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Record W4416947315 · doi:10.1038/s41467-025-65909-3

Lattice-hydrogen cycling mechanism enables pH-universal hydrogen evolution at ampere-level current densities

2025· article· en· W4416947315 on OpenAlexaff
Yan Zhang, Biao Feng, Jingyi Tian, Shiqi Zhou, Changkai Zhou, Yiqun Chen, Xiaoli Xia, Xizhang Wang, Lijun Yang, Luming Peng, Qiang Wu, Hongwen Huang, Zheng Hu

Bibliographic record

VenueNature Communications · 2025
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsMinistry of Education and Child Care
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of ChinaScience and Technology Support Program of Jiangsu ProvinceNanjing UniversityGovernment of Jiangsu ProvinceSalt Science Research Foundation
KeywordsHydrogenElectrolyteDissociation (chemistry)CatalysisHydrogen productionRaman spectroscopyHydrogen economyAdsorption

Abstract

fetched live from OpenAlex

Abstract Controllable supply of hydrogen intermediate across a wide pH range is crucial for electroreduction reactions, but is hindered by pH-dependent hydrogen species formation on conventional catalysts. We report a lattice-hydrogen cycling mechanism that dissociates hydrogen intermediate availability from electrolyte pH. By integrating proton-blocking Ru with thermally-hydrogenated H x WO 3 , we create a dynamic hydrogen reservoir, enabling efficient hydrogen supply. In-situ Raman spectroscopy, isotopic labeling, and theoretical simulations reveal the lattice hydrogen in H x WO 3 migrates swiftly to Ru active sites via low-energy-barrier pathways, while consumed hydrogen is spontaneously replenished via proton adsorption (acidic) or water dissociation (alkaline/neutral). Consequently, this catalyst achieves a competitive pH-universal performance for hydrogen evolution reaction, with low overpotentials (125 mV acidic, 142 mV alkaline, 219 mV neutral @1 A cm -2 ) alongside 500-hour stability.

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 score0.002
Threshold uncertainty score0.005

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.270
Teacher spread0.250 · 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

Citations7
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueNature Communications→Same topicElectrocatalysts for Energy Conversion→French-language works237,207→