Manipulation and optimization of electron transport by nanopore array targets

Yue YANG (杨月); Boyuan LI (李博原); Yuchi WU (吴玉迟); Bin ZHU (朱斌); Bo ZHANG (张博); Zhimeng ZHANG (张智猛); Minghai YU (于明海); Feng LU (卢峰); Kainan ZHOU (周凯南); Lianqiang SHAN (单连强); Lihua CAO (曹莉华); Zongqing ZHAO (赵宗清); Weimin ZHOU (周维民); Yuqiu GU (谷渝秋)

doi:10.1088/2058-6272/abbd37

Plasma Science and Technology > 2021 > 23(1): 15001-015001. > DOI: 10.1088/2058-6272/abbd37

Yue YANG (杨月), Boyuan LI (李博原), Yuchi WU (吴玉迟), Bin ZHU (朱斌), Bo ZHANG (张博), Zhimeng ZHANG (张智猛), Minghai YU (于明海), Feng LU (卢峰), Kainan ZHOU (周凯南), Lianqiang SHAN (单连强), Lihua CAO (曹莉华), Zongqing ZHAO (赵宗清), Weimin ZHOU (周维民), Yuqiu GU (谷渝秋). Manipulation and optimization of electron transport by nanopore array targets[J]. Plasma Science and Technology, 2021, 23(1): 15001-015001. DOI: 10.1088/2058-6272/abbd37

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Manipulation and optimization of electron transport by nanopore array targets

¹ Laser Fusion Research Center, China Academy of Engineering Physics, Mianyang 621900, People's Republic of China
² Key Laboratory for Laser Plasmas (Ministry of Education), School of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai 200240, People's Republic of China
³ Institute of Applied Physics and Computational Mathematics, Beijing 100088, People's Republic of China
⁴ Key Laboratory of HEDP of the Ministry of Education & CAPT, Peking University, Beijing 100871, People's Republic of China

Funds: This work was supported by the National Key R&D Program of China (Grant No. 2016YFA0401100), the Science and Technology on Plasma Physics Laboratory (Grant Nos. 6142A04180201 and JCKYS2020212006), National Natural Science Foundation of China (Grant No. 11975214) and the Science Challenge Program (Grant Nos. TZ2016005 and TZ2018005).

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Received Date: July 14, 2020
Revised Date: September 28, 2020
Accepted Date: September 29, 2020

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Abstract

Abstract

The transport of sub-picosecond laser-driven fast electrons in nanopore array targets is studied. Attributed to the generation of micro-structured magnetic fields, most fast electron beams are proven to be effectively guided and restricted during the propagation. Different transport patterns of fast electrons in the targets are observed in experiments and reproduced by particle-in-cell simulations, representing two components: initially collimated low-energy electrons in the center and high-energy scattering electrons turning into surrounding annular beams. The critical energy for confined electrons is deduced theoretically. The electron guidance and confinement by the nano-structured targets offer a technological approach to manipulate and optimize the fast electron transport by properly modulating pulse parameters and target design, showing great potential in many applications including ion acceleration, microfocus x-ray sources and inertial confinement fusion.
- nanopore array,
- laser-driven electrons,
- fast electron transport,
- electron collimation

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[1]	Chodura R 1982 Phys. Fluid 25 1628
[2]	Riemann K U 1991 J. Phys. D: Appl. Phys. 24 493
[3]	Riemann K U 2009 Plasma Sources Sci. Technol. 18 014006
[4]	Ghim Y C and Hershkowitz N 2009 Appl. Phys. Lett. 94 151503
[5]	Femandez Palop J I et al 1995 J. Appl. Phys. 77 2937
[6]	Femandez Palop J I et al 1996 Surf. Coat. Tech. 84 341
[7]	Wang Z X et al 2003 Chin. Phys. Lett. 20 1537
[8]	Gong Y et al 2010 Chin. J. Comput. Phys. 27 883
[9]	Zhao X Y et al 2011 Acta Phys. Sin. 60 045205 (in Chinese)
[10]	Zou X et al 2004 Chin. Phys. Lett. 21 1572
[11]	Zou X et al 2011 Chin. Phys. Lett. 28 125201
[12]	Liu H P et al 2012 Acta Phys. Sin. 61 035201 (in Chinese)
[13]	Liu H P et al 2016 Acta Phys. Sin. 65 245201 (in Chinese)
[14]	Liu H P and Zou X 2020 Acta Phys. Sin. 69 025201 (in Chinese)
[15]	Tsallis C 1988 J. Stat. Phys. 52 479
[16]	Hatami M M 2015 Phys. Plasmas 22 013508
[17]	Hatami M M 2015 Phys. Plasmas 22 023506
[18]	Hatami M M, Tribeche M and Mamun A A 2018 Phys.Plasmas 25 094502
[19]	Zhao X Y et al 2019 Acta Phys. Sin. 68 185204 (in Chinese)
[20]	Liu Y, Liu S Q and Xu K 2012 Phys. Plasmas 19 073702
[21]	Liu Y, Liu S Q and Zhou L 2013 Phys. Plasmas 20 043702
[22]	Tantawy S A E, Tribeche M and Moslem W M 2012 Phys.Plasmas 19 032104
[23]	Emamuddin M et al 2013 Phys. Plasmas 20 083708
[24]	Navab Safa N, Ghomi H and Niknam A R 2014 Phys. Plasmas 21 082111
[25]	Mehdipoor M and Mohsenpour T 2015 Phys. Plasmas 22 112110
[26]	Borgohain D R, Saharia K and Goswami K S 2016 Phys.Plasmas 23 122113
[27]	Borgohain D R and Saharia K 2018 Phys. Plasmas 25 032122
[28]	Basnet S and Khanal R 2019 Phys. Plasmas 26 043516
[29]	Gyergyek T and Kovačič J 2017 Phys. Plasmas 24 063505
[30]	Gyergyek T and Kovačič J 2017 Phys. Plasmas 24 063506
[31]	Liu J Y et al 2011 Phys. Plasmas 18 013506
[32]	Ou J and Yang J H 2012 Phys. Plasmas 19 113504
[33]	Li J J, Ma J X and Wei Z A 2013 Phys. Plasmas 20 063503
[34]	Wang T T, Ma J X and Wei Z A 2015 Phys. Plasmas 22 093505

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Manipulation and optimization of electron transport by nanopore array targets