Design and optimization of radioisotope sources for betavoltaic batteries |
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| Authors: | Tariq R. Alam Michael G. Spencer Mark A. Prelas Mark A. Pierson |
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| Affiliation: | 1. Department of Mechanical Engineering, Virginia Tech, Blacksburg, VA, USA;2. School of Engineering, Morgan State University, Baltimore, MD, USA;3. Nuclear Science and Engineering Institute, University of Missouri, Columbia, MO, USA |
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| Abstract: | A Monte Carlo source model using PENELOPE was developed to investigate different tritiated metals in order to design a better radioisotope source for betavoltaic batteries. The source model takes into account the self‐absorption of beta particles in the source which is a major factor for an efficient source design. The average beta energy, beta flux, source power output, and source efficiency were estimated for various source thicknesses. The simulated results for titanium tritide with 0° and 90° angular distributions of beta particles were validated with experimental results. The importance of the backscattering effect due to isotropic particle emission was analyzed. The results showed that the normalized average beta energy increases with the source thickness, and it reaches peak energy depending on the density and the specific activity of the source. The beta flux and power output also increase with increasing source thickness. However, the incremental increase in beta flux and power output becomes minimal for higher thicknesses, as the source efficiency decreases significantly at higher thicknesses due to the self‐absorption effect. Thus, a saturation threshold is reached. A low‐density source material such as beryllium tritide provided a higher power output with higher efficiency. A maximum power output of approximately 4 mW/cm3 was obtained for beryllium tritide with SiC. A form factor approach was used to estimate the optimum source thickness. The optimum source thickness was found near the thickness where the peak beta particle average energy occurs. |
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| Keywords: | beta flux betavoltaic batteries self‐absorption source optimization |
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