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Record W4241301340 · doi:10.26434/chemrxiv.14707233.v1

Simplifying and Expanding the Scope of Boron Imidazolate Framework (BIF) Synthesis Using Mechanochemistry

2021· preprint· en· W4241301340 on OpenAlexafffund
Cameron B. Lennox, Jean‐Louis Do, Joshua Crew, Mihails Arhangelskis, Hatem M. Titi, Ashlee J. Howarth, Omar K. Farha, Tomislav Friščić

Bibliographic record

VenueChemRxiv · 2021
Typepreprint
Languageen
FieldChemistry
TopicMetal-Organic Frameworks: Synthesis and Applications
Canadian institutionsConcordia UniversityMcGill UniversityFonds de Recherche du Québec – Nature et Technologies
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMechanochemistryImidazolatePorosityDensity functional theoryBoron nitrideBoronMaterials scienceScope (computer science)Chemical engineeringAdsorptionNanotechnologyComputational chemistryChemistryPhysical chemistryComputer scienceEngineeringComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

Mechanochemistry enables rapid access to boron imidazolate frameworks (BIFs), including ultralight materials based on Li and Cu(I) nodes, as well as new and previously unexplored systems based on Ag(I) nodes. Compared to solution methods, mechanochemistry is faster, provides materials with improved porosity, and replaces harsh reactants (e.g. n-butyllithium) with simpler and safer oxides, carbonates or hydroxides. Periodic density-functional theory (DFT) calculations on polymorphic pairs of BIFs based on Li + , Cu + , and Ag + nodes reveals that heavy-atom nodes increase the stability of the open SOD-framework relative to the non-porous dia -polymorph.

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 score0.002
Threshold uncertainty score0.006

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.037
GPT teacher head0.287
Teacher spread0.249 · 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

Citations0
Published2021
Admission routes2
Has abstractyes

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