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Record W4401001026 · doi:10.26434/chemrxiv-2024-df783

Chiral Symmetry Breaking in Colloidal Metal Nanoparticle Solutions by Circularly Polarized Light

2024· preprint· en· W4401001026 on OpenAlexaff
Monika Ghalawat, Daniel Feferman, Lucas V. Besteiro, Wanting He, Artur Movsesyan, Jesús Valdez, Audrey Moores, Zhiming Wang, Dongling Ma, Alexander O. Govorov, Gil Markovich

Bibliographic record

VenueChemRxiv · 2024
Typepreprint
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsMcGill UniversityInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsSymmetry breakingCircular polarizationPlasmonNanoparticleMaterials scienceColloidPolarization (electrochemistry)Molecular physicsPlasmonic nanoparticlesSpontaneous symmetry breakingChemical physicsOpticsPhysicsOptoelectronicsNanotechnologyChemistryQuantum mechanics

Abstract

fetched live from OpenAlex

Shape symmetry breaking in the formation of inorganic nanostructures is of large current interest. It was typically achieved through growth of colloidal nanoparticles with adsorbed chiral molecules. Photochemical processes induced through asymmetric plasmon excitation by circularly polarized light in surface immobilized nanostructures also led to symmetry breaking. Here we show that chiral symmetry breaking can be achieved on randomly rotating gold@silver core-shell nanobars in colloidal solution, by means of circularly polarized illumination, where orientational averaging does not eliminate the symmetry breaking of an asymmetric plasmon-induced galvanic replacement reaction. Different morphological effects that are produced by circularly vs. linearly polarized light illumination demonstrate the intricate effect of light polarization on the localized plasmonic-induced photochemical response. The symmetry breaking becomes smaller in more symmetric geometrical shapes such as triangular nanoprisms and nanocubes, down to zero in spherical ones. The symmetry breaking rises when the nanobars are immobilized on a substrate and illuminated from a single direction.

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 score0.002

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 communication0.0010.000
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 head0.019
GPT teacher head0.243
Teacher spread0.224 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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