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Record W2889643732 · doi:10.1002/adma.201801790

Plasmonic Chirality and Circular Dichroism in Bioassembled and Nonbiological Systems: Theoretical Background and Recent Progress

2018· review· en· W2889643732 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAdvanced Materials · 2018
Typereview
Languageen
FieldMaterials Science
TopicMetamaterials and Metasurfaces Applications
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNational Key Research and Development Program of ChinaChina Postdoctoral Science FoundationNational Natural Science Foundation of ChinaFundamental Research Funds for the Central UniversitiesVolkswagen Foundation
KeywordsPlasmonChirality (physics)Circular polarizationMetamaterialCircular dichroismNanotechnologyMaterials sciencePhotonicsPolarization (electrochemistry)Plasmonic nanoparticlesPhysicsOpticsOptoelectronicsChemistrySymmetry breakingQuantum mechanics

Abstract

fetched live from OpenAlex

Nature is chiral, thus chirality is a key concept required to understand a multitude of systems in physics, chemistry, and biology. The field of optics offers valuable tools to probe the chirality of nanosystems, including the measurement of circular dichroism, the differential interaction strength between matter and circularly polarized light with opposite helicity. Simultaneously, the use of plasmonic systems with giant light-interaction cross-sections opens new paths to investigate and manipulate systems on the nanoscale. Consequently, the interest in chiral plasmonic and hybrid systems has continually grown in recent years, due to their potential applications in biosensing, polarization-encoded optical communication, polarization-selective chemical reactions, and materials with polarization-dependent light-matter interaction. Experimentally, chiral properties of nanostructures can be either created artificially using modern fabrication techniques involving inorganic materials, or borrowed from nature using bioassembly or biomolecular templating. Herein, the recent progress in the field of plasmonic chirality is summarized, with a focus on both the theoretical background and the experimental advances in the study of chirality in various systems, including molecular-plasmonic assemblies, chiral plasmonic nanostructures, chiral assemblies of interacting plasmonic nanoparticles, and chiral metal metasurfaces and metamaterials. The growth prospects of this field are also discussed.

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.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.938
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.072
GPT teacher head0.365
Teacher spread0.293 · 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