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Record W4292438707 · doi:10.1002/advs.202203199

Positively Charged Pt‐Based Nanoreactor for Efficient and Stable Hydrogen Evolution

2022· article· en· W4292438707 on OpenAlexaff
Kun Feng, Jiabin Xu, Yufeng Chen, Shuo Li, Zhenhui Kang, Jun Zhong

Bibliographic record

VenueAdvanced Science · 2022
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsWestern University
FundersNational Key Research and Development Program of ChinaNatural Science Foundation of Jiangsu ProvinceNational Natural Science Foundation of China
KeywordsNanoreactorOverpotentialDissociation (chemistry)Materials scienceOxygen evolutionX-ray absorption spectroscopyChemical engineeringHydrogenNanotechnologyChemical physicsChemistryAbsorption spectroscopyElectrodePhysical chemistryNanoparticlePhysicsElectrochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Positively charged Pt can work as the active center for hydrogen evolution reaction (HER) but the corresponding design of state‐of‐the‐art electrocatalysts at high current densities has never been realized. Here the application of positively charged Pt in an effective Fe‐PtNiPO nanoreactor for highly efficient and stable HER is demonstrated. Synchrotron radiation X‐ray absorption spectroscopy confirms the formation of internal positively charged Pt and the in situ experiments reveal the quick charge transfer in the nanoreactor. Ni‐based materials around Pt are used to tune the electronic structure and promote the water dissociation to form locally enriched H + , while a porous Fe shell can both prevent the loss of active material and allow the efficient material transport. All the beneficial compositions work together to form an effective nanoreactor for HER. As a result, the Fe‐PtNiPO nanoreactor shows a low overpotential of 19 mV to achieve 10 mA cm −2 and exhibits a high mass activity of 10.93 A mg Pt −1 (at 100 mV). Most importantly, it only needs an ultra‐low overpotential of 193 mV to achieve a high current density of 1000 mA cm −2 with an excellent stability over 300 h, which represents one of the best electrocatalysts for alkaline HER and might be used for large‐scale industrial application in the future.

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 score0.029
Threshold uncertainty score0.858

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.007
GPT teacher head0.225
Teacher spread0.218 · 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

Citations28
Published2022
Admission routes1
Has abstractyes

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