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Record W3165819635 · doi:10.1039/d0cs00918k

Mechanochemical methods for the transfer of electrons and exchange of ions: inorganic reactivity from nanoparticles to organometallics

2021· review· en· W3165819635 on OpenAlexafffund
Blaine G. Fiss, Austin J. Richard, Georgia Douglas, Monika Kojic, Tomislav Friščić, Audrey Moores

Bibliographic record

VenueChemical Society Reviews · 2021
Typereview
Languageen
FieldEngineering
TopicSurface Chemistry and Catalysis
Canadian institutionsMcGill UniversityCentre in Green Chemistry and Catalysis
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsReactivity (psychology)MechanochemistryNanoparticleChemistryElectron transferMetathesisIonNanotechnologyInorganic chemistryCombinatorial chemistryPhotochemistryOrganic chemistryMaterials science

Abstract

fetched live from OpenAlex

Mechanochemistry by milling, grinding, extrusion or other types of shear and mechanical agitation has shown novel reactivity for a wide range of reactions, not seen in traditional solution-based environments. While the area has been extensively investigated and reviewed in the context of organic and solid-state supramolecular chemistry, less attention has been given to the recent advances in the context of inorganic transformations. Here we provide a perspective of inorganic mechanochemical reactions, focusing on transformations that are based on transfer of charged species: exchange of ions and electrons (redox reactions). These types of mechanochemical transformations typically lead to the formation of new nanoparticles and organometallic complexes. Herein, we provide an overview of mechanochemical reactivity that complements the recent developments in organic synthesis and catalysis.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.472
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
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 head0.060
GPT teacher head0.345
Teacher spread0.284 · 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
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

Citations61
Published2021
Admission routes2
Has abstractyes

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