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Record W2725419163 · doi:10.1149/ma2017-02/45/1990

(Keynote) Formate/Formic Acid Synthesis from CO<sub>2</sub> Electroduction Using Bi and Pb Nanostructures

2017· article· en· W2725419163 on OpenAlexaff
Daniel Guay, Erwan Bertin, Mengyang Fan, Sébastien Garbarino, Ana P. M. Tavares, Claudie Roy, Sona Kazemi, Gianluigi A. Botton

Bibliographic record

VenueECS Meeting Abstracts · 2017
Typearticle
Languageen
FieldChemical Engineering
TopicCarbon dioxide utilization in catalysis
Canadian institutionsMcMaster UniversityBC Research (Canada)Institut National de la Recherche Scientifique
Fundersnot available
KeywordsFormic acidFormateSynthetic fuelEnvironmental scienceSyngasChemical industryEnvironmental chemistryPulp and paper industryCatalysisWaste managementChemistryMaterials scienceEnvironmental engineeringOrganic chemistry

Abstract

fetched live from OpenAlex

The rise in atmospheric CO 2 concentration since the beginning of the Industrial Age has raised concerns on its potential effect on global temperatures. While several factors such as natural climate changes, variations in solar activity, and volcanic eruptions may also contribute to observed variations in CO 2 concentrations, it has been well established that anthropogenic emissions contribute to the annual emission of over 30 billion tonnes of CO 2 , only about half of which is recycled through natural pathways. CO 2 conversion into value-added products is an avenue explored to mitigate environmental issues. Conversion methods 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 the intermittent energy produced by windmills and photovoltaic panels. Fuel synthesis may be achieved via either the production of a syngas mixture (H 2 and CO) through the water gas shift reaction and subsequent conversion into hydrocarbon fuel through processes such as Fisher-Tropsch, or by direct electrochemical reduction of CO 2 . While all methods may result in similar conversion yields, depending on the catalyst used, direct electrochemical conversion of CO 2 into value-added products is a low-temperature process, with the further 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 a hydrogen storage medium. Direct formic acid, and more recently, direct formate fuel cells, have been investigated in the literature 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. 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 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 electrolyte which in turn leads to a high local concentrations of CO 2 . In this study, we compared the activity and stability for CO 2 electroreduction of high surface area metallic Bi and Pb films. In both cases, the materials films were prepared through a direct electrodeposition (potentiostatic method). Both types of films were extensively characterised 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. Figure 1

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)0.002
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 score0.006
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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 integrity0.0000.000
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 head0.013
GPT teacher head0.239
Teacher spread0.226 · 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
Published2017
Admission routes1
Has abstractyes

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