Magnetic behavior of NiCu nanowire arrays: Compositional, geometry and temperature dependence

Arrays of Ni100-xCux nanowires ranging in composition 0¿=¿x¿=¿75, diameter from 35 to 80¿nm, and length from 150¿nm to 28¿µm have been fabricated by electrochemical co-deposition of Ni and Cu into self-ordered anodic aluminum oxide membranes. As determined by X-ray diffraction and Transmission Electron Microscopy, the crystalline structure shows fcc cubic symmetry with [111] preferred texture and preferential Ni or Cu lattice depending on the composition. Their magnetic properties such as coercivity and squareness have been determined as a function of composition and geometry in a Vibrating Sample Magnetometer in the temperature range from 10 to 290¿K for applied magnetic fields parallel and perpendicular to the nanowires axis. Addition of Cu into the NiCu alloy up to 50% enhances both parallel coercivity and squareness. For the higher Cu content, these properties decrease and the magnetization easy axis becomes oriented perpendicular to the wires. In addition, coercivity and squareness increase by decreasing the diameter of nanowires which is ascribed to the increase of shape anisotropy. The temperature dependent measurements reflect a complex behavior of the magnetic anisotropy as a result of energy contributions with different evolution with temperature

Respectable Challenges to Respectable Theory: Cognitive Dissonance Theory Requires Conceptualization Clarification and Operational Tools

Despite its long tradition in social psychology, we consider that Cognitive Dissonance Theory presents serious flaws concerning its methodology which question the relevance of the theory, limit breakthroughs, and hinder the evaluation of its core hypotheses. In our opinion, these issues are mainly due to operational and methodological weaknesses that have not been sufficiently addressed since the beginnings of the theory. We start by reviewing the ambiguities concerning the definition and conceptualization of the term cognitive dissonance. We then review the ways it has been operationalized and we present the shortcomings of the actual paradigms. To acquire a better understanding of the theory, we advocate a stronger focus on the nature and consequences of the cognitive dissonance state itself. Next, we emphasize the actual lack of standardization, both in the ways to induce cognitive dissonance and to assess it, which impairs the comparability of the results. Last, in addition to reviewing these limits, we suggest new ways to improve the methodology and we conclude on the importance for the field of psychology to take advantage of these important challenges to go forwards

Evidence of Skyrmion-Tube Mediated Magnetization Reversal in Modulated Nanowires

Magnetic nanowires, conceived as individual building blocks for spintronic devices, constitute a well-suited model to design and study magnetization reversal processes, or to tackle fundamental questions, such as the presence of topologically protected magnetization textures under particular conditions. Recently, a skyrmion-tube mediated magnetization reversal process was theoretically reported in diameter modulated cylindrical nanowires. In these nanowires, a vortex nucleates at the end of the segments with larger diameter and propagates, resulting in a first switching of the nanowire core magnetization at small fields. In this work, we show experimental evidence of the so-called Bloch skyrmion-tubes, using advanced Magnetic Force Microscopy modes to image the magnetization reversal process of FeCoCu diameter modulated nanowires. By monitoring the magnetic state of the nanowire during applied field sweeping, a detected drop of magnetic signal at a given critical field unveils the presence of a skyrmion-tube, due to mutually compensating stray field components. That evidences the presence of a skyrmion-tube as an intermediate stage during the magnetization reversal, whose presence is related to the geometrical dimensions of the cylindrical segments

Efeito da bracatinga (Mimosa scabrella) na produção de matéria seca de pastagem sob sistema silvipastorial.

Edición de las Memorias de la 22a. Reunión ALPA, 2011, Montevideo. E68 Poster

Spin configuration in isolated FeCoCu nanowires modulated in diameter

Cylindrical Fe28Co67Cu5 nanowires modulated in diameter between 22 and 35 nm are synthesized by electroplating into the nanopores of alumina membranes. High-sensitivity MFM imaging (with a detection noise of 1 µN m-1) reveals the presence of single-domain structures in remanence with strong contrast at the ends of the nanowires, as well as at the transition regions where the diameter is modulated. Micromagnetic simulations suggest that curling of the magnetization takes place at these transition sites, extending over 10–20 nm and giving rise to stray fields measurable with our MFM. An additional weaker contrast is imaged, which is interpreted to arise from inhomogeneities in the nanowire diameter

Plasmonic coupling in closed-packed ordered gallium nanoparticles

Plasmonic gallium (Ga) nanoparticles (NPs) are well known to exhibit good performance in numerous applications such as surface enhanced fluorescence and Raman spectroscopy or biosensing. However, to reach the optimal optical performance, the strength of the localized surface plasmon resonances (LSPRs) must be enhanced particularly by suitable narrowing the NP size distribution among other factors. With this purpose, our last work demonstrated the production of hexagonal ordered arrays of Ga NPs by using templates of aluminium (Al) shallow pit arrays, whose LSPRs were observed in the VIS region. The quantitative analysis of the optical properties by spectroscopic ellipsometry confirmed an outstanding improvement of the LSPR intensity and full width at half maximum (FWHM) due to the imposed ordering. Here, by engineering the template dimensions, and therefore by tuning Ga NPs size, we expand the LSPRs of the Ga NPs to cover a wider range of the electromagnetic spectrum from the UV to the IR regions. More interestingly, the factors that cause this optical performance improvement are studied with the universal plasmon ruler equation, supported with discrete dipole approximation simulations. The results allow us to conclude that the plasmonic coupling between NPs originated in the ordered systems is the main cause for the optimized optical responseThe research is supported by the MINECO (CTQ2014-53334-C2-2-R, CTQ2017-84309-C2-2-R and MAT201676824-C3-1-R) and Comunidad de Madrid (P2018/NMT4349 and S2018/NMT-4321 NANOMAGCOST) projects. ARC acknowledges Ramón y Cajal program (under contract number RYC-2015-18047

Self-pruning Graph Neural Network for Predicting Inflammatory Disease Activity in Multiple Sclerosis from Brain MR Images

Multiple Sclerosis (MS) is a severe neurological disease characterized by inflammatory lesions in the central nervous system. Hence, predicting inflammatory disease activity is crucial for disease assessment and treatment. However, MS lesions can occur throughout the brain and vary in shape, size and total count among patients. The high variance in lesion load and locations makes it challenging for machine learning methods to learn a globally effective representation of whole-brain MRI scans to assess and predict disease. Technically it is non-trivial to incorporate essential biomarkers such as lesion load or spatial proximity. Our work represents the first attempt to utilize graph neural networks (GNN) to aggregate these biomarkers for a novel global representation. We propose a two-stage MS inflammatory disease activity prediction approach. First, a 3D segmentation network detects lesions, and a self-supervised algorithm extracts their image features. Second, the detected lesions are used to build a patient graph. The lesions act as nodes in the graph and are initialized with image features extracted in the first stage. Finally, the lesions are connected based on their spatial proximity and the inflammatory disease activity prediction is formulated as a graph classification task. Furthermore, we propose a self-pruning strategy to auto-select the most critical lesions for prediction. Our proposed method outperforms the existing baseline by a large margin (AUCs of 0.67 vs. 0.61 and 0.66 vs. 0.60 for one-year and two-year inflammatory disease activity, respectively). Finally, our proposed method enjoys inherent explainability by assigning an importance score to each lesion for the overall prediction. Code is available at https://github.com/chinmay5/ms_ida.gi