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Record W3035438889 · doi:10.1021/acs.jpcc.0c03871

Shapes, Plasmonic Properties, and Reactivity of Magnesium Nanoparticles

2020· review· en· W3035438889 on OpenAlexfundno aff
Emilie Ringe

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2020
Typereview
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsnot available
FundersFonds de recherche du Québec – Nature et technologiesH2020 European Research CouncilEngineering and Physical Sciences Research CouncilNatural Sciences and Engineering Research Council of Canada3M
KeywordsPlasmonNanoparticleMaterials scienceSurface plasmon resonanceSurface plasmonNanotechnologyChemical physicsOptoelectronicsChemistry

Abstract

fetched live from OpenAlex

Localized surface plasmon resonances have attracted much attention due to their ability to enhance light-matter interactions and manipulate light at the subwavelength level. Recently, alternatives to the rare and expensive noble metals Ag and Au have been sought for more sustainable and large-scale plasmonic utilization. Mg supports plasmon resonances, is one of the most abundant elements in earth's crust, and is fully biocompatible, making it an attractive framework for plasmonics. This feature article first reports the hexagonal, folded, and kite-like shapes expected theoretically from a modified Wulff construction for single crystal and twinned Mg structures and describes their excellent match with experimental results. Then, the optical response of Mg nanoparticles is overviewed, highlighting Mg's ability to sustain localized surface plasmon resonances across the ultraviolet, visible, and near-infrared electromagnetic ranges. The various resonant modes of hexagons, leading to the highly localized electric field characteristic of plasmonic behavior, are presented numerically and experimentally. The evolution of these modes and the associated field from hexagons to the lower symmetry folded structures is then probed, again by matching simulations, optical, and electron spectroscopy data. Lastly, results demonstrating the opportunities and challenges related to the high chemical reactivity of Mg are discussed, including surface oxide formation and galvanic replacement as a synthetic tool for bimetallics. This Feature Article concludes with a summary of the next steps, open questions, and future directions in the field of Mg nanoplasmonics.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.244
Threshold uncertainty score0.312

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.048
GPT teacher head0.264
Teacher spread0.217 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreReview

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

Citations99
Published2020
Admission routes1
Has abstractyes

Explore more

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