Comparative evaluation on uniform corrosion resistance behaviour of ferritic stainless steels: experimental studies of electrochemical tests

Ferritic stainless steels were exposed to electrochemical polarization tests in 1N sulfuric acid solution. Somecritical parameter to uniform corrosion, as critical intensity (Icr), passive intensity (Ip) and corrosion rate(Vcorr), were determined from the polarization tests. To understand uniform corrosion behavior of this family ofstainless steel, a new equation has been determined taking the most relevant elements (Ni, Cr, Mo and N) intoaccount. An excellent correlation between predicted and experimental results was obtained. The developmentof the new equation is really useful to simulate the relation between the uniform corrosion and the chemicalcomposition in a defined Ferritic Stainless Steel

A microscopic model for a class of mixed-spin quantum antiferromagnets

We propose a microscopic model that describes the magnetic behavior of the mixed-spin quantum systems R$_2$BaNiO$_5$ (R= magnetic rare earth). An evaluation of the properties of this model by Quantum Monte Carlo simulations shows remarkable good agreement with the experimental data and provides new insight into the physics of mixed-spin quantum magnets.Comment: revised version to be published in Phys. Rev.

Magnetic ordering, spin waves, and Haldane gap excitations in (Nd_x Y_{1-x})_2 Ba Ni O_5 linear-chain mixed-spin antiferromagnets

Linear-chain nickelates with the composition (Nd_x Y_{1-x})_2 Ba Ni O_5 (x=1, x=0.75, x=0.5, and x=0.25) are studied in a series of neutron scattering experiments. Powder diffraction is used to determine the temperature dependence of the magnetic structure in all four systems. Single-crystal inelastic neutron scattering is employed to investigate the temperature dependence of the Haldane-gap excitations and low-energy spin waves in the x=1 compound Nd_2 Ba Ni O_5. The results of these experiments are discussed in the context of the ``Haldane chain in a staggered field'' model for R_2 Ba Ni O_5 systems, and quantitative agreement with theory is obtained.Comment: Major rewriting and inclusion of new experimental data 30 pages, 14 figure

The antiferromagnetic/paramagnetic transition in mixed-spin compounds R2BaNiO5

We present an extensive Quantum Monte Carlo study of the magnetic properties ofthe mixed-spin quantum systems R2BaNiO5 (R= magnetic rare earth)which show coexistence of 3-dimensional magnetic long-range orderwith 1-dimensional quantum gap excitations.We discuss the validity of the performed simulations in thecritical region and show the excellent agreement with experimental results. We emphasize the importance of quantum fluctuations contained in ourstudy which is absent in previous mean-field-like treatments.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43878/1/10051_2004_Article_143.pd

Examining Neural Connectivity in Schizophrenia Using Task-Based EEG: A Graph Theory Approach

Schizophrenia (SZ) is a complex disorder characterized by a range of symptoms and behaviors that have significant consequences for individuals, families, and society in general. Electroencephalography (EEG) is a valuable tool for understanding the neural dynamics and functional abnormalities associated with schizophrenia. Research studies utilizing EEG have identified specific patterns of brain activity in individuals diagnosed with schizophrenia that may reflect disturbances in neural synchronization and information processing in cortical circuits. Considering the temporal dynamics of functional connectivity provides a more comprehensive understanding of brain networks’ organization and how they change during different cognitive states. This temporal perspective would enhance our understanding of the underlying mechanisms of schizophrenia. In the present study, we will use measures based on graph theory to obtain dynamic and static indicators in order to evaluate differences in the functional connectivity of individuals diagnosed with SZ and healthy controls using an ecologically valid task. At the static level, patients showed alterations in their ability to segregate information, particularly in the default mode network (DMN). As for dynamic measures, patients showed reduced values in most metrics (segregation, integration, centrality, and resilience), reflecting a reduced number of dynamic states of brain networks. Our results show the utility of combining static and dynamic indicators of functional connectivity from EEG sensors.This research was funded by Agencia Estatal de Investigación, AEI, PID2019-105145RB-I00