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Record W4225422884 · doi:10.1007/s40820-022-00860-2

Interface Engineering of NixSy@MnOxHy Nanorods to Efficiently Enhance Overall-Water-Splitting Activity and Stability

2022· article· en· W4225422884 on OpenAlexafffund
Pan Wang, Yuanzhi Luo, Gaixia Zhang, Zhangsen Chen, Hariprasad Ranganathan, Shuhui Sun, Zhicong Shi

Bibliographic record

VenueNano-Micro Letters · 2022
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsInstitut National de la Recherche Scientifique
FundersBasic and Applied Basic Research Foundation of Guangdong ProvinceWestern Economic Diversification CanadaNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchShanghai Jiao Tong UniversityInstitut national de la recherche scientifiqueUniversity of SaskatchewanCanadian Light Source
KeywordsElectrocatalystNanorodBifunctionalWater splittingMaterials scienceOxygen evolutionHydrothermal circulationChemical engineeringElectrolyteHeterojunctionCatalysisNanotechnologyElectrochemistryChemistryElectrodePhysical chemistryPhotocatalysis

Abstract

fetched live from OpenAlex

Highlights Three-dimensional (3D) core‐shell heterostructured Ni x S y @MnO x H y nanorods grown on nickel foam (Ni x S y @MnO x H y /NF) were successfully fabricated via a simple hydrothermal reaction and a subsequent electrodeposition process. The fabricated Ni x S y @MnO x H y /NF shows outstanding bifunctional activity and stability for hydrogen evolution reaction and oxygen evolution reaction, as well as overall‐water‐splitting performance. The main origins are the interface engineering of Ni x S y @MnO x H y , the shell‐protection characteristic of MnO x H y , and the 3D open nanorod structure, which remarkably endow the electrocatalyst with high activity and stability. Abstract Exploring highly active and stable transition metal-based bifunctional electrocatalysts has recently attracted extensive research interests for achieving high inherent activity, abundant exposed active sites, rapid mass transfer, and strong structure stability for overall water splitting. Herein, an interface engineering coupled with shell-protection strategy was applied to construct three-dimensional (3D) core‐shell Ni x S y @MnO x H y heterostructure nanorods grown on nickel foam (Ni x S y @MnO x H y /NF) as a bifunctional electrocatalyst. Ni x S y @MnO x H y /NF was synthesized via a facile hydrothermal reaction followed by an electrodeposition process. The X-ray absorption fine structure spectra reveal that abundant Mn‐S bonds connect the heterostructure interfaces of Ni x S y @MnO x H y , leading to a strong electronic interaction, which improves the intrinsic activities of hydrogen evolution reaction and oxygen evolution reaction (OER). Besides, as an efficient protective shell, the MnO x H y dramatically inhibits the electrochemical corrosion of the electrocatalyst at high current densities, which remarkably enhances the stability at high potentials. Furthermore, the 3D nanorod structure not only exposes enriched active sites, but also accelerates the electrolyte diffusion and bubble desorption. Therefore, Ni x S y @MnO x H y /NF exhibits exceptional bifunctional activity and stability for overall water splitting, with low overpotentials of 326 and 356 mV for OER at 100 and 500 mA cm –2 , respectively, along with high stability of 150 h at 100 mA cm –2 . Furthermore, for overall water splitting, it presents a low cell voltage of 1.529 V at 10 mA cm –2 , accompanied by excellent stability at 100 mA cm –2 for 100 h. This work sheds a light on exploring highly active and stable bifunctional electrocatalysts by the interface engineering coupled with shell-protection strategy.

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 score0.002

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 communication0.0000.000
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 head0.005
GPT teacher head0.207
Teacher spread0.203 · 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".

Quick stats

Citations178
Published2022
Admission routes2
Has abstractyes

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