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Record W4417450677 · doi:10.1007/s44373-025-00082-2

Practical applications of offshore hydrogen production and innovations in porous transport layers for water electrolyzers

2025· article· en· W4417450677 on OpenAlexfundno aff
Xuewei Mao, Weibing Lin, Jing Lian, Zhenye Kang

Bibliographic record

VenueDiscover Electrochemistry. · 2025
Typearticle
Languageen
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsnot available
FundersHainan Provincial Department of Science and TechnologyHainan UniversityUniversity of Toronto
KeywordsHydrogen productionSubmarine pipelineRenewable energyElectrolysis of waterOffshore wind powerSeawaterDurabilityElectrolysis

Abstract

fetched live from OpenAlex

Green hydrogen, produced using renewable energy, is vital for achieving global decarbonization. Offshore wind energy, with its high efficiency and scalability, offers a promising pathway for cost-effective hydrogen production. The review systematically compares offshore and onshore renewable energy-driven hydrogen systems, highlighting the technical and economic challenges specific to marine environments, including corrosive seawater exposure, intermittent energy supply, and infrastructure scalability. This review also examines advancements in proton exchange membrane water electrolysis (PEMWE) technologies, particularly innovations in porous transport layers (PTLs), which are critical for managing mass transfer, conductivity, and durability in harsh marine environments. The development of perforated PTLs, such as SP-PTLs with corrosion-resistant coatings, significantly enhances performance, enabling stable operation in seawater conditions. Breakthroughs like dual-functional electrolysis that can simultaneously produce hydrogen and high-purity magnesium hydroxide, reduce costs by leveraging seawater’s mineral resources. The review concludes with a forward-looking perspective, emphasizing the urgency of developing low-cost PTLs, modular floating electrolyzer platforms, and policy frameworks to accelerate cost parity with fossil-derived hydrogen. By addressing these challenges, offshore hydrogen production can emerge as a linchpin of the net-zero transition, harmonizing technological advancement, economic viability, and environmental sustainability.

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 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 score0.012
Threshold uncertainty score0.615

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 head0.007
GPT teacher head0.258
Teacher spread0.251 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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