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Record W3018326793 · doi:10.1002/anie.202004501

Stable Actinide π Complexes of a Neutral 1,4‐Diborabenzene

2020· article· en· W3018326793 on OpenAlexafffund
Valerie Paprocki, Peter Hrobárik, Katie L. M. Harriman, Martin S. Luff, Thomas Kupfer, Martin Kaupp, Muralee Murugesu, Holger Braunschweig

Bibliographic record

VenueAngewandte Chemie International Edition · 2020
Typearticle
Languageen
FieldChemistry
TopicOrganometallic Complex Synthesis and Catalysis
Canadian institutionsUniversity of Ottawa
FundersH2020 European Research CouncilNatural Sciences and Engineering Research Council of Canada
KeywordsActinideChemistryLigand (biochemistry)ThoriumMetalUraniumComputational chemistryGroup 2 organometallic chemistryBlock (permutation group theory)StereochemistryMoleculeCombinatorial chemistryCrystallographyInorganic chemistryMaterials scienceOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract The π coordination of arene and anionic heteroarene ligands is a ubiquitous bonding motif in the organometallic chemistry of d‐block and f‐block elements. By contrast, related π interactions of neutral heteroarenes including neutral bora‐π‐aromatics are less prevalent particularly for the f‐block, due to less effective metal‐to‐ligand backbonding. In fact, π complexes with neutral heteroarene ligands are essentially unknown for the actinides. We have now overcome these limitations by exploiting the exceptionally strong π donor capabilities of a neutral 1,4‐diborabenzene. A series of remarkably robust, π‐coordinated thorium(IV) and uranium(IV) half‐sandwich complexes were synthesized by simply combining the bora‐π‐aromatic with ThCl 4 (dme) 2 or UCl 4 , representing the first examples of actinide complexes with a neutral boracycle as sandwich‐type ligand. Experimental and computational studies showed that the strong actinide–heteroarene interactions are predominately electrostatic in nature with distinct ligand‐to‐metal π donation and without significant π/δ backbonding contributions.

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 categoriesInsufficient payload (model declined to judge)
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 score0.136
Threshold uncertainty score0.966

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0350.000

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 head0.028
GPT teacher head0.249
Teacher spread0.221 · 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
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

Citations19
Published2020
Admission routes2
Has abstractyes

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