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Record W2959524987 · doi:10.1002/anie.201906755

Mechanochemistry for Synthesis

2019· review· en· W2959524987 on OpenAlexafffund
Tomislav Friščić, Cristina Mottillo, Hatem M. Titi

Bibliographic record

VenueAngewandte Chemie International Edition · 2019
Typereview
Languageen
FieldChemistry
TopicCrystallography and molecular interactions
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMechanochemistryMaterials scienceNanotechnology

Abstract

fetched live from OpenAlex

Mechanochemical solvent-free reactions by milling, grinding or other types of mechanical action have emerged as a viable alternative to solution chemistry. Mechanochemistry offers not only a possibility to eliminate the need for bulk solvent use, and reduce the generation of waste, but it also unlocks the door to a different reaction environment in which synthetic strategies, reactions and molecules previously not accessible in solution, can be achieved. This Minireview examines the potential of mechanochemistry in chemical and materials synthesis, by providing a cross-section of the recent developments in using ball milling for the formation of molecules and materials based on covalent and coordination bonds.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.027
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0270.027

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 head0.047
GPT teacher head0.332
Teacher spread0.285 · 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 designNot applicable
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

Citations1,090
Published2019
Admission routes2
Has abstractyes

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