Conceptual design of Americium nuclear battery for space power applications

This work presents simplified 242mAm-fueled nuclear battery concept design featuring direct fission products energy conversion and passive heat rejection. Optimization of the battery operating characteristics and dimensions was performed. The calculations of power conversion efficiency under thermal and nuclear design constraints showed that 5.6 W e/kg power density can be achieved, which corresponds to conversion efficiency of about 4%. A system with about 190 cm outer radius translates into 17.8 MT mass per 100 kW e. Total power scales linearly with the outer surface area of the battery through which the residual heat is rejected. Tradeoffs between the battery lifetime, mass, dimensions, power rating, and conversion efficiency are presented and discussed. The battery can be used in a wide variety of interplanetary missions with power requirements in the kW to MW range. Copyright © 2007 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

Americium nuclear battery for space power applications

The work presents simplified242mAm fueled nuclear battery concept design featuring direct fission products energy conversion and passive heat rejection. The performed calculations of power conversion efficiency under thermal and nuclear design constraints showed that 14 W/kg power density can be achieved, which corresponds to conversion efficiency of about 6%. Total power of the battery scales linearly with its surface area. 144 kW of electric power can be produced by a nuclear battery with an external radius of about 174 cm and total mass of less than 10300 kg. The mass of242m Am fuel for such a system is 3200 gram.

Hierarchically structured nanocarbon electrodes for flexible solid lithium batteries

The ever increasing demand for storage of electrical energy in portable electronic devices and electric vehicles is driving technological improvements in rechargeable batteries. Lithium (Li) batteries have many advantages over other rechargeable battery technologies, including high specific energy and energy density, operation over a wide range of temperatures (-40 to 70. °C) and a low self-discharge rate, which translates into a long shelf-life (~10 years) [1]. However, upon release of the first generation of rechargeable Li batteries, explosions related to the shorting of the circuit through Li dendrites bridging the anode and cathode were observed. As a result, Li metal batteries today are generally relegated to non-rechargeable primary battery applications, because the dendritic growth of Li is associated with the charging and discharging process. However, there still remain significant advantages in realizing rechargeable secondary batteries based on Li metal anodes because they possess superior electrical conductivity, higher specific energy and lower heat generation due to lower internal resistance. One of the most practical solutions is to use a solid polymer electrolyte to act as a physical barrier against dendrite growth. This may enable the use of Li metal once again in rechargeable secondary batteries [2]. Here we report a flexible and solid Li battery using a polymer electrolyte with a hierarchical and highly porous nanocarbon electrode comprising aligned multiwalled carbon nanotubes (CNTs) and carbon nanohorns (CNHs). Electrodes with high specific surface area are realized through the combination of CNHs with CNTs and provide a significant performance enhancement to the solid Li battery performance. © 2013 Elsevier Ltd.

The use of non-dimensional parameters to study stress in lithiumion battery electrode storage particles

Mechanical degradation is thought to be one of the causes of capacity fade within Lithium-Ion batteries. In this work we develop a coupled stress-diffusion model for idealized spherical storage particles, which is analogous to the development of thermal strains. We then non-dimensionalize the model and identify three important parameters that control the development of stress within these particles. We can therefore use a wide number of values for these parameters to make predictions about the stress responses of different materials. The maximum stress developed within the particle for different values of these parameters are plotted as stress maps. A two dimensional model of a battery was then developed, in order to study the effect of particle morphology. Copyright © 2012 by ASME.

An integrated 2-D model of a lithium ion battery: The effect of material parameters and morphology on storage particle stress

An integrated 2-D model of a lithium ion battery is developed to study the mechanical stress in storage particles as a function of material properties. A previously developed coupled stress-diffusion model for storage particles is implemented in 2-D and integrated into a complete battery system. The effect of morphology on the stress and lithium concentration is studied for the case of extraction of lithium in terms of previously developed non-dimensional parameters. These non-dimensional parameters include the material properties of the storage particles in the system, among other variables. We examine particles functioning in isolation as well as in closely-packed systems. Our results show that the particle distance from the separator, in combination with the material properties of the particle, is critical in predicting the stress generated within the particle. © 2012 Springer-Verlag.

Revealing lithium-silicide phase transformations in nano-structured silicon-based lithium ion batteries via in situ NMR spectroscopy.

Nano-structured silicon anodes are attractive alternatives to graphitic carbons in rechargeable Li-ion batteries, owing to their extremely high capacities. Despite their advantages, numerous issues remain to be addressed, the most basic being to understand the complex kinetics and thermodynamics that control the reactions and structural rearrangements. Elucidating this necessitates real-time in situ metrologies, which are highly challenging, if the whole electrode structure is studied at an atomistic level for multiple cycles under realistic cycling conditions. Here we report that Si nanowires grown on a conducting carbon-fibre support provide a robust model battery system that can be studied by (7)Li in situ NMR spectroscopy. The method allows the (de)alloying reactions of the amorphous silicides to be followed in the 2nd cycle and beyond. In combination with density-functional theory calculations, the results provide insight into the amorphous and amorphous-to-crystalline lithium-silicide transformations, particularly those at low voltages, which are highly relevant to practical cycling strategies.

Design and simulations of SOI CMOS micro-hotplate gas sensors

This paper describes a new generation of integrated solid-state gas-sensors embedded in SOI micro-hotplates. The micro-hotplates lie on a SOI membrane and consist of MOSFET heaters that elevate the operating temperature, through self-heating, of a gas sensitive material. These sensors are fully compatible with SOI CMOS or BiCMOS technologies, offer ultra-low power consumption (under 100 mW), high sensitivity, low noise, low unit cost, reproducibility and reliability through the use of on-chip integration. In addition, the new integrated sensors offer a nearly uniform temperature distribution over the active area at its operating temperatures at up to about 300-350°C. This makes SOI-based gas-sensing devices particularly attractive for use in handheld battery-operated gas monitors. This paper reports on the design of a chemo-resistive gas sensor and proposes for the first time an intelligent SOI membrane microcalorimeter using active micro-FET heaters and temperature sensors. A comprehensive set of numerical and analogue simulations is also presented including complex 2D and 3D electro-thermal numerical analyses. © 2001 Elsevier Science B.V. All rights reserved.

Streaming covariance selection with applications to adaptive querying in sensor networks

Sensor networks can be naturally represented as graphical models, where the edge set encodes the presence of sparsity in the correlation structure between sensors. Such graphical representations can be valuable for information mining purposes as well as for optimizing bandwidth and battery usage with minimal loss of estimation accuracy. We use a computationally efficient technique for estimating sparse graphical models which fits a sparse linear regression locally at each node of the graph via the Lasso estimator. Using a recently suggested online, temporally adaptive implementation of the Lasso, we propose an algorithm for streaming graphical model selection over sensor networks. With battery consumption minimization applications in mind, we use this algorithm as the basis of an adaptive querying scheme. We discuss implementation issues in the context of environmental monitoring using sensor networks, where the objective is short-term forecasting of local wind direction. The algorithm is tested against real UK weather data and conclusions are drawn about certain tradeoffs inherent in decentralized sensor networks data analysis. © 2010 The Author. Published by Oxford University Press on behalf of The British Computer Society. All rights reserved.

Diffusion and chemical reaction in the porous structures of solid oxide fuel cells

The Rolls-Royce Integrated-Planar Solid Oxide Fuel Cell (IP-SOFC) consists of ceramic modules which have electrochemical cells printed on the outer surfaces. The cathodes are the outermost layer of each cell and are supplied with oxygen from air flowing over the outside of the module. The anodes are in direct contact with the ceramic structure and are supplied with fuel from internal gas channels. Natural gas is reformed into hydrogen for use by the fuel cells in a separate reformer module of similar design except that the fuel cells are replaced by a reforming catalyst layer. The performance of the modules is intrinsically linked to the behaviour of the gas flows within their porous structures. Because the porous layers are very thin, a one-dimensional flow model provides a good representation of the flow property variations between fuel channel and fuel cell or reforming catalyst. The multi-component convective-diffusive flows are simulated using a new theory of flow in porous material, the Cylindrical Pore Interpolation Model. The effects of the catalysed methane reforming and water-gas shift chemical reactions are also considered using appropriate kinetic models. It is found that the shift reaction, which is catalysed by the anode material, has certain beneficial effects on the fuel cell module performance. In the reformer module it was found that the flow resistance of the porous support structure makes it difficult to sustain a high methane conversion rate. Although the analysis is based on IP-SOFC geometry, the modelling approach and general conclusions are applicable to other types of SOFC.

Zinc oxide nanowire based hydrogen sensor on SOI CMOS platform

Here we report on the successful low-temperature growth of zinc oxide nanowires (ZnONWs) on silicon-on-insulator (SOI) CMOS micro-hotplates and their response, at different operating temperatures, to hydrogen in air. The SOI micro-hotplates were fabricated in a commercial CMOS foundry followed by a deep reactive ion etch (DRIE) in a MEMS foundry to form ultra-low power membranes. The micro-hotplates comprise p+ silicon micro-heaters and interdigitated metal electrodes (measuring the change in resistance of the gas sensitive nanomaterial). The ZnONWs were grown as a post-CMOS process onto the hotplates using a CMOS friendly hydrothermal method. The ZnONWs showed a good response to 500 to 5000 ppm of hydrogen in air. We believe that the integration of ZnONWs with a MEMS platform results in a low power, low cost, hydrogen sensor that would be suitable for handheld battery-operated gas sensors. © 2011 Published by Elsevier Ltd.