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Record W4234354917 · doi:10.1149/ma2015-03/1/412

Understanding the Aging Degradation of Doped Barium Cerate Proton Conductor in Ambient Air at Room Temperature

2015· article· en· W4234354917 on OpenAlexaff
Ning Yan, Tong Gao, Wei Wang, Jing‐Li Luo

Bibliographic record

VenueECS Meeting Abstracts · 2015
Typearticle
Languageen
FieldMaterials Science
TopicAdvancements in Solid Oxide Fuel Cells
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMaterials scienceElectrolyteConductivityDopingProton conductorInorganic chemistryChemical engineeringElectrodeChemistryPhysical chemistry

Abstract

fetched live from OpenAlex

As a promising alternative power generation technology, solid oxide fuel cells (SOFC) have been intensively studied during the past several decades [1]. Among all the solid electrolyte candidates, proton conducting materials, e.g., BaCeO3, exhibit relatively high ionic conductivity at intermediate temperature (< 750 oC). Particularly, Zr and Y doped cerate, e.g., BaZr0.1Ce0.7Y0.2O3 (BZCY) was widely reported to have excellent conductivity as well as adequate stability in resisting concentrated CO2 up to 30 % with moisture at elevated temperatures typical for SOFC operation [2,3]. Herein, via using a combinations of various electrochemical measurements together with materials characterization techniques including XRD, TEM, SEM, XPS, TG-MS and FTIR, we firstly report that BZCY was prone to a gradual degradation in ambient air at room temperature with considerably minor CO2 (~0.04%) and humidity (<45% relative humidity). The adsorbed H2O acted as an effective catalyst that promoted the decomposition of BZCY via reaction with CO2, subsequently leading to the formation of BaCO3 nanorods as the major impurity phase, presumably following a microcrucible mechanism. Yttrium (oxy)carbonate and amorphous CeO2 and ZrO2 were also produced. It is also confirmed that the doping elements of Ce and Y caused the degradation of BZCY. During the fuel cells tests, the formed impurities on BZCY significantly hindered the electrocatalytic reactions at the electrolyte/electrode interfaces. We also proposed the regeneration and appropriate storage method of the electrolyte materials. Figure 1. TEM microscopic analysis of: (left) HAADF-STEM image of degraded BZCY with amorphous mixed oxides microcrucible and BaCO3 nanorods: (right) elemental mapping of Ba, Ce, Zr and Y. [1] X. W. Zhou, N. Yan, K. T. Chuang, J. L. Luo, RSC Adv., 4(2014), 118. [2] N. Yan, X. Z. Fu, K. T. Chuang, J. L. Luo, J. Power Sources, 254(2014),48. [3] L Yang, et. al., Science 326 (2009), 126. 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 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 score0.001
Threshold uncertainty score0.003

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0010.000
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 head0.079
GPT teacher head0.292
Teacher spread0.213 · 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
Published2015
Admission routes1
Has abstractyes

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