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Record W4404143985 · doi:10.26434/chemrxiv-2024-z5rtb

Rapid and selective formic acid dehydrogenation catalysis by molecular ruthenium hydrides supported by rigid PCcarbeneP pincer ligands

2024· preprint· en· W4404143985 on OpenAlexafffund
Laurie J. Donnelly, Warren E. Piers, Benjamin S. Gelfand

Bibliographic record

VenueChemRxiv · 2024
Typepreprint
Languageen
FieldChemical Engineering
TopicCarbon dioxide utilization in catalysis
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsPincer movementDehydrogenationRutheniumFormic acidCatalysisChemistryCombinatorial chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

A series of four molecular ruthenium hydrido complexes supported by previously reported rigid PCcarbeneP pincer ligand frameworks were evaluated as formic acid dehydrogenation (FAD) catalysts. The ligands in the complexes LRRu(H)X (R = H, NMe2; X = Cl, kappa-2-O2CH) differ in the electron richness by substitution on the aryl groups linking the di-iso-propylphosphine arms to the central carbene donor. We find that only the unsubstituted (R = H) chloro and formato complexes are effective catalyst precursors; the NMe2 substituted derivatives decompose under catalytic conditions. However, the two compounds LHRu(H)X are highly active (TOF = 1300-4200 h-1), long lived (TON up to 122 000) and selective (dihydrogen and carbon dioxide are the sole products) at 21˚C with no base additives necessary in 13M formic acid in water/dioxane. These performance metrics compare well with state of the art catalysts operating under ambient conditions. Mechanistic experiments support a simple two-step mechanism involving rate limiting protonolysis of the Ru-H by formic acid to release H2 and rapid loss of CO2 via -elimination from the resulting formato complex. This second step is facilitated kinetically because the donor properties of the X ligands lower the barrier to formation of the 1 binding mode for the formato ligand, needed to access the -elimination transition state for CO2 loss. Structural and DFT studies support this notion.

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 categoriesMeta-epidemiology (narrow)
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 score0.040
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
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 head0.006
GPT teacher head0.222
Teacher spread0.216 · 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

Citations0
Published2024
Admission routes2
Has abstractyes

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