J
J.-Ph. Ansermet
Researcher at École Polytechnique Fédérale de Lausanne
Publications - 78
Citations - 2989
J.-Ph. Ansermet is an academic researcher from École Polytechnique Fédérale de Lausanne. The author has contributed to research in topics: Magnetization & Magnetoresistance. The author has an hindex of 28, co-authored 75 publications receiving 2824 citations. Previous affiliations of J.-Ph. Ansermet include École Polytechnique.
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Giant magnetoresistance of nanowires of multilayers
TL;DR: In this article, a new technique was proposed which enables tailoring of the morphology of a metallic nanostructured material down to the 10 nm length scale using nanoporous nuclear track etched membranes.
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Current-induced magnetization reversal in magnetic nanowires
TL;DR: In this article, the effect of pulsed currents on magnetization reversal was studied on single ferromagnetic nanowires of diameter about 80 nm and 6000 nm length, and the injected current triggered the magnetisation reversal at a value of the applied field distant from the switching field by as much as 20%.
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Magnetoresistance of Ferromagnetic Nanowires
TL;DR: In this article, the full magnetoresistive hysteresis loops of single Ni and Co nanowires, including the irreversible jump, are understood qualitatively, and major progress has been made towards their quantitative description, on the basis of anisotropic magnetoresistance.
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Measurements of magnetization switching in individual nickel nanowires
Wolfgang Wernsdorfer,Klaus Hasselbach,Alain Benoit,Bernard Barbara,Bernard Doudin,J. Meier,J.-Ph. Ansermet,Dominique Mailly +7 more
TL;DR: In this article, the authors studied the magnetization switching of individual ferromagnetic cylinders at low temperatures (0.1 -6 K) using a niobium microbridge-dc superconducting quantum interference device.
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Spin-dependent Peltier effect of perpendicular currents in multilayered nanowires
TL;DR: In this article, the authors presented a method to construct an EKF-based EKG-based model of the human brain and showed that it can be used to predict human brain activity.