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Record W3024692322 · doi:10.1149/ma2020-01361484mtgabs

Electrochemically Enhancing Nanostructured Fe-Oxide/Co<sub>3</sub>O<sub>4 </sub>for the Reverse Water Gas Shift Reaction

2020· article· en· W3024692322 on OpenAlexaff
Christopher Panaritis, Martin Couillard, Elena A. Baranova

Bibliographic record

VenueECS Meeting Abstracts · 2020
Typearticle
Languageen
FieldEnergy
TopicIron oxide chemistry and applications
Canadian institutionsNational Research Council CanadaUniversity of Ottawa
Fundersnot available
KeywordsWater-gas shift reactionCatalysisOxideCarbon monoxideChemical engineeringMaterials scienceCobalt oxideHydrogenSyngasOxygenCarbon fibersInorganic chemistryNanotechnologyChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The abundant amount of CO 2 in the atmosphere is a valuable resource that when managed correctly can replace energy from the fossil fuel industry and provide a carbon-neutral solution that will reduce the impacts of the climate and ecological crisis[1]. This is achieved by reducing CO 2 with hydrogen (H 2 ) through the reverse water gas shift (RWGS) reaction to produced carbon monoxide (CO). CO then acts as a source molecule in the Fischer-Tropsch synthesis to manufacture hydrocarbon fuels. Due to the high stability of the CO 2 molecule, significant thermal energy is required to undertake the reaction. Iron-oxide (FeO x ) has been shown to be an active and thermally stable catalysts towards the RWGS reaction. FeO x (iron-oxide) nanowires are fabricated through the polyol reduction method and have been characterized through scanning transmission electron microscopy (STEM) analysis[2]. Following the wet deposition method, the Fe nanowires are finely dispersed on cobalt-oxide (Co 3 O 4 ) to act as a support and semi-conductor. The dispersion of Fe on Co 3 O 4 enhances the electronic properties of the catalyst through the metal-support interaction (MSI) effect[3]. The MSI entails the back spillover of promoting oxygen (O δ- ) ionic species from Co 3 O 4 to FeO x by an increase in temperature, altering the work function of FeO x and allowing to cycle oxygen from the breaking of CO 2 . Through the Electrochemical Promotion of Catalysis (EPOC) phenomenon the catalytic activity can be enhanced by altering the binding energy of the reactant and intermediate species on the catalytic surface[4]. The MSI and EPOC phenomena have been shown to be functionally equivalent in terms of the change in work function. The difference between them is that in EPOC the movement of ions can be controlled through the application of an electrical current or potential difference, while the MSI effect is controlled by a thermal input. EPOC entails the use of solid electrolytes, for instance yttria-stabilized zirconia (YSZ) and barium zirconate yttrium-doped (BZY) which are oxygen and proton conductors, respectively. The catalyst-working electrodes ( i.e. FeO x nanowires) are deposited on one side of the electrolyte and on the opposite side, inert gold counter and reference electrodes. Through the application of a potential difference between the electrodes, promoting species migrate through the three-phase (solid-gas-catalyst) boundary in order to interact with the exposed-catalyst surface. In the case of BZY, when a potential difference is applied between the counter and working electrode, H + are removed from the surface through the three-phase boundary (tpb) towards BZY, referred to as positive polarization. When the polarization is reversed from the working to counter electrode, H + migrate from BZY through the tpb towards the catalytic surface. Utilizing YSZ, results in the opposite migration with O 2- ions. Regardless of the type of solid electrolyte used the catalyst is oxidized under positive polarization and reduced under negative polarization. The use of the Co 3 O 4 semiconductor allows to combine both the MSI and EPOC effect at 350°C, by finely dispersing the Fe nanowires on Co 3 O 4 to expose active sites and lowering the rate of sintering while being conductive to close the circuit[5]. As opposed to using other supports that do not display fully conductive properties, this approach provides an electronic path for the promoters to follow. Results have shown the working-catalyst FeO x /Co 3 O 4 on YSZ and BZY to be highly selective to CO formation under oxidizing (3CO 2 :H 2 ) and reducing (CO 2 :7H 2 ) conditions, with a superior activity experienced under rich reducing conditions. Furthermore, alteration in work function from the EPOC effect, has led to a promotional response for both YSZ and BZY. Combining the MSI and EPOC effect allows for high RWGS activity, establishing a promising solution in utilizing CO 2 as a resource while using transition metals. Additionally, the EPOC effect will be elucidated through Fourier-Transform Infrared (FTIR) spectroscopy to provide insight on the promoting mechanism occurring during polarization. 1. Porosoff, M. D., Yan, B. &amp; Chen, J. G. Catalytic reduction of CO 2 by H 2 for synthesis of CO, methanol and hydrocarbons: challenges and opportunities. Energy Environ. Sci. 2, 303 (2015). 1. Baranova, E. A., Bock, C., Ilin, D., Wang, D. &amp; MacDougall, B. Infrared spectroscopy on size-controlled synthesized Pt-based nano-catalysts. Surf. Sci. 600, 3502–3511 (2006). 2. Panaritis, C., Edake, M., Couillard, M., Einakchi, R. &amp; Baranova, E. A. Insight towards the role of ceria-based supports for reverse water gas shift reaction over RuFe nanoparticles. J. CO2 Util. 26, 350–358 (2018). 3. Vayenas, C. G., Bebelis, S., Pliangos, C., Brosda, S. &amp; Tsiplakides, D. Electrochemical Activation of Catalysis . (Springer US, 2001). 4. Zagoraios, D. et al. Electrochemical promotion of methane oxidation over nanodispersed Pd/Co 3 O 4 catalysts. Catal. Today (2019). doi:10.1016/j.cattod.2019.02.030

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)0.001
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 score0.018
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.219
Teacher spread0.209 · 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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