The influence of activated carbon as an additive in anode materials for low temperature solid oxide fuel cells

The effects of activated carbon (AC) as an additive in multi-oxide nano composite LiNiCuZn–O for application as anode in solid oxide fuel cell (SOFC) is reported. The composite was synthesized using solid state reactions method with varying content of AC in range 0.1%–0.9% for use as anode in the cell. The cell was composed of the synthesized composite as anode, LiNiCuZn–O as cathode and Samaria doped ceria (SDC) as electrolyte. The prepared composites were characterized for morphology and crystal structure by scanning electron microscope (SEM) and x-ray diffraction (XRD) respectively. Furthermore, the crystallite sizes of LiNiCuZn–O and LiNiCuZn–O with AC as an additive have been found in the range from 50 nm to 70 nm. The prepared composite materials were observed porous and the porosity of the sample having 0.5% additive was found highest. The conductivity and power density of the SOFC were studied at temperature of 600 °C. The maximum value of conductivity was found as 4.79 S/cm for the composite containing 0.5% AC as measured by using 4-probe method. The maximum value of power density of the fuel cell with anode comprising of 0.5% AC along with the mentioned cathode and the electrolyte was 455 mW/cm². Therefore, out of the compositions studied, the composite comprising of LiNiCuZn–O with 0.5% AC offered best performance for anode in the cell. This oxide composite is reported as a potential candidate for use as anode in low temperature SOFCs.     

A model for multicomponent diffusion in oxide melts

A general flux equation for multicomponent diffusion in oxide melts is presented. An explicit method was developed to calculate the gradients of single-ion activities from those of oxides with the constraints of local equilibrium and electroneutrality. This resolves ambiguity in quantifying the thermochemical driving force for ionic diffusion. A model equation for multicomponent ionic diffusion was derived within the framework of non-equilibrium thermodynamics by de Groot and Mazur. The proposed model takes empirically measurable quantities as input variables, so the diffusion calculations are consistent with thermochemical data, as furnished by the CALPHAD (CALculation of PHAse Diagrams) method, as well as ionic mobility measurements. Although the model is derived for oxides, it can be applied to diffusion in other concentrated liquid electrolytes, such as chloride and fluoride melts. Formulas for multicomponent ionic diffusion in various reference frames are presented with respect to mole fraction.     

Why do people purchase virtual goods? A uses and gratification (U&G) theory perspective

Few literature studies have investigated the relationships between different uses and gratifications (U&Gs) of mobile instant messaging (MIM) apps, continuation, and purchase intentions. To address this gap, the researchers aimed to examine the influence of the content, social, process, and technology U&Gs of MIM on continuation intentions toward MIMs, and purchase intentions toward virtual goods available on MIMs. A comprehensive research model was developed based on the U&G theory, which was tested using cross-sectional data from 309 Japanese MIM users. The study considered six different U&Gs of MIM as independent variables and purchase intentions towards stickers and continuation intentions towards MIM as dependent variables. The study results suggest that exposure U&G has a significant positive association with MIM sticker purchase intentions. The entertainment and affection U&G are positively associated with continuation intentions towards MIM use. The study contributes to the literature by investigating U&Gs that motivate MIM users to have both positive purchase intentions toward virtual goods, such as stickers, and continuation intentions toward MIMs. The study has significant theoretical and practical implications for both researchers and practitioners who are interested in virtual goods, the virtual economy, MIM apps, social media, new media, and the service economy.     

Non-singular antiplane fracture theory within nonlocal anisotropic elasticity

In the present paper, the distributed dislocation technique is applied for the analysis of anisotropic materials weakened by cracks. Eringen's theory of nonlocal elasticity of Helmholtz type is employed. The non-singular screw dislocation within anisotropic elasticity is distributed to model cracks of mode III. The corresponding dislocation density functions are evaluated using the proper crack-face boundary conditions. The nonlocal stress field within a plane weakened by cracks is determined. The crack opening displacement is also discussed within the framework of nonlocal elasticity. The stress singularity of the classical linear elasticity is removed by the introduction of the nonlocal theory of elasticity. The general anisotropic case and the special case of orthotropic material are studied. The effect of material orthotropy is presented for a crack which is not necessarily aligned with the principal orthotropy direction.     

Robot learning through task identification

The operation of an autonomous mobile robot in a semi-structured environment is a complex, usually non-linear and partly unpredictable process. Lacking a theory of robot–environment interaction that allows the design of robot control code based on theoretical analysis, roboticists still have to resort to trial-and-error methods in mobile robotics.The RobotMODIC project aims to develop a theoretical understanding of a robot’s interaction with its environment, and uses system identification techniques to identify the system robot–task–environment. In this paper, we present two practical examples of the RobotMODIC process: mobile robot self-localisation and mobile robot training to achieve door traversal.In both examples, a transparent mathematical function is obtained that maps inputs–sensory perception in both cases–to output — location and steering velocity respectively. Analysis of the obtained models reveals further information about the way in which a task is achieved, the relevance of individual sensors, possible ways of obtaining more parsimonious models, etc.     

OPAH a model for optimal design of multipurpose small hydropower plants

The investment in small hydropower plants requires the analysis of hydrological, technical, operational, budgetary, economical and financial aspects. The analysis of each possible configuration demands the joint action of several technicians, consuming substantial time and money. During initial design of the project, simplified procedures are usually adopted which may compromise the quality of the base configuration.In this paper we will present a global overview of the OPAH model, which was developed to surpass these limitations. This global model performs the optimization of project configuration. This model uses non-linear programming optimization to analyze the multipurpose operation of the hydropower plant. It uses a numeric simulation model of unsteady flow under pressure to analyze the hydraulic circuit. It uses an economical and financial simulation model that takes in to account the project risk associated to hydrologic and market variability, the financial capacity of the investor and the fiscal aspects.     

Eye-tracking for user modeling in exploratory learning environments: An empirical evaluation

In this paper, we describe research on using eye-tracking data for on-line assessment of user meta-cognitive behavior during interaction with an environment for exploration-based learning. This work contributes to user modeling and intelligent interfaces research by extending existing research on eye-tracking in HCI to on-line capturing of high-level user mental states for real-time interaction tailoring. We first describe the empirical work we did to understand the user meta-cognitive behaviors to be modeled. We then illustrate the probabilistic user model we designed to capture these behaviors with the help of on-line information on user attention patterns derived from eye-tracking data. Next, we describe the evaluation of this model, showing that gaze-tracking data can significantly improve model performance compared to lower level, time-based evidence. Finally, we discuss work we have done on using pupil dilation information, also gathered through eye-tracking data, to further improve model accuracy.     

Habits make smartphone use more pervasive

Examining several sources of data on smartphone use, this paper presents evidence for the popular conjecture that mobile devices are “habit-forming.” The form of habits we identified is called a checking habit: brief, repetitive inspection of dynamic content quickly accessible on the device. We describe findings on kinds and frequencies of checking behaviors in three studies. We found that checking habits occasionally spur users to do other things with the device and may increase usage overall. Data from a controlled field experiment show that checking behaviors emerge and are reinforced by informational “rewards” that are very quickly accessible. Qualitative data suggest that although repetitive habitual use is frequent, it is experienced more as an annoyance than an addiction. We conclude that supporting habit-formation is an opportunity for making smartphones more “personal” and “pervasive.”