Anomalous lattice parameter of magnetic semiconductor alloys

The addition of transition metals to III-V semiconductors radically changes their electronic, magnetic, and structural properties. We show by ab initio calculations that in contrast to the conventional semiconductor alloys, the lattice parameter in magnetic semiconductor alloys, including those with diluted concentration, strongly deviates from Vegard's law. We find a direct correlation between the magnetic moment and the anion-transition metal bond lengths and derive a simple and general formula that determines the lattice parameter of a particular magnetic semiconductor by considering both the composition and magnetic moment. This dependence can explain some experimentally observed anomalies and stimulate other kind of investigations.

Effect of Co addition on the lattice parameter, electrical conductivity and sintering of gadolinia-doped ceria

Co-sintering aid has been added to Ce1.9Gd0.1O1.95 (CGO) by treating a commercial powder with Co(NO3)(2) (COCGO), X-ray diffraction (XRD) measurements of lattice parameter indicated that the Co was located on the CGO particle surface after calcination at 650 degreesC. After heat treatment at temperatures above 650 degreesC, the room temperature lattice parameter of CGO was found to increase, indicating redistribution of the Gd. Compared to CGO, the lattice parameter of CGO + 2 cation% Co (2CoCGO) was lower for a given temperature (650-1100 degreesC), A.C. impedance revealed that the lattice conductivity of 2CoCGO was enhanced when densified at lower temperatures, Transmission electron microscopy (TEM) showed that, even after sintering for 4 h at 980 degreesC, most of the Co was located at grain boundaries. (C) 2002 Published by Elsevier Science B.V.

Evolutionary tuning of SVM parameter values in multiclass problems

Support vector machines (SVMs) were originally formulated for the solution of binary classification problems. In multiclass problems, a decomposition approach is often employed, in which the multiclass problem is divided into multiple binary subproblems, whose results are combined. Generally, the performance of SVM classifiers is affected by the selection of values for their parameters. This paper investigates the use of genetic algorithms (GAs) to tune the parameters of the binary SVMs in common multiclass decompositions. The developed GA may search for a set of parameter values common to all binary classifiers or for differentiated values for each binary classifier. (C) 2008 Elsevier B.V. All rights reserved.

Graphene to fluorographene and fluorographane: A theoretical study

We report here a fully reactive molecular dynamics study on the structural and dynamical aspects of the fluorination of graphene membranes (fluorographene). Our results show that fluorination tends to produce defective areas on the graphene membranes with significant distortions of carbon-carbon bonds. Depending on the amount of incorporated fluorine atoms, large membrane holes were observed due to carbon atom losses. These results may explain the broad distribution of the structural lattice parameter values experimentally observed. We have also investigated the effects of mixing hydrogen and fluorine atoms on the graphene functionalization. Our results show that, when in small amounts, the presence of hydrogen atoms produces a significant decrease in the rate of fluorine incorporation onto the membrane. On the other hand, when fluorine is the minority element, it produces a significant catalytic effect on the rate of hydrogen incorporation. We have also observed the spontaneous formation of new hybrid structures with different stable configurations (chair-like, zigzag-like and boat-like) which we named fluorographane. © 2013 IOP Publishing Ltd.

Parameter-free extraction of the functional network topology from intracranial EEG recordings: a time-resolved study of graph properties in focal onset seizures

Rationale: Focal onset epileptic seizures are due to abnormal interactions between distributed brain areas. By estimating the cross-correlation matrix of multi-site intra-cerebral EEG recordings (iEEG), one can quantify these interactions. To assess the topology of the underlying functional network, the binary connectivity matrix has to be derived from the cross-correlation matrix by use of a threshold. Classically, a unique threshold is used that constrains the topology [1]. Our method aims to set the threshold in a data-driven way by separating genuine from random cross-correlation. We compare our approach to the fixed threshold method and study the dynamics of the functional topology. Methods: We investigate the iEEG of patients suffering from focal onset seizures who underwent evaluation for the possibility of surgery. The equal-time cross-correlation matrices are evaluated using a sliding time window. We then compare 3 approaches assessing the corresponding binary networks. For each time window: * Our parameter-free method derives from the cross-correlation strength matrix (CCS)[2]. It aims at disentangling genuine from random correlations (due to finite length and varying frequency content of the signals). In practice, a threshold is evaluated for each pair of channels independently, in a data-driven way. * The fixed mean degree (FMD) uses a unique threshold on the whole connectivity matrix so as to ensure a user defined mean degree. * The varying mean degree (VMD) uses the mean degree of the CCS network to set a unique threshold for the entire connectivity matrix. * Finally, the connectivity (c), connectedness (given by k, the number of disconnected sub-networks), mean global and local efficiencies (Eg, El, resp.) are computed from FMD, CCS, VMD, and their corresponding random and lattice networks. Results: Compared to FMD and VMD, CCS networks present: *topologies that are different in terms of c, k, Eg and El. *from the pre-ictal to the ictal and then post-ictal period, topological features time courses that are more stable within a period, and more contrasted from one period to the next. For CCS, pre-ictal connectivity is low, increases to a high level during the seizure, then decreases at offset. k shows a ‘‘U-curve’’ underlining the synchronization of all electrodes during the seizure. Eg and El time courses fluctuate between the corresponding random and lattice networks values in a reproducible manner. Conclusions: The definition of a data-driven threshold provides new insights into the topology of the epileptic functional networks.

Comparisons of z values between fine-grained titanomagnetites within interstitial glass and large-grained titanomaghemtes in older ocean-floor basalts

Transmission electron microscopy observations and rock magnetic measurements reveal that alteration of fine- and large-grained iron-titanium oxides can occur at different rates. Fine-grained titanomagnetite occurs as a crystallization product within interstitial glass that originated as an immiscible liquid within a fully differentiated melt; in several samples with ages to 32 Ma it displays very little or no oxidation (z = ca. 0). In contrast, samples with ages of 10 Ma or older are observed to also contain highly oxidized (z >/= 0.66) large-grained titanomaghemite. These large grains, having originated by direct crystallization from melt, are associated with pore space. Such pore space can serve as a conduit for fluids that promote alteration, whereas fine grains may have been "armored" against alteration by the glass matrix in which they are embedded. Apparently, alteration of oceanic crust is a heterogeneous process on a microscopic scale. The existence of pristine, fine-grained titanomagnetite in the interstitial glass of older ocean-floor basalts that have undergone significant alteration implies that such glassy material is capable of carrying original thermal remanent magnetization and may be suitable for paleointensity determinations.