Affiliation:
1. Institute of Microelectronics Technology RAS, Acad. Osipian Str. 6, 142432 Chernogolovka, Russia
Abstract
The approaches for predicting output parameters of betavoltaic batteries are reviewed. The need to develop a strategy for predicting these parameters with sufficient accuracy for the optimization of betavoltaic cell design without using the simple trial and error approach is discussed. The strengths and weaknesses of previously proposed approaches for the prediction are considered. Possible reasons for the difference between the calculated and measured parameters are analyzed. The depth dependencies of beta particles deposited energy for Si, SiC, GaN, and Ga2O3 and 20% purity 63Ni and titanium tritide as radioisotope sources are simulated using the Monte Carlo algorithm taking into account the full beta energy spectrum, the isotropic angular distribution of emitted electrons and the self-absorption inside the radioisotope source for homogeneously distributed emitting points. The maximum short circuit current densities for the same semiconductors and radioisotope sources are calculated. The methodology allowing the prediction of betavoltaic cell output parameters with accuracy no worse than 30% is described. The results of experimental and theoretical investigations of the temperature dependence of betavoltaic cell output parameters are briefly discussed. The radiation damage by electrons with the subthreshold energy and the need to develop models for its prediction is considered.
Subject
Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous),Building and Construction
Reference125 articles.
1. Betavoltaic power sources;Olsen;Phys. Today,2012
2. A review of nuclear batteries;Prelas;Progr. Nucl. Energy,2014
3. Advances in Betavoltaic Power Sources;Revankar;J. Energy Power Sources,2014
4. Principles of Betavoltaic Battery Design;Alam;J. Energy Power Sources,2016
5. High power direct energy conversion by nuclear batteries;Spencer;Appl. Phys. Rev.,2019
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献