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A comprehensive review of the material innovations and corrosion mitigation strategies for PEMWE bipolar plates

2024· review· en· W4402737766 on OpenAlexaff
Yasin Mehdizadeh Chellehbari, Mohammadhossein Johar, Abhay Gupta, Samaneh Shahgaldi

Bibliographic record

VenueInternational Journal of Hydrogen Energy · 2024
Typereview
Languageen
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsCorrosionMaterials scienceEnvironmental scienceMetallurgy

Abstract

fetched live from OpenAlex

Proton exchange membrane water electrolyzers (PEMWE) are being considered as a high efficiency potential option for green hydrogen production. Bipolar plates (BPPs) are a crucial element within PEMWEs serving a significant function in the sepration of product gases, distribution of flow field, electron collection, and heat conduction. This review paper aims to investigate recent research on materials used in BPPs and examine several corrosion prevention strategies aimed at enhancing their durability and performance in PEMWEs. It presents a thorough examination of the materials utilized in BPPs, encompassing both conventional metals and advanced coatings. The analysis focuses on elucidating the distinct advantages and limits associated with these materials in relation to conductivity, mechanical strength, and resistance to corrosion. The review examines electrochemical techniques and microscopy methods utilized to assess corrosion behavior, guiding the selection and optimization of materials. Ultimately, this review offers a thorough comprehension of the current advancements in BPP materials and corrosion protection strategies for PEMWEs. • Consolidating recent research on BPP materials and corrosion prevention in PEMWEs. • Examining BPP materials, including traditional metals and advanced coatings. • Elucidating strengths and weaknesses of materials in conductivity and corrosion. • Investigating the physical and electrochemical characterization techniques.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.029
GPT teacher head0.313
Teacher spread0.284 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations59
Published2024
Admission routes1
Has abstractyes

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