MétaCan
Menu
Back to cohort
Record W3087137869 · doi:10.1021/acs.nanolett.0c03340

Bismuth Oxyhydroxide-Pt Inverse Interface for Enhanced Methanol Electrooxidation Performance

2020· article· en· W3087137869 on OpenAlexaff
Xuchun Wang, Miao Xie, Fenglei Lyu, Yun Mui Yiu, Zhiqiang Wang, Jiatang Chen, Lo‐Yueh Chang, Yujian Xia, Qixuan Zhong, Mingyu Chu, Hao Yang, Tao Cheng, Tsun‐Kong Sham, Qiao Zhang

Bibliographic record

VenueNano Letters · 2020
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsWestern University
FundersCollaborative Innovation Center of Suzhou Nano Science and TechnologyNatural Science Foundation of Jiangsu ProvincePriority Academic Program Development of Jiangsu Higher Education InstitutionsChina Postdoctoral Science FoundationMinistry of Education of the People's Republic of ChinaNational Natural Science Foundation of China
KeywordsMethanolX-ray photoelectron spectroscopyBismuthAdsorptionElectrochemistryMethanol fuelX-ray absorption spectroscopyCatalysisChemical engineeringChemistryRedoxInorganic chemistryMaterials scienceAbsorption spectroscopyPhysical chemistryElectrodeOrganic chemistry

Abstract

fetched live from OpenAlex

Developing efficient Pt-based electrocatalysts for the methanol oxidation reaction (MOR) is of pivotal importance for large-scale application of direct methanol fuel cells (DMFCs), but Pt suffers from severe deactivation brought by the carbonaceous intermediates such as CO. Here, we demonstrate the formation of a bismuth oxyhydroxide (BiOx(OH)y)-Pt inverse interface via electrochemical reconstruction for enhanced methanol oxidation. By combining density functional theory calculations, X-ray absorption spectroscopy, ambient pressure X-ray photoelectron spectroscopy, and electrochemical characterizations, we reveal that the BiOx(OH)y-Pt inverse interface can induce the electron deficiency of neighboring Pt; this would result in weakened CO adsorption and strengthened OH adsorption, thereby facilitating the removal of the poisonous intermediates and ensuring the high activity and good stability of Pt2Bi sample. This work provides a comprehensive understanding of the inverse interface structure and deep insight into the active sites for MOR, offering great opportunities for rational fabrication of efficient electrocatalysts for DMFCs.

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)0.000
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 score0.032
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.225
Teacher spread0.212 · 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

Citations88
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueNano LettersSame topicElectrocatalysts for Energy ConversionFrench-language works237,207