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Record W4382011723 · doi:10.1002/adma.202303535

PAF‐6 Doped with Phosphoric Acid through Alkaline Nitrogen Atoms Boosting High‐Temperature Proton‐Exchange Membranes for High Performance of Fuel Cells

2023· article· en· W4382011723 on OpenAlexaff
Liying Wang, Yuliang Wang, Zhangnan Li, Tianyang Li, Ruyu Zhang, Jing Li, Baijun Liu, Zhongyuan Lv, Weiwei Cai, Shuhui Sun, Wei Hu, Yunfeng Lu, Guangshan Zhu

Bibliographic record

VenueAdvanced Materials · 2023
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsInstitut National de la Recherche Scientifique
FundersChinese Academy of SciencesNational Natural Science Foundation of China
KeywordsMaterials scienceMembranePhosphoric acidProton exchange membrane fuel cellChemical engineeringProton transportProtonationAlkaline fuel cellIon exchangeChemistryOrganic chemistryIon

Abstract

fetched live from OpenAlex

Abstract High‐temperature proton‐exchange‐membrane fuel cells (HT‐PEMFCs) can offer improved energy efficiency and tolerance to fuel/air impurities. The high expense of the high‐temperature proton‐exchange membranes (HT‐PEMs) and their low durability at high temperature still impede their further practical applications. In this work, a phosphoric acid (PA)‐doped porous aromatic framework (PAF‐6‐PA) is incorporated into poly[2,2′‐(p‐oxydiphenylene)‐5,5′‐benzimidazole] (OPBI) to fabricate novel PAF‐6‐PA/OPBI composite HT‐PEMs through solution‐casting. The alkaline nitrogen structure in PAF‐6 can be protonated with PA to provide proton hopping sites, and its porous structure can enhance the PA retention in the membranes, thus creating fast pathways for proton transfer. The hydrogen bond interaction between the rigid PAF‐6 and OPBI can also enhance the mechanical properties and chemical stability of the composite membranes. Consequently, PAF‐6‐PA/OPBI exhibits an optimal proton conductivity of 0.089 S cm −1 at 200 °C, and peak power density of 437.7 mW cm −2 (Pt: 0.3 mg cm −2 ), which is significantly higher than that of the OPBI. The PAF‐6‐PA/OPBI provides a novel strategy for the practical application of PBI‐based HT‐PEMs.

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 categoriesMeta-epidemiology (narrow)
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 score0.022
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.203
Teacher spread0.196 · 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.

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

Citations98
Published2023
Admission routes1
Has abstractyes

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