Abstract
A focused microbeam system with ion beams at MeV energies is a unique tool for material science, biomedical applications, and space risk evaluation. Microbeam system design traditionally relies on experienced knowledge of microbeam optics and many elaborate calculation procedures. In this work, an ion optics design code, CADAIT, is developed to design microbeam systems automatically. For a given microbeam layout, it allows for the automatic optimization of focusing conditions, the calculation of optical parameters, and the size of the focused beam through ray tracing. CADAIT enables the automatic optical design of microbeam layouts under input parameters and the selection of microbeam layouts with high performance. The accuracy of the CADAIT is verified with ion optics software packages (WinTRAX, Zgoubi, and FANM), which show good agreement. The evaluation of the performance of existing microbeam facilities with CADAIT and the application of CADAIT in the automatic design of a 12 MeV proton microbeam system are discussed. Thanks to its high efficiency in the optical design of microbeam systems, the CADAIT code is used to train artificial intelligence (AI) models for the intelligent design of microbeam systems with tremendous CADAIT-generated data. The artificial intelligence trained model, Artificial Intelligence Microbeam Producer (AIMP), is demonstrated to be capable of generating microbeam systems with superior performance and robust layouts within one minute. The above results show that CADAIT can significantly decrease the complexity and duration of microbeam optical design and prove the feasibility of intelligent microbeam design.
Data Availability Statement
My manuscript has no associated data.
References
M.B.H. Breese, D.N. Jamieson, P.J.C. King, Material analysis using a nuclear microprobe (John Wiley and Sons, New York, 1996)
H. Imaseki, M. Yukawa, F. Watt, The scanning microbeam PIXE analysis facility at NIRS. Nucl. Instrum. Methods B. 210, 42–47 (2003). https://doi.org/10.1016/S0168-583X(03)01002-4
F. Watt, J.A. van Kan, I. Rajta, The National University of Singapore high energy ion nano-probe facility: performance tests. Nucl. Instrum. Methods B. 210, 14–20 (2003). https://doi.org/10.1016/S0168-583X(03)01003-6
C. Udalagama, E.J. Teo, S.F. Chan, Proton beam writing of long, arbitrary structures for micro/nano photonics and fluidics applications. Nucl. Instrum. Methods B. 269, 2417–2421 (2011). https://doi.org/10.1016/j.nimb.2011.02.051
J. Wei, G. Du, J. Guo, The rectification of mono- and bivalent ions in single conical nanopores. Nucl. Instrum. Methods B. 404, 219–223 (2017). https://doi.org/10.1016/j.nimb.2016.12.015
Q. Liu, J. Zhao, J. Guo, Correction to “Sub-5 nm lithography with single GeV heavy ions using inorganic resist.” Nano Lett. 22, 2586–2587 (2022). https://doi.org/10.1021/acs.nanolett.2c00588
B.E. Fischer, K.O. Voss, G. Du, Targeted irradiation of biological cells using an ion microprobe—Why a small beam spot is not sufficient for success. Nucl. Instrum. Methods B. 267, 2122–2124 (2009). https://doi.org/10.1016/j.nimb.2009.03.068
T. Funayama, T. Sakashita, M. Suzuki, An irradiation device for biological targets using focused microbeams of cyclotron-accelerated heavy ion. NucL. Instrum. Methods B. 465, 101–109 (2020). https://doi.org/10.1016/j.nimb.2019.12.028
Y. Tao, H.Q. Tan, Z. Mi, The radiobiology beam line facility at the centre for ion beam applications, national university of Singapore. Nucl. Instrum. Methods B. 456, 26–31 (2019). https://doi.org/10.1016/j.nimb.2019.06.038
F. Watt, X. Chen, C.B. Chen, Whole cell structural imaging at 20 nanometre resolutions using MeV ions. Nucl. Instrum. Methods B. 306, 6–11 (2013). https://doi.org/10.1016/j.nimb.2012.11.047
Z. Mi, C. Chen, H. Tan, Quantifying nanodiamonds biodistribution in whole cells with correlative iono-nanoscopy. Nat. Commun.Commun. 12, 4657 (2021). https://doi.org/10.1038/s41467-021-25004-9
J. Guo, G. Mao, W. Liu, The bitmap decryption model on interleaved SRAM using multiple-bit upset analysis. IEEE Trans. Nucl. Sci.Nucl. Sci. 69, 1857–1864 (2022). https://doi.org/10.1109/TNS.2022.3186083
T. Kamiya, K. Takano, T. Satoh, Microbeam complex at TIARA: technologies to meet a wide range of applications. Nucl. Instrum. Methods B. 269, 2184–2188 (2011). https://doi.org/10.1016/j.nimb.2011.02.043
Y. Yao, J.A. van Kan, Automatic beam focusing in the 2nd generation PBW line at sub-10nm line resolution. Nucl. Instrum. Methods B. 348, 203–208 (2015). https://doi.org/10.1016/j.nimb.2014.12.066
D.N. Jamieson, New generation nuclear microprobe systems. Nucl. Instrum. Methods B. 181, 1–11 (2001). https://doi.org/10.1016/S0168-583X(01)00547-X
R. Szymanski, D.N. Jamieson, Ion source brightness and nuclear microprobe applications. Nucl. Instrum. Methods B. 130, 80–85 (1997). https://doi.org/10.1016/S0168-583X(97)00268-1
X. Xu, R. Pang, P.S. Raman, Fabrication and development of high brightness nano-aperture ion source. Microelectron. Eng.. Eng. 174, 20–23 (2017). https://doi.org/10.1016/j.mee.2016.12.009
N. Liu, P. Santhana Raman, X. Xu, Development of ion sources: Towards high brightness for proton beam writing applications. Nucl. Instrum. Methods B. 348, 23–28 (2015). https://doi.org/10.1016/j.nimb.2015.01.017
C.G. Ryan, D.N. Jamieson, A high performance quadrupole quintuplet lens system for the CSIRO–GEMOC nuclear microprobe. Nucl. Instrum. Methods B. 158, 97–106 (1999). https://doi.org/10.1016/S0168-583X(99)00360-2
P. Barberet, L. Daudin, N. Gordillo, First results obtained using the CENBG nanobeam line: Performances and applications. Nucl. Instrum. Methods B. 269, 2163–2167 (2011). https://doi.org/10.1016/j.nimb.2011.02.036
C.G. Ryan, D.N. Jamieson, W.L. Griffin, The new CSIRO–GEMOC nuclear microprobe: first results, performance and recent applications. Nucl. Instrum. Methods B. 181, 12–19 (2001). https://doi.org/10.1016/S0168-583X(01)00548-1
A. Ponomarov, I. Rajta, G. Nagy, Single-stage quintuplet for upgrading triplet based lens system: simulation for Atomki microprobe. Nucl. Instrum. Methods B. 404, 34–40 (2017). https://doi.org/10.1016/j.nimb.2017.01.057
A.G. Ponomarev, A.A. Ponomarov, Beam optics in nuclear microprobe: a review. Nucl. Instrum. Methods B. 497, 15–23 (2021). https://doi.org/10.1016/j.nimb.2021.03.024
G.W. Grime, F. Watt, Beam optics of quadrupole probe-forming systems (Adam Hilger, Bristol, 1984)
G.W. Grime, WinTRAX: A raytracing software package for the design of multipole focusing systems. Nucl. Instrum. Methods B. 306, 76–80 (2013). https://doi.org/10.1016/j.nimb.2012.11.038
https://www.ph.unimelb.edu.au/~dnj/research/pram/pramdist.htm
G.H. Gillespie, B.W. Hill, Particle optics and accelerator modeling software for industrial and laboratory beamline design. Nucl. Instrum. Methods B. 139, 476–480 (1998). https://doi.org/10.1016/S0168-583X(97)00940-3
F. Méot, The ray-tracing code Zgoubi. Nucl. Instrum. Methods A. 427, 353–356 (1999). https://doi.org/10.1016/S0168-9002(98)01508-3
F. Méot, The ray-tracing code Zgoubi—Status. Nucl. Instrum. Methods A. 767, 112–125 (2014). https://doi.org/10.1016/j.nima.2014.07.022
Y. Dou, J.A. van Kan, FANM: a software for focus and aberrations of nuclear microprobe. Ultramicroscopy 220, 113163 (2021). https://doi.org/10.1016/j.ultramic.2020.113163
R. Storn, K. Price, Differential evolution—a simple and efficient heuristic for global optimization over continuous spaces. J. Global Optim.Optim. 11, 341–359 (1997). https://doi.org/10.1023/A:1008202821328
H. Mou, G. Mao, J. Zhang, Design of 50 MeV proton microbeam based on cyclotron accelerator. Nucl. Sci. Tech.. Sci. Tech. 34, 92 (2023). https://doi.org/10.1007/s41365-023-01235-x
G.W. Grime, F. Watt, G.D. Blower, Real and parasitic aberrations of quadrupole probe-forming systems. Nucl. Instrum. Methods B. 197, 97–109 (1982). https://doi.org/10.1016/0167-5087(82)90123-5
Y. Dou, T. Osipowicz, J.A. van Kan, Breaking the 10 nm barrier using molecular ions in nuclear microprobes. Ultramicroscopy 253, 113812 (2023). https://doi.org/10.1016/j.ultramic.2023.113812
Y. Dou, D.N. Jamieson, J. Liu, A study of GeV proton microprobe lens system designs with normal magnetic quadrupole. Nucl. Instrum. Methods B. 412, 214–220 (2017). https://doi.org/10.1016/j.nimb.2017.09.020
T. Zhao, R. Zhao, M. Eskénazi, Learning discourse-level diversity for neural dialog models using conditional variational autoencoders. Annu. Meet. Assoc. Comput. Linguist. (2017). https://doi.org/10.48550/arXiv.1703.10960
Funding
This work was supported by the National Key R&D Program of China (No. 2021YFA1601400) and the National Natural Science Foundation of China (Nos. 1197283 and U1632271).
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Mou, H., Li, Y., Zhao, C. et al. CADAIT: a code for automatic design and AI training of microbeam systems. Eur. Phys. J. Plus 140, 56 (2025). https://doi.org/10.1140/epjp/s13360-024-05895-5
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DOI: https://doi.org/10.1140/epjp/s13360-024-05895-5