انتخاب بهینه مبدل نیمه‌هادی جهت افزایش توان و بازدهی در باتری‌های بتاولتائیک با چشمه‌های بتازای 3H، 63Ni و 147Pm

نوع مقاله : مقاله پژوهشی

نویسندگان

گروه فیزیک، دانشکده و پژوهشکده علوم پایه، دانشگاه جامع امام حسین (ع)، صندوق پستی 1698715461، تهران-ایران

چکیده

مواد نیمه‌هادی به‌عنوان مبدل انرژی گسیلی به انرژی الکتریکی در باتری‌های بتاولتائیک نقش مهمی را ایفا می‌کند. انتخاب بهینه آن‌ها باعث افزایش بازدهی در این باتری‌ها خواهد شد. در این پژوهش بر اساس نیمه‌هادی‌های متداول و با تکیه ‌بر افزایش حداکثری بازدهی باتری بتاولتائیک و امکان به‌کارگیری چشمه‌های بتازای 63Ni ،3H و 147Pm، شاخص‌ها و معیارهای انتخاب بهینه مواد نیمه‌هادی مشخص گردید. معیارهای ارزیابی شامل ضریب پس‌پراکندگی ذرات بتا از نیمه‌هادی، بازدهی تولید زوج الکترون-حفره، مشخصات و ویژ‌گی‌های الکترونیکی، آستانه آسیب تابشی، بهره تولید تابش ترمزی، توان توقف و نفوذ ذرات بتا در نیمه‌هادی، مشخصات فیزیکی و تحمل دمایی، قابلیت دسترسی و ساخت در نظر گرفته‌شده است. بر اساس این معیارها و با مقایسه با نیمه‌هادی سیلیکون، نیمه‌هادی‌های متداول مورد ارزیابی کمی قرار گرفته‌شده است. تعداد ده نیمه‌هادی B4C ،MgO ،AlN ،C-BN ،6H-SiC ،4H-SiC ،3C-SiC ،2H-SiC ،Diamond ،β-B باعدد اتمی مؤثر کم‌تر از 14 و باند گپ بالاتر از 1/12 الکترون‌ولت در دمای اتاق (K 300) در مقایسه با نیمه‌هادی سیلیکون، مورد ارزیابی قرار گرفت. با توجه به نتایج حاصل از شاخص‌های ارزیابی، نیمه‌هادی‌های 4H-SiC ،c-BN ،Diamond گزینه‌های مناسب‌تر از نظر بازدهی انتخاب گردید. با توجه به ارزیابی‌های انجام‌شده در این پژوهش، برای ساختارهای دو بعدی باتری بتاولتائیک نوع پیوند نیمه‌هادی برای الماس از نوع شاتکی با رادیوایزوتوپ 147pm، همچنین برای نیمه‌هادی 4H-SiC با رادیوایزوتوپ‌های 63Ni و یا 3H و برای ساختارهای سه‌بعدی باتری‌های بتاولتائیک ترکیب Si با رادیوایزوتوپ‌های 147pm و یا 63Ni پیشنهاد می‌گردد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

The Optimal Choice of Semiconductor Converter to Increase Power and Efficiency in Betavoltaic Batteries with 3H, 63Ni, and 147Pm Beta Sources

نویسندگان [English]

  • D. Ghasemabadi
  • H. Zaki Dizaji
  • M Abdollahzade
Department of Physics, Faculty of Basic Sciences, Imam Hossein Comprehensive University, P.O.Box: 1698715461, Tehran - Iran
چکیده [English]

Semiconductor materials play an important role as transmitters of electrical energy in betavoltaic batteries. Optimal selection will increase the efficiency of these batteries. In this study, based on common semiconductors and relying on increasing the maximum efficiency of betavoltaic batteries and the possibility of using 3H, 63Ni, and 147Pm beta sources, the indicators and criteria for optimal selection of semiconductor materials were determined. Evaluation criteria include backscattering coefficient of beta particles from semiconductors, efficiency of electron-hole pairs generation, electronic specifications and properties, radiation damage threshold, radiation yield, stopping power and penetration of beta particles in semiconductors, physical characteristics, and temperature tolerance, accessibility, and fabrication were considered. Based on these criteria and compared with silicon semiconductors, conventional semiconductors have been quantitatively evaluated. Ten semiconductors including β-B, Diamond, 2H-SiC, 3C-SiC, 4H-SiC, 6H-SiC, c-BN, AlN, MgO, B4C with effective atomic number less than 14 and bandgap above 1.12 eV at room temperature (300K) compared to silicon semiconductors were evaluated. Considering the results of evaluation indicators, Diamond, c-BN, and 4H-SiC were selected as more suitable semiconductors in terms of efficiency. Based on the experiments performed in this study, a betavoltaic semiconductor type junction for Schottky diamond with 147pm radioisotope, for 4H-SiC semiconductors with 63Ni or 3H radioisotopes, and for three-dimensional structures of betavoltaic batteries, Si combination with 147pm or 63Ni radioisotopes is recommended for planar batteries.

کلیدواژه‌ها [English]

  • Semiconductor
  • Battery
  • Betavoltaic
  • Efficiency
  • Evaluation criteria
  • Optimal choice
  1. Naseem MB, Kim HS, Lee J, Kim CH, In SI. Betavoltaic nuclear battery: A review of recent progress and challenges as an alternative energy source. J Phys Chem C. 2023;127(16):7565–79. https://doi.org/10.1021/acs.jpcc.3c00684
  2. Kim HS, Lee J, Lee S, Powar NS, Naseem MB, Kim CH, et al. Multiple-year battery based on highly efficient and stable dual-site radioactive isotope dye-sensitized betavoltaic cell. J Power Sources. 2024; 606:234427. https://doi.org/10.1016/j.jpowsour.2024.234427
  3. Guo H, Lal A. Nano power betavoltaic micro batteries. In: Proceedings of the 12th International Conference on Solid-State Sensors, Actuators and Microsystems (TRANSDUCERS '03); 2003 June 8-12; Boston, MA, USA. IEEE; 2003. p. 36–9. https://doi.org/10.1109/ SENSOR.2003.1215247
  4. Zhao C, Lei L, Liao F, Yuan D, Zhao Y. Efficiency prediction of planar betavoltaic batteries basing on precise modeling of semiconductor units. Appl Phys Lett. 2020;117 (26):263901. https://doi.org/10.1063/ 5.0033052
  5. Zheng R, Lu J, Wang Y, Chen Z, Zhang X, Li X, et al. Understanding efficiency improvements of betavoltaic batteries based on 4H-SiC, GaN, and diamond. Appl Phys Lett. 2022;121(10): 103902. https://doi.org/10.1063/5.0102995
  6. Zhao C, Liao F, Liu K, Zhao Y. Breaking the myth: Wide-bandgap semiconductors not always the best for betavoltaic batteries. Appl Phys Lett. 2021;119 (15):153904. https://doi.org/10.1063/5.0068269
  7. Pierson MA. Principles of betavoltaic battery design. J Energy Power Sources. 2016; 3:11–41.
  8. Adams T, Revankar S, Cabauy P, Elkind B, Cheu D. Betavoltaic performance under extreme Nucl Technol Radiat Prot. 2016; 31 (4):356–60. https://doi.org/10.2298/NTRP1604 356A
  9. Mohamadian M. Conceptual design and simulation of nuclear battery using in artificial cardiac pacemaker. Amirkabir University of Technology; 2008.
  10. Ghasemi Nejad GR, Rahmani F, Abaeiani GR. Design and optimization of beta-cell temperature sensor based on 63Ni–Si. Appl Radiat Isot. 2014; 86: 46–51. https://doi.org/10.1016/j.apradiso.2013.12.027.
  11. Rahmani F, Khosravinia H. Optimization of silicon parameters as a betavoltaic battery: Comparison of Si p-n and Ni/Si Schottky barrier. Radiat Phys Chem. 2016; 125: 205–12. https://doi.org/10.1016/j.radphyschem. 2016.04.012
  12. Amirmazlaghani M. Design and simulation of a radioisotope battery based on PtSi/Si Schottky diode. Nuclear Conference; 2014. (in Persian)
  13. Mirahmadi Babaheidari J. Study of an emission-electric converter based on semiconductor materials. University of Zanjan; 2014. (in Persian)
  14. Movahedian Z, Tavakoli-Anbaran H. Design and optimization of Si-35S betavoltaic liquid nuclear battery in micro dimensions in order to build. Ann Nucl Energy. 2020; 143:107483. https://doi.org/10. 1016/j.anucene.2020.107483
  15. Maleki P. Enhancing the simulation capabilities of betavoltaic micro batteries using the combined MCNPX-SILVACO code. J Nucl Sci Technol. 2019 (in Persian).
  16. Liu Y, Hu R, Yang Y, Wang G, Luo S, Liu N. Investigation on a radiation tolerant betavoltaic battery based on Schottky barrier diode. Appl Radiat Isot. 2012; 70(3): 438–41. https://doi.org/10.1016/j. apradiso.2011.10.013
  17. Alam TR, Pierson MA. Principles of betavoltaic battery design. J Energy Power Sources. 2016; 3(1): 11–41.
  18. Krasnov AA, Legotin SA. Advances in the development of betavoltaic power sources (a review). Instrum Exp Tech. 2020;63(4):437–52. https://doi. org/10.1134/S0020441220040156
  19. Tang X, Ding D, Liu Y, Chen D. Optimization design and analysis of Si-63Ni betavoltaic battery. Sci China Technol Sci. 2012;55(4):990–6. https://doi.org/10. 1007/s11431-012-4752-6
  20. Li XY, Lu JB, Liu YM, Xu X, He R, Zheng RZ. Exploratory study of betavoltaic battery using ZnO as the energy converting material. Nucl Sci Tech. 2019; 30(4):60. https://doi.org/10.1007/11s41365-019-0577-3
  21. Klein CA. Bandgap dependence and related features of radiation ionization energies in semiconductors. J Appl Phys. 1968;39(4):2029–38. https://doi.org/10. 1063/1.1656484.
  22. Sachenko AV, Shkrebtii AI, Korkishko RM, Kostylyov VP, Kulish MR, Sokolovskyi IO. Efficiency analysis of betavoltaic elements. Solid-State Electron. 2015; 111:147–52. https://doi.org/10. 1016/j.sse.2015.05.042
  23. Belghachi A, Bozkurt K, Ozdemir O, Avci O. Enhancement of Ni-63 planar source efficiency for betavoltaic batteries. J Phys Appl Phys. 2020;53(44): http://dx.doi.org/10.1088/1361-6463/ab9977
  24. Eckerman K, Endo A. ICRP Publication 107. Nuclear decay data for dosimetric calculations. Ann ICRP. 2008; 38(3): 7–96. https://doi.org/10.1016/j.icrp.2008.004
  25. Goldstein JI, Newbury DE, Michael JR, Ritchie NW, Scott JHJ, Joy DC. Scanning electron microscopy and X-ray microanalysis. Springer; 2017. https://doi. org/10.1007/978-1-4939-6676-9
  26. Hussain A, Yang LH, Zou YB, Mao SF, Da B, Li HM, et al. Monte Carlo simulation study of electron yields from compound semiconductor materials. J Appl Phys. 2020;128(1):015305. https://doi.org/10.1063/ 5.0012154
  27. Wu M, Wang S, Ou Y, Wang W. Optimization design of betavoltaic battery based on titanium tritide and silicon using Monte Carlo code. Appl Radiat Isot. 2018; 142:22–7. https://doi.org/ 10.1016/j.apradiso. 2018.09.017
  28. Spencer MG, Alam T. High power direct energy conversion by nuclear batteries. Appl Phys Rev. 2019;6(3):031305. https://doi.org/10.1063/1.5123163
  29. Zhang L, Cheng HL, Hu XC, Xu XB. Model and optimal design of 147Pm SiC-based betavoltaic cell. Superlattices Microstruct. 2018; 123:60–70. https:// doi.org/10.1016/j.spmi.2018.01.007
  30. Rahastama S, Waris A, Viridi S, Iskandar F. Optimization of surface passivation parameters in [147Pm]-Si planar p-n junction betavoltaic based on analytical 1-D minority carrier diffusion equation approaches. Appl Radiat Isot. 2019; 151: 226–34. https://doi.org/10.1016/j.apradiso.2019. 03. 030
  31. Grushko V, Beliuskina O, Mamalis A, Lysakovskiy V, Mitskevich E, Kiriev A, et al. Energy conversion efficiency in betavoltaic cells based on the diamond Schottky diode with a thin drift layer. Appl Radiat Isot. 2020; 157:109017. http://dx.doi.org/10.1016/ j.apradiso.2019.109017
  32. Yunpeng L, Xiao G, Zhangang J, Xiaobin T. Temperature dependence of 63Ni-Si betavoltaic microbattery. Appl Radiat Isot. 2018; 135:47–56. https://doi.org/10.1016/j.apradiso.2018.01.017
  33. Owens A. Semiconductor radiation detectors [Internet]. Boca Raton, Fla.: CRC Press; 2019. Available from: https://www.routledge.com/ Semiconductor-Radiation-Detectors/Owens/p/book/9780367779689. https://doi.org/10.1007/978-3-540-71679-2
  34. Owens A. Compound semiconductor radiation detectors. CRC Press; 2012. 521 p. (Series in sensors). https://doi.org/10.1016/j.nima.2004.05.071
  35. Murphy JW, Voss LF, Frye CD, Shao Q, Kazkaz K, Stoyer MA, et al. Design considerations for three-dimensional betavoltaics. AIP Adv. 2019; 9(6): 065208. https://doi.org/10.1063/1.5097775
  36. Liu YM, Lu JB, Li XY, Xu X, He R, Wang HD. A 4H–SiC betavoltaic battery based on a 63Ni source. Nucl Sci Tech. 2018;29(11):168. https://doi.org/10. 1007/s41365-018-0494-x
  37. Goss JP, Eyre RJ, Briddon PR. Theoretical models for doping diamond for semiconductor applications. Phys Status Solidi B. 2008;245(9):1679–700. h https://doi.org/10.1002/pssb.200744115
  38. Pinault-Thaury MA, Tillocher T, Habka N, Kobor D, Jomard F, Chevallier J, et al. n-Type CVD diamond: Epitaxy and doping. Mater Sci Eng B. 2011;176(17): 1401–8. https://doi.org/10.1016/j.mseb.2011.02.015
  39. Izyumskaya N, Demchenko DO, Das S, Özgür Ü, Avrutin V, Morkoç H. Recent development of boron nitride towards electronic applications. Adv Electron Mater. 2017;3(5):1600485. https://doi.org/10.1002/ aelm.201600485
  40. Tsao JY, Chowdhury S, Hollis MA, Jena D, Johnson NM, Jones KA, et al. Ultrawide-bandgap semiconductors: Research opportunities and challenges. Adv Electron Mater. 2018;4(1):1600501. https://doi. org/10.1002/aelm.201600501
  41. Tsao JY, Chowdhury S, Hollis MA, Jena D, Johnson NM, Jones KA, et al. Ultrawide-bandgap semiconductors: Research opportunities and challenges. Adv Electron Mater. 2018;4(1):1600501. https://doi.org/10.1002/aelm. 201600501

 

 

 

ارتقاء امنیت وب با وف ایرانی