Diffusion-emission theory of photon enhanced thermionic emission solar energy harvesters

Numerical and semi-analytical models are presented for photon-enhanced-thermionic-emission (PETE) devices. The models take diffusion of electrons, inhomogeneous photogeneration, and bulk and surface recombination into account. The efficiencies of PETE devices with silicon cathodes are calculated. Our model predicts significantly different electron affinity and temperature dependence for the device than the earlier model based on a rate-equation description of the cathode. We show that surface recombination can reduce the efficiency below 10% at the cathode temperature of 800 K and the concentration of 1000 suns, but operating the device at high injection levels can increase the efficiency to 15%.Comment: 5 pages, 4 figure

Capturing nonlinear dynamics of two-fluid Couette flows with asymptotic models

The nonlinear stability of two-fluid Couette flows is studied using a novel evolution equation whose dynamics are validated by direct numerical simulations (DNS). The evolution equation incorporates inertial effects at arbitrary Reynolds numbers through a non-local term arising from the coupling between the two fluid regions, and is valid when one of the layers is thin. The equation predicts asymmetric solutions and exhibits bistability, features that are essential observations in the experiments of Barthelet et al. (1995). Related low-inertia models have been used in qualitative predictions rather than the direct comparisons carried out here, and ad hoc modifications appear to be necessary in order to predict asymmetry and bistability. Comparisons between model solutions and DNS show excellent agreement at Reynolds numbers of O(10³) found in the experiments. Direct comparisons are also made with the available experimental results of Barthelet et al. (1995) when the thin layer occupies 1/5 of the channel height. Pointwise comparisons of the travelling wave shapes are carried out and once again the agreement is very good

Mechanism Design in Social Networks

This paper studies an auction design problem for a seller to sell a commodity in a social network, where each individual (the seller or a buyer) can only communicate with her neighbors. The challenge to the seller is to design a mechanism to incentivize the buyers, who are aware of the auction, to further propagate the information to their neighbors so that more buyers will participate in the auction and hence, the seller will be able to make a higher revenue. We propose a novel auction mechanism, called information diffusion mechanism (IDM), which incentivizes the buyers to not only truthfully report their valuations on the commodity to the seller, but also further propagate the auction information to all their neighbors. In comparison, the direct extension of the well-known Vickrey-Clarke-Groves (VCG) mechanism in social networks can also incentivize the information diffusion, but it will decrease the seller's revenue or even lead to a deficit sometimes. The formalization of the problem has not yet been addressed in the literature of mechanism design and our solution is very significant in the presence of large-scale online social networks.Comment: In The Thirty-First AAAI Conference on Artificial Intelligence, San Francisco, US, 04-09 Feb 201

Nonlinear dynamics of surfactant-laden two-fluid Couette flows in the presence of inertia

The nonlinear stability of immiscible two–fluid Couette flows in the presence of inertia is considered. The interface between the two viscous fluids can support insoluble surfactants and the interplay between the underlying hydrodynamic instabilities and Marangoni ef- fects is explored analytically and computationally in both two and three dimensions. Asymptotic analysis when one of the layers is thin relative to the other yields a coupled system of nonlinear equations describing the spatiotemporal evolution of the interface and its local surfactant concentration. The system is nonlocal and arises by appropri- ately matching solutions of the linearised Navier–Stokes equations in the thicker layer to the solution in the thin layer. The scaled models are used to study different physical mechanisms by varying the Reynolds number, the viscosity ratio between the two layers, the total amount of surfactant present initially and a scaled P ́eclet number measuring diffusion of surfactant along the interface. The linear stability of the underlying flow to two– and three–dimensional disturbances is investigated and a Squire’s type theorem is found to hold when inertia is absent. When inertia is present, three–dimensional distur- bances can be more unstable than two–dimensional ones and so Squire’s theorem does not hold. The linear instabilities are followed into the nonlinear regime by solving the evo- lution equations numerically; this is achieved by implementing highly accurate linearly implicit schemes in time with spectral discretisations in space. Numerical experiments for finite Reynolds numbers indicate that for two–dimensional flows the solutions are mostly nonlinear travelling waves of permanent form, even though these can lose stabil- ity via Hopf bifurcations to time–periodic travelling waves. As the length of the system (that is the wavelength of periodic waves) increases, the dynamics become more complex and include time–periodic, quasi–periodic as well as chaotic fluctuations. It is also found that one–dimensional interfacial travelling waves of permanent form can become unstable to spanwise perturbations for a wide range of parameters, producing three–dimensional flows with interfacial profiles that are two–dimensional and travel in the direction of the underlying shear. Nonlinear flows are also computed for parameters which predict linear instability to three–dimensional disturbances but not two–dimensional ones. These are found to have a one–dimensional interface in a rotated frame with respect to the direction of the underlying shear and travel obliquely without changing form

Substitutional effects of in by Cu in CeIn2

We have investigated the evolution of the magnetic properties on the Ce(In1'xCux)2 (0 < x ≤ 0.3) series of alloys. The orthorhombic structure of the CeIn2 alloy (Imma) changes into the hexagonal AlB2-type (P6/mmm) for x = 0.05 and, then, into the hexagonal CaIn2-type (P63/mmm) for higher Cu concentrations, up to x = 0.3. The dc (ac) magnetic susceptibility shows an abrupt decrease of the magnetic transition temperature from 22 K to 5.4 K (x = 0.05). The results indicate the influence of the crystallographic type of structure and disorder effects on the magnetic behavior along the series. © Owned by the authors, published by EDP Sciences, 2014

Thermomagnetic and magnetocaloric properties of metamagnetic Ni-Mn-In-Co Heusler alloy in magnetic fields up to 140 kOe

High cooling power of magnetocaloric refrigeration can be achieved only at large amounts of heat, which can be transferred in one cycle from cold end hot end at quasi-isothermal conditions. The simple and robust experimental method of direct measuring of the transferred heat of materials with magnetocaloric effect (MCE) in thermal contact with massive copper block with definite heat capacity in quasi-isothermal regime was proposed. The vacuum calorimeter for the specific transferred heat ∆Q and adiabatic temperature change ∆T measurements of MCE materials in the fields of Bitter coil magnet up to H = 140 kOe was designed and tested on samples of Ni43Mn37.9In12.1Co7 Heusler alloy with inverse MCE in the vicinity of meta-magnetostructural phase transition (PT). It was found, that the magnetic field H = 80 kOe produces complete PT from martensite to austenite with ∆Q = - 1600 J/kg at initial temperature 273 K

Neural network controller for active demand side management with PV energy in the residential sector

In this paper, we describe the development of a control system for Demand-Side Management in the residential sector with Distributed Generation. The electrical system under study incorporates local PV energy generation, an electricity storage system, connection to the grid and a home automation system. The distributed control system is composed of two modules: a scheduler and a coordinator, both implemented with neural networks. The control system enhances the local energy performance, scheduling the tasks demanded by the user and maximizing the use of local generation