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Boris Iwanschitz
Researcher at Winterthur Museum, Garden and Library
Publications - 30
Citations - 1488
Boris Iwanschitz is an academic researcher from Winterthur Museum, Garden and Library. The author has contributed to research in topics: Anode & Solid oxide fuel cell. The author has an hindex of 14, co-authored 30 publications receiving 1312 citations.
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Fundamental mechanisms limiting solid oxide fuel cell durability
TL;DR: In this article, the fundamental issues associated with solid oxide fuel cell (SOFC) durability have been reviewed with an emphasis on general features in SOFCs and respective anode and cathode related phenomena.
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Microstructure degradation of cermet anodes for solid oxide fuel cells: Quantification of nickel grain growth in dry and in humid atmospheres
Lorenz Holzer,Boris Iwanschitz,Thomas Hocker,Beat Münch,Michel Prestat,Daniel Wiedenmann,U. Vogt,P. Holtappels,Josef Sfeir,Andreas Mai,Thomas Graule +10 more
TL;DR: In this paper, the effects of compositional and environmental parameters on the kinetics of microstructural degradation are investigated for porous Ni/CGO anodes in solid oxide fuel cells (SOFC).
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Quantitative relationships between composition, particle size, triple phase boundary length and surface area in nickel-cermet anodes for Solid Oxide Fuel Cells
TL;DR: In this paper, the quantitative relationship between the primary microstructural parameters (i.e., phase volume fractions Phi, the particle and pore sizes and the corresponding size distributions PSD) with the more complex topological features (triple phase boundary length TPBL, and specific surface area SSA) in porous Ni-cermet anodes is discussed.
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Degradation of SOFC Anodes upon Redox Cycling: A Comparison Between Ni/YSZ and Ni/CGO
TL;DR: In this article, the stability of solid oxide fuel cells (SOFCs) with two different anodes was investigated by impedance spectroscopy as well as by four-point electrical conductivity measurements.
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A neural network estimator of Solid Oxide Fuel Cell performance for on-field diagnostics and prognostics applications
TL;DR: In this article, a neural network (NN) model of solid oxide fuel cells (SOFC) aimed at implementing on-field diagnosis of SOFC-based distributed power generators is proposed.