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Stephen J. Paddison

Researcher at University of Tennessee

Publications -  131
Citations -  8172

Stephen J. Paddison is an academic researcher from University of Tennessee. The author has contributed to research in topics: Membrane & Hydrogen bond. The author has an hindex of 43, co-authored 125 publications receiving 7253 citations. Previous affiliations of Stephen J. Paddison include University of Calgary & University of Alabama in Huntsville.

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Transport in proton conductors for fuel-cell applications: simulations, elementary reactions, and phenomenology.

TL;DR: Theoretical Methodologies and Simulation Tools, and Poisson−Boltzmann Theory, and Phenomenology of Transport inProton-Conducting Materials for Fuel-CellApplications46664.2.1.
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Proton Conduction Mechanisms at Low Degrees of Hydration in Sulfonic Acid–Based Polymer Electrolyte Membranes

TL;DR: In this paper, the role of local chemistry of the hydrophilic side chains and its effect on the dissociation of the proton and eventual stableness is discussed in connection with their role in the conduction of protons in sulfonic acid-based polymer electrolyte membranes.
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The mechanism of proton conduction in phosphoric acid

TL;DR: An ab initio molecular dynamics study is presented that reveals, for the first time, the microscopic mechanism of this high proton conductivity ineat liquid phosphoric acid.
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Short-side-chain proton conducting perfluorosulfonic acid ionomers: Why they perform better in PEM fuel cells

TL;DR: In this article, short-side-chain (SSC) perfluorosulfonic acid ionomers of different ion exchange capacity, IEC, (Dow 840 and Dow 1150) are characterized with respect to water sorption, transport (proton conductivity, electroosmotic water drag and water diffusion), microstructure and visco-elastic properties as a function of temperature and degree of hydration.
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Modelling of morphology and proton transport in PFSA membranes

TL;DR: The state of computational modelling of PFSA membranes has progressed sufficiently over the last decade to enable its use as a powerful predictive tool with which to guide the process of designing novel membrane materials for fuel cell applications.