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Record W2599110916 · doi:10.1149/ma2016-01/44/2166

Influence of Composition of Ti/SnO<sub>2</sub>-Sb<sub>2</sub>O<sub>5</sub> on the Kinetics of Electro-Oxidation

2016· article· en· W2599110916 on OpenAlexaff
Qing Ni, Donald W. Kirk, Steven J. Thorpe

Bibliographic record

VenueECS Meeting Abstracts · 2016
Typearticle
Languageen
FieldMaterials Science
TopicThermal and Kinetic Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTafel equationMaterials scienceDielectric spectroscopyOxalic acidAnodeX-ray photoelectron spectroscopyThin filmAntimonyCyclic voltammetryInorganic chemistryAnalytical Chemistry (journal)TinElectrodeElectrochemistryChemical engineeringChemistryMetallurgyNanotechnologyPhysical chemistry

Abstract

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The Ti/SnO2-Sb2O5 anode is a promising material for the anodic oxidation of organic compounds for the application of wastewater treatment. The material consists of a thin film of Sb-doped SnO2 on the titanium substrate. The influence of Sb doping on the conductivity of SnO2 thin films has been well documented, but its effect on the catalysis of electro-oxidation remains largely unknown. The current investigation presents a systematic study addressing this knowledge gap. A series of Ti/SnO2-Sb2O5 anodes were prepared using thermal deposition and electro-deposition. These films contained a wide range of doping levels, expressed as atomic fraction Sb/(Sn+Sb), essentially from SnO2 dominant to SbOx dominant. The surface composition of deposited coatings was determined by X-ray photoelectron spectroscopy. The electrochemical activities of the electrodes were evaluated through the use of polarization scans performed in a simulated wastewater system containing oxalic acid as an organic analog target for destruction. All electrodes exhibited Tafel behavior. Different anodes were compared based on their activity, defined as the anodic current at 1.7VSHE normalized by the surface roughness of the electrode. Electrochemical impedance spectroscopy was used to estimate the effective surface area, by means of effective double-layer capacitance. Scanning voltammetry in 0.01mol/L oxalic acid showed Tafel slopes varying between 180~250mV/dec (Figure 1). Some samples with very high and low doping levels of antimony showed even higher Tafel slopes. The above findings were related to the conductivity of the doped films. Herrmann et al., reported that the conductivity of the mixed antimony-tin oxide was highly dependent on the level of Sb doping in the film1. According to their study, the SnO2-Sb2O5 mixed oxide was highly conductive with Sb doping level between 1.7% and 40%. Oxides with doping levels outside this range exhibited a drop in conductivity by three orders of magnitude. In the present investigation, the uncompensated resistance of the coating films in the electrodes can results in abnormally high Tafel slopes as shown in Figure 1. The activities of the anodes were compared at 1.7VSHE. The current levels were normalized to the double-layer capacitance of the electrode and plotted against the doping level as shown in Figure 2. A volcano curve is evident from the figure, which suggested that the electrode had an optimum doping level at about 2% Sb doping. This level of doping was different from the composition corresponding to the highest conductivity that was identified by Herrmann et al. 1. The beneficial increase in the performance of the electrode at this doping level of could be related to the surface arrangement of Sb atoms in the SnO2 lattice. Ongoing work is being conducted to characterize the surface features of the Sb-doped SnO2materials. Reference: 1. J-M. J. Herrmann, J-L. Portefaix, M. Forissier, F. Figueras, P. Pichat, Electrical Behavior of Powdered Tin-Antimony Mixed Oxide Catalysts. J. Chem. Soc. Farad. Trans. I, 75, 1346 (1979). Figure 1

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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)0.001
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.213
Teacher spread0.204 · 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
Published2016
Admission routes1
Has abstractyes

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