Denis Wisniewski

Theoretical Maximum Efficiency for a Linearly Graded Alphavoltaic Nuclear Battery

This paper presents a study on the optimization of the amount of energy deposited by alpha particles in the depletion region of a silicon carbide (SiC) alphavoltaic cell using Monte Carlo models. Three Monte Carlo codes were used in this study: SRIM/TRIM, GEANT4, and MCNPX. The models examined the transport of 5.307-MeV alpha particles emitted by 210Po. Energy deposition in a 1-μm depletion region of SiC was calculated using an isotropic alpha source for a spherical geometry using GEANT4, and a monodirectional alpha source for a slab geometry using both SRIM/TRIM and GEANT4. In addition, an isotropic point source was modeled using GEANT4 and MCNPX for a slab geometry. These geometries were optimized for the maximum possible alphavoltaic energy efficiency. The models, which match very well, indicate that the maximum theoretical energy conversion efficiency, which was optimized for a SiC alphavoltaic cell, is [approximately]3.6% for the isotropic alpha source on a slab geometry and 2.1% for both the monodirectional alpha source on a slab geometry and the isotropic alpha source at the center of a sphere. This study provides a useful guide governing the upper limit of expected efficiency for an alphavoltaic cell using a linearly graded single junction SiC transducer.

Theoretical Maximum Efficiencies of Optimized Slab and Spherical Betavoltaic Systems Utilizing Sulfur-35, Strontium-90, and Yttrium-90

Monte Carlo simulations have been used for calculating the energy deposition of beta particles in the depletion region of a silicon carbide (SiC) betavoltaic cell along with the corresponding theoretical efficiencies. Three Monte Carlo codes were used in the study: GEANT4, PENELOPE, and MCNPX. These codes were used to examine the transportation of beta particles from 90Y, 90Sr, and 35S. Both the average beta energy from each source and the entire spectrum were modeled for calculating maximum theoretical energy deposition in both a spherical and slab geometry. A simulated depletion region was added in postprocessing containing the maximum energy deposited per micrometer. The calculated maximum efficiencies with the slab configuration model are approximately 1.95%, 0.30%, and 0.025% using monoenergetic average energy and 1.54%, 0.25%, and 0.019% using an energy spectrum for 35S, 90Sr, and 90Y, respectively. These efficiencies when using the spherical configuration model are 2.02%, 0.31%, and 0.023% using the monoenergetic average energy and 1.10%, 0.17%, and 0.013% using an energy spectrum for 35S, 90Sr, and 90Y, respectively.

Introduction to Nuclear Batteries and Radioisotopes

This chapter provides the reader with background and fundamental information on the subject of nuclear batteries. The approach used in this chapter is to describe the characteristics of a nuclear battery relying on easy to understand physical properties. For example, a commonly used descriptive parameter is the maximum power density. However, a more intuitive parameter is to use the inverse of maximum power density and define a quantity of minimum volume per Watt for a radioisotope volume source or minimum surface area per Watt for a radioisotope surface source. This approach gives the reader a feel for actual dimensional limitations of the technology as well as other constraints.

Potential Applications for Nuclear Batteries

The obvious attributes of radioisotopes are a large amount of energy stored per unit mass and long life-time. These properties have been the primary motivation in the development of nuclear batteries driven with radioisotopes. The applications have changed over time based on the evolution of technology. In this chapter, successful nuclear battery designs are discussed along with the applications that they were designed for. In addition, the technologies which have evolved over time requiring significant energy storage and long shelf lives are discussed.

Interactions of Ionizing Radiation with Matter and Direct Energy Conversion

Ionizing radiation is a broad term which refers to the fact that different types of radiation will create ion pairs in matter. Ionizing radiation includes ions (e.g., fission fragments and alpha particles), beta particles, gamma rays, x-rays, and neutrons. Radioisotopes emit ionizing radiation and are viewed as the primary power source for nuclear batteries. This chapter will explore various radioisotope sources and their properties. The transducers which can be used in concert with radioisotope sources will be discussed.

Power Density Dilution Due to the Interface of the Isotope with the Transducer

In chapter 4, definitions for various types of dilution factors for a nuclear battery are discussed. The average atomic density of the radioisotope in a nuclear battery cell is described and a relationship between the average atomic density and dilution factor are derived. The dilution factor will impact the minimum scale and the power density of the battery. It is an important parameter that is used in the assessment of nuclear battery designs.

Efficiency Limitations for Various Nuclear Battery Configurations

A nuclear battery can be viewed as a radiation source embedded in various layers of materials with one of the layers being a transducer. The goal of nuclear battery design is to deposit as much of the power produced by the source into the transducer. Nuclear battery designs vary depending on the source, the transducer and the method by which the source and transducer are interfaced. It is this variability in design which can obfuscate the simple nature of the design. This chapter’s focus is on the fundamental vision of nuclear battery design.