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Record W2800879134 · doi:10.1149/ma2018-01/28/1625

Enhanced CO<sub>2</sub> Electrochemical Conversion at Bi-Modified Pb Foams

2018· article· en· W2800879134 on OpenAlexaff
Daniel Guay, Mengyang Fan, Sébastien Garbarino, Gianluigi A. Botton, Ana C. Tavares

Bibliographic record

VenueECS Meeting Abstracts · 2018
Typearticle
Languageen
FieldEnergy
TopicCO2 Reduction Techniques and Catalysts
Canadian institutionsMcMaster UniversityInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsFormic acidFormateMethanolElectrochemistrySynthetic fuelElectrolyteChemical engineeringCatalysisMaterials scienceSyngasInorganic chemistryChemistryOrganic chemistryElectrode

Abstract

fetched live from OpenAlex

CO2 conversion methods to remediate anthropogenic emissions appear promising, as they offer the potential to produce liquid and gaseous fuels for use either in the aeronautics industry, or as a chemical storage method for intermittent energy produced by windmills and photovoltaic panels. Fuel synthesis may be achieved via either the production of a syngas mixture (H2 and CO) through the water gas shift reaction and subsequent conversion into hydrocarbon fuel, or by direct electrochemical reduction of CO2. Direct electrochemical conversion of CO2 into value-added products is a low-temperature process, with the advantage of requiring relatively simple equipment. Formic acid, or formate salts, are used in a variety of chemical processes such as electrowinning, leather tanning, and aircraft de-icing. Alternatively, formic acid and formate salts may be considered as a hydrogen storage medium. On top of that, direct formic acid, and more recently direct formate, fuel cells, have been investigated as they demonstrate significant benefits over methanol fuel cells, including higher open circuit voltage and lower crossover. Pb and Bi are promising catalysts with good selectivity for formate. In the case of lead, it can be prepared in the form of dendrites with nanometre-sized tips. Local high electric fields can exist at the tip of these dendrites that can induce a concentration of electrolytes which in turn leads to improve electroreduction of CO2 [[1]]. Bismuth is non-toxic and has negligible environmental impact. It has few commercial applications, and its price has been low and relatively stable in recent years. In this work, we studied the activity and stability for CO2 electroreduction onto high surface area metallic Pb films. The latter Pb films were further functionalized by Bi overlayers to enhance CO2 reduction properties. For both materials, the material films were prepared through a potentiostatic method. Both types of films were extensively characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), high-resolution transmission electron microscopy (HR-TEM) and x-ray diffraction (XRD), while electrochemical activities were characterized by cyclic voltammetry (CV), linear sweep voltammetry (LSV), and potentiostatic measurements. [1] M. Fang, S. Garbarino, G.A. Botton, A.C. Tavares and D. Guay, J. Mater. Chem A 5 (2017) 20747-20756

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 score0.005

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.011
GPT teacher head0.245
Teacher spread0.234 · 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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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