantumChirality (physics)ChemistrySpatial configurationMatrix (chemical analysis)Chemical physicsAtomic physicsMaterials scienceOpticsPhysicsStereochemistryQuantum mechanicsOrganic chemistryChiral symmetry

Abstract

fetched live from OpenAlex

We propose a practical way of spatially separating a ("racemic") mixture of left-handed (L) and right-handed (R) chiral molecules using optically induced forces. The enantioselectivity of the method emanates from the sign difference between the n<-->m electric-dipole matrix elements of enantiomers of opposite handedness, and the, uniquely chiral, "cyclic adiabatic passage" laser configuration. The combination of these two factors is shown to cause considerable differences in the magnitude and direction of the optically induced forces as felt by enantiomers of opposite handedness. Two arrangements, tested by performing quantum wave packet propagation and classical trajectories, are suggested. Both arrangements involve the intracavity interaction of the racemic mixture with three, partially overlapping, cw laser beams. The first arrangement is composed of trapped molecules at 1 mK interacting with standing wave lasers. The second configuration uses a tightly skimmed molecular beam of a racemic mixture, forming one arm of a four-sided cavity, intersecting at a small angle the three laser 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 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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.241
Teacher spread0.235 · 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 designTheoretical or conceptual
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

Citations72
Published2010
Admission routes2
Has abstractyes

Explore more

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