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Transport phenomena in proton conducting media

2011· article· en· W1980477963 on OpenAlexaff
Michael Eikerling

Bibliographic record

VenueJournal of Physics Condensed Matter · 2011
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsProtonPhysicsNuclear physics

Abstract

fetched live from OpenAlex

Proton transport phenomena are of paramount importance for acid-base chemistry, energy transduction in biological organisms, corrosion processes, and energy conversion in electrochemical systems such as polymer electrolyte fuel cells. The relevance for such a plethora of materials and systems, and the ever-lasting fascination with the highly concerted nature of underlying processes drive research across disciplines in chemistry, biology, physics and chemical engineering. A proton never travels alone. Proton motion is strongly correlated with its environment, usually comprised of an electrolyte and a solid or soft host material. For the transport in nature's most benign proton solvent and shuttle, water that is, insights from ab initio simulations, matured over the last 15 years, have furnished molecular details of the structural diffusion mechanism of protons. Excess proton movement in water consists of sequences of Eigen?Zundel?Eigen transitions, triggered by hydrogen bond breaking and making in the surrounding water network. Nowadays, there is little debate about the validity of this mechanism in water, which bears a stunning resemblance to the basic mechanistic picture put forward by de Grotthuss in 1806. While strong coupling of an excess proton with degrees of freedom of solvent and host materials facilitates proton motion, this coupling also creates negative synergies. In general, proton mobility in biomaterials and electrochemical proton conducting media is highly sensitive to the abundance and structure of the proton solvent. In polymer electrolyte membranes, in which protons are bound to move in nano-sized water-channels, evaporation of water or local membrane dehydration due to electro-osmotic coupling are well-known phenomena that could dramatically diminish proton conductivity. Contributions in this special issue address various vital aspects of the concerted nature of proton motion and they elucidate important structural and dynamic effects of solvent, charge-bearing species at interfaces and porous host materials on proton transport properties. As a common thread, articles in this special issue contribute to understanding the functionality provided by complex materials, beyond hydrogen bond fluctuations in water. The first group of articles (Smirnov et al, Henry et al, Medvedev and Stuchebrukhov) elucidates various aspects of the impact of local structural fluctuations, hydrogen bonding and long-range electrostatic forces on proton transfer across and at the surface of mitochondrial membranes. The second group of articles (Ilhan and Spohr, Allahyarov et al and Idupulapati et al) employ molecular dynamics simulations to rationalize vital dependencies of proton transport mechanisms in aqueous-based polymer electrolyte membranes on the nanoporous, phase-separated ionomer morphology, and on the level of hydration. The articles by Gebel et al, Boillat et al, and Aleksandrova et al employ small angle neutron scattering, neutron radiography, and electrochemical atomic force microscopy, respectively, to obtain detailed insights into the kinetics of water sorption, water distribution, water transport properties, as well as spatial maps of proton conductivity in fuel cell membranes. The contribution of Paschos et al provides a comprehensive review of phosphate-based solid state protonic conductors for intermediate temperature fuel cells. The topic of proton conductive materials for high-temperature, water-free operation of fuel cells is continued in the article of Verbraeken et al which addresses synthesis and characterization of a proton conducting perovskite. The guest editor wishes to acknowledge and thank all contributing authors for their commitment to this special issue. Moreover, I would like to thank the staff at IOP Publishing for coordinating submission and refereeing processes. Finally, for the readers, I hope that this special issue will be a valuable and stimulating source of insights into the versatile and eminently important field of transport phenomena in proton conducting media. Complex dynamics of fluids in disordered and crowded environments contents Electrostatic models of electron-driven proton transfer across a lipid membrane Anatoly Yu Smirnov, Lev G Mourokh and Franco Nori Molecular basis of proton uptake in single and double mutants of cytochrome c oxidase Rowan M Henry, David Caplan, Elisa Fadda and R?gis Pom?s Proton diffusion along biological membranes E S Medvedev and A A Stuchebrukhov Ab initio molecular dynamics of proton networks in narrow polymer electrolyte pores Mehmet A Ilhan and Eckhard Spohr A simulation study of field-induced proton-conduction pathways in dry ionomers Elshad Allahyarov, Philip L Taylor and Hartmut L?wen Molecular structure and transport dynamics in perfluoro sulfonyl imide membranes Nagesh Idupulapati, Ram Devanathan and Michel Dupuis The kinetics of water sorption in Nafion membranes: a small-angle neutron scattering study G?rard Gebel, Sandrine Lyonnard, Hakima Mendil-Jakani and Arnaud Morin Using 2H labeling with neutron radiography for the study of solid polymer electrolyte water transport properties P Boillat, P Oberholzer, B C Seyfang, A K?stner, R Perego, G G Scherer, E H Lehmann and A Wokaun Spatial distribution and dynamics of proton conductivity in fuel cell membranes: potential and limitations of electrochemical atomic force microscopy measurements E Aleksandrova, S Hink, R Hiesgen and E Roduner A review on phosphate based, solid state, protonic conductors for intermediate temperature fuel cells O Paschos, J Kunze, U Stimming and F Maglia A structural study of the proton conducting B-site ordered perovskite Ba3Ca1.18Ta1.82O8.73 Maarten C Verbraeken, Hermenegildo A L Viana, Philip Wormald and John T S Irvine

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 score0.048
Threshold uncertainty score0.879

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.038
GPT teacher head0.204
Teacher spread0.165 · 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".

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Citations5
Published2011
Admission routes1
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