L. Clime
École Polytechnique de Montréal
11 Papers
59 Citations
L. Clime is an academic researcher from École Polytechnique de Montréal. The author has contributed to research in topics: Nanowire & Saturation (magnetic). The author has an hindex of 9, co-authored 11 publications.
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Papers
First-Order Reversal Curves Diagrams of Ferromagnetic Soft Nanowire Arrays
TL;DR: In this paper, first-order reversal curves (FORC) diagrams are used to map the statistical distributions of magnetic hysterons, based on their critical fields (H c) and local interaction fields (Hu), throughout the magnetization reversal.
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Reversible and quasireversible information in first-order reversal curve diagrams
TL;DR: In this paper, two methods for extracting information from first-order reversal curves (FORCs) obtained on low coercivity samples are presented, where the proportion of reversibility as a function of applied field can be extracted by calculating the ratio of the initial slope of each FORC to the susceptibility on the major hysteresis loop upper branch at the same field.
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Progress towards the optimization of the signal-to-noise ratio in giant magnetoimpedance sensors
David Ménard,G. Rudkowska,L. Clime,P. Ciureanu,Arthur Yelon,Sébastien Saez,Christophe Dolabdjian,Didier Robbes +7 more
TL;DR: In this paper, a rough estimate of thermally induced magnetic noise is proposed, which suggests that the magnetic noise in a GMI sensing element can contribute a significant part of its intrinsic noise.
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•Journal Article
Anisotropy optimization of giant magnetoimpedance sensors
TL;DR: In this paper, as-cast melt extracted CoFeSiBNb wires 375 μm in average diameter prepared by MXT Inc of Montreal have a predominantly helical anisotropy due to residual tensile and torsional stresses quenched in during preparation when a supplementary tensile stress is applied along the wire, its easy axis of magnetization rotates towards the transverse (or circumferential) direction.
13
•Journal Article
First order reversal curves diagram deduced by a shepard method for bivariate interpolation of scattered data
TL;DR: In this article, a new identification strategy of the distribution in Preisach-type models is described, where the mixed second derivative of the First Order Reversal Curves (FORC) is evaluated after an interpolation in the weighted least-squares sense and a Shepard interpolation method is applied in order to replace the initial irregular grid with a regular one.
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