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Record W4415664861 · doi:10.1021/acscatal.5c03678

Electrodeposited Films of Manganese–Bipyridine Complexes for Aqueous Electrochemical CO <sub>2</sub> Reduction

2025· article· en· W4415664861 on OpenAlexaff
Israel Silva, Po Ching Hsu, Rodrigo Cruz-Ceja, Jeremiah C. Choate, Marcos Gil‐Sepulcre, G. K. Surya Prakash, Serena DeBeer, Olaf Ruediger, Smaranda C. Marinescu

Bibliographic record

VenueACS Catalysis · 2025
Typearticle
Languageen
FieldEnergy
TopicCO2 Reduction Techniques and Catalysts
Canadian institutionsCarbon Engineering (Canada)
FundersH2020 Marie Skłodowska-Curie ActionsUniversity of Southern CaliforniaAlexander von Humboldt-StiftungMax-Planck-GesellschaftNational Science Foundation
KeywordsFormateBulk electrolysisElectrocatalystElectrolysisCyclic voltammetryManganeseAqueous solutionCatalysisElectrochemistry

Abstract

fetched live from OpenAlex

The advancement and innovation of immobilized catalytic systems toward upscaling and improved stability for the efficient reduction of CO 2 have been a focal point in electrocatalysis research. Herein, the modification of carbon cloth electrodes is reported through the electropolymerization of a well-studied manganese bipyridine complex. A conjugated, polymeric network of manganese active sites is generated using diazonium ion chemistry, facilitating the conversion of CO 2 into highly valued C 1 products. Two variations of diamine manganese complexes are investigated by directing the film’s generated aryl radical polymer growth through surface attachment at either the 4,4′- or the 5,5′-substituent position of the respective bipyridine ligand. The functionalized electrodes were characterized via X-ray photoelectron spectroscopy (XPS) and various electrochemical measurements to determine the structure and electronic environment of the covalently anchored complexes. Electrolysis and cyclic voltammetry studies reveal the activity of the manganese devices in aqueous media for the production of syngas (CO and H 2 ) and formate (HCOO ¯ ), achieving turnover numbers (TON) of up to ∼8000 and electrolysis current densities of up to 10 mA/cm 2 .

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 score0.023
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.007
GPT teacher head0.248
Teacher spread0.241 · 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

Citations3
Published2025
Admission routes1
Has abstractyes

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