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Record W2921700746 · doi:10.1021/acsaem.8b02137

Combining the Advantages of Hollow and One-Dimensional Structures: Balanced Activity and Stability toward Methanol Oxidation Based on the Interface of PtCo Nanochains

2019· article· en· W2921700746 on OpenAlexaff
Yunwei Liu, Zelin Chen, Chang Liu, Jinfeng Zhang, Xiaopeng Han, Cheng Zhong, Dewei Rao, Yuesheng Wang, Wenbin Hu, Yida Deng

Bibliographic record

VenueACS Applied Energy Materials · 2019
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsHydro-Québec
FundersNational Natural Science Foundation of China
KeywordsMethanolElectrocatalystMaterials scienceCatalysisMethanol fuelNanotechnologyInterface (matter)Fuel cellsChemical engineeringChemistryElectrodeElectrochemistryComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

Active and durable electrocatalysts for methanol oxidation reaction (MOR) are of great importance to the practical application of direct methanol fuel cell technology. Although tremendous efforts have been devoted to optimize the electrocatalysts, these electrocatalysts still fall far short of expectation and suffer from rapid activity loss. Herein, we report a new strategy for designing PtCo nanochains as a methanol oxidation electrocatalyst with high activity and excellent stability. The obtained PtCo nanochains consist of a string of hollow spheres that forms a one-dimensional chain structure. We find that having a defect-rich interface between adjacent hollow spheres is responsible for high catalytic performance and stability. With this special morphology, the PtCo nanochains exhibit exceptional activity (3.73 A·mg–1Pt) and stability (90.8% of initial current retained after 1500 cycles) for methanol oxidation. These findings will provide a new insight in designing and synthesizing high-performance electrocatalysts.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.059
Threshold uncertainty score0.592

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.012
GPT teacher head0.238
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.

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".

Quick stats

Citations21
Published2019
Admission routes1
Has abstractyes

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