Polyhedral monocarbaborane chemistry. Carboxylic acid derivatives of the [closo-2-CB9H10](-) anion

Reaction of B10H14 with para-(OHC)C6H4(COOH) in aqueous KOH gives the [nido-6-CB9H11-6-(C6H4-para-COOH)](-) anion I which upon cluster closure with iodine in alkali solution gives the [closo-2-CB9H9-2-(C6H4-para-COOH)](-) anion 2; an analogous procedure with B10H14 and glyoxalic acid OHCCOOH gives the [closo-2-CB9H9-2-(COOH)](-) anion 4 via the [arachno-6-CB9H13-6-(COOH)](-) anion 3

Molecular dynamics study of oxygen diffusion in Pr₂NiO_4+δ

Oxygen transport in tetragonal Pr2NiO4+δ has been investigated using molecular dynamics simulations in conjunction with a set of Born model potentials. Oxygen diffusion in Pr2NiO4+δ is highly anisotropic, occurring almost entirely via an interstitialcy mechanism in the a-b plane. The calculated oxygen diffusivity has a weak dependence upon the concentration of oxygen interstitials, in agreement with experimental observations. In the temperature range 800-1500 K, the activation energy for migration varied between 0.49 and 0.64 eV depending upon the degree of hyperstoichiometry. The present results are compared to previous work on oxygen self-diffusion in related K2NiF4 structure materials

Anisotropic oxygen diffusion in tetragonal La₂NiO_4+δ: molecular dynamics calculations

Molecular dynamics simulations, used in conjunction with a set of Born model potentials, have been employed to study oxygen transport in tetragonal La2NiO4+δ. We predict an interstitialcy mechanism with an activation energy of migration of 0.51 eV in the temperature range 800-1100 K. The simulations are consistent with the most recent experiments. The prevalence of oxygen diffusion in the a-b plane accounts for the anisotropy observed in measurements of diffusivity in tetragonal La2NiO4+δ

TauFactor: An open-source application for calculating tortuosity factors from tomographic data

TauFactor is a MatLab application for efficiently calculating the tortuosity factor, as well as volume fractions, surface areas and triple phase boundary densities, from image based microstructural data. The tortuosity factor quantifies the apparent decrease in diffusive transport resulting from convolutions of the flow paths through porous media. TauFactor was originally developed to improve the understanding of electrode microstructures for batteries and fuel cells; however, the tortuosity factor has been of interest to a wide range of disciplines for over a century, including geoscience, biology and optics. It is still common practice to use correlations, such as that developed by Bruggeman, to approximate the tortuosity factor, but in recent years the increasing availability of 3D imaging techniques has spurred interest in calculating this quantity more directly. This tool provides a fast and accurate computational platform applicable to the big datasets (>10^8 voxels) typical of modern tomography, without requiring high computational power

Development of lanthanum nickelate as a cathode for use in intermediate temperature solid oxide fuel cells

The performance of lanthanum nickelate, La2NiO4+δ (LNO), as a cathode in IT-SOFCs with the electrolyte cerium gadolinium oxide, Ce0.9Gd0.1O2−δ (CGO), has been investigated by AC impedance spectroscopy of symmetrical cells. A significant reduction in the area specific resistance (ASR) has been achieved with a layered cathode structure consisting of a thin compact LNO layer between the dense electrolyte and porous electrode. This decrease in ASR is believed to be a result of contact at the electrolyte/cathode boundary enhancing the oxygen ion transfer to the electrolyte. An ASR of 1.0 Ω cm2 at 700 °C was measured in a symmetrical cell with this layered structure, compared to an ASR of 7.4 Ω cm2 in a cell without the compact layer. In addition, further improvements were observed by enhancing the cell current collection and it is anticipated that a symmetrical cell consisting of a layered structure with adequate current collection would lower these ASR values further

Interstitialcy diffusion of oxygen in tetragonal La₂CoO_4+δ

We report on the mechanism and energy barrier for oxygen diffusion in tetragonal La2CoO4+δ. The first principles-based calculations in the Density Functional Theory (DFT) formalism were performed to precisely describe the dominant migration paths for the interstitial oxygen atom in La2CoO4+δ. Atomistic simulations using molecular dynamics (MD) were performed to quantify the temperature dependent collective diffusivity, and to enable a comparison of the diffusion barriers found from the force field-based simulations to those obtained from the first principles-based calculations. Both techniques consistently predict that oxygen migrates dominantly via an interstitialcy mechanism. The single interstitialcy migration path involves the removal of an apical lattice oxygen atom out from the LaO-plane and placing it into the nearest available interstitial site, whilst the original interstitial replaces the displaced apical oxygen on the LaO-plane. The facile migration of the interstitial oxygen in this path is enabled by the cooperative titling-untilting of the CoO6 octahedron. DFT calculations indicate that this process has an activation energy significantly lower than that of the direct interstitial site exchange mechanism. For 800-1000 K, the MD diffusivities are consistent with the available experimental data within one order of magnitude. The DFT- and the MD-predictions suggest that the diffusion barrier for the interstitialcy mechanism is within 0.31-0.80 eV. The identified migration path, activation energies and diffusivities, and the associated uncertainties are discussed in the context of the previous experimental and theoretical results from the related Ruddlesden-Popper structures

Altering movement parameters disrupts metacognitive accuracy

Correctly estimating the confidence we should have in our decisions has traditionally been viewed as a perceptual judgement based solely on the strength or quality of sensory information. However, accumulating evidence has demonstrated that the motor system contributes to judgements of perceptual confidence. Here, we manipulated the speed at which participants' moved using a behavioural priming task and showed that increasing movement speed above participants' baseline measures disrupts their ability to form accurate confidence judgements about their performance. Specifically, after being primed to move faster than they would naturally, participants reported higher confidence in their incorrect decisions than when they moved at their natural pace. We refer to this finding as the adamantly wrong effect. The results are consistent with the hypothesis that veridical feedback from the effector used to indicate a decision is employed to form accurate metacognitive judgements of performance

Oxygen diffusion in Sr_0.75Y_0.25CoO_2.625: a molecular dynamics study

Oxygen diffusion in Sr0.75Y0.25CoO2.625 is investigated using molecular dynamics simulations in conjunction with an established set of Born model potentials. We predict an activation energy of diffusion for 1.56 eV in the temperature range of 1000-1400 K. We observe extensive disordering of the oxygen ions over a subset of lattice sites. Furthermore, oxygen ion diffusion both in the a-b plane and along the c axis requires the same set of rate-limiting ion hops. It is predicted that oxygen transport in Sr0.75Y0.25CoO2.625 is therefore isotropic

Emotional representations of space vary as a function of peoples' affect and interoceptive sensibility

Most research on people’s representation of space has focused on spatial appraisal and navigation. But there is more to space besides navigation and assessment: people have different emotional experiences at different places, which create emotionally tinged representations of space. Little is known about the emotional representation of space and the factors that shape it. The purpose of this study was to develop a graphic methodology to study the emotional representation of space and some of the environmental features (non-natural vs. natural) and personal features (affective state and interoceptive sensibility) that modulate it. We gave participants blank maps of the region where they lived and asked them to apply shade where they had happy/sad memories, and where they wanted to go after Covid-19 lockdown. Participants also completed self-reports on affective state and interoceptive sensibility. By adapting methods for analyzing neuroimaging data, we examined shaded pixels to quantify where and how strong emotions are represented in space. The results revealed that happy memories were consistently associated with similar spatial locations. Yet, this mapping response varied as a function of participants’ affective state and interoceptive sensibility. Certain regions were associated with happier memories in participants whose affective state was more positive and interoceptive sensibility was higher. The maps of happy memories, desired locations to visit after lockdown, and regions where participants recalled happier memories as a function of positive affect and interoceptive sensibility overlayed significantly with natural environments. These results suggest that people’s emotional representations of their environment are shaped by the naturalness of places, and by their affective state and interoceptive sensibility

Prediction of the functional properties of ceramic materials from composition using artificial neural networks

We describe the development of artificial neural networks (ANN) for the prediction of the properties of ceramic materials. The ceramics studied here include polycrystalline, inorganic, non-metallic materials and are investigated on the basis of their dielectric and ionic properties. Dielectric materials are of interest in telecommunication applications where they are used in tuning and filtering equipment. Ionic and mixed conductors are the subjects of a concerted effort in the search for new materials that can be incorporated into efficient, clean electrochemical devices of interest in energy production and greenhouse gas reduction applications. Multi-layer perceptron ANNs are trained using the back-propagation algorithm and utilise data obtained from the literature to learn composition-property relationships between the inputs and outputs of the system. The trained networks use compositional information to predict the relative permittivity and oxygen diffusion properties of ceramic materials. The results show that ANNs are able to produce accurate predictions of the properties of these ceramic materials which can be used to develop materials suitable for use in telecommunication and energy production applications