Sim-SPR: an Open-Source Surface Plasmon Resonance Simulator for Academic and Industrial Purposes
Source abstract
Abstract
In this paper, an open-source simulation tool is proposed to evaluate the SPR effect considering a multilayer structure. The open-source simulator is called Sim-SPR and it follows the principles of software engineering. Furthermore, Sim-SPR is dedicated to analyze reflectance of prism-based SPR sensors using Otto’s configuration. It is important to emphasize that there is no available open-source simulation tool specifically built in this context in the literature. The Sim-SPR accuracy, efficiency, and reliability were analyzed by comparing our obtained results considering three different scenarios with two other simulation tools available in the literature, presenting minimal relative error. The results still include a sensitivity analysis of prism-based SPR sensors focusing on resonant angle.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Plasmonic and Surface Plasmon Research · Photonic and Optical Devices · Optical Coatings and Gratings
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (31)
Show source-provided references
1. Comsol multiphysics – RF module. https://br.comsol.com/rf-module . Accessed on December 1st, 2018
2. Lumerical’s system simulation. https://www.lumerical.com/ . Accessed on December 1st, 2018
3. Sentaurus device. https://www.synopsys.com/silicon/tcad/device-simulation/sentaurus-device.html . Accessed on December 1st, 2018
4. Software winspall. http://www.res-tec.de/index.html . Accessed on December 1st, 2018
5. Abelès F (1950) La thèorie gènèrale des couches minces. J Phys Radium 11(7):307–309. https://doi.org/10.1051/jphysrad:0195000110703070010.1051/jphysrad:01950001107030700 ↗
6. Akowuah EK, Gorman T, Haxha S (2009) Design and optimization of a novel surface plasmon resonance biosensor based on otto configuration. Opt Express 17(26):23511–23521. https://doi.org/10.1364/OE.17.02351110.1364/OE.17.023511 ↗
7. Banerjee J, Bera M, Ray M (2017) Theoretical differential phase analysis for characterization of aqueous solution using surface plasmon resonance. Plasmonics 12(6):1787–179610.1007/s11468-016-0446-4 ↗
8. Fontana E (2006) Thickness optimization of metal films for the development of surface-plasmon-based sensors for nonabsorbing media. Appl Opt 45(29):7632–7642. https://doi.org/10.1364/AO.45.00763210.1364/AO.45.007632 ↗
9. Fontana E, Kim J, Llamas-Garro I, Cavalcanti GO (2015) Microfabricated otto chip device for surface plasmon resonance-based optical sensing. Appl Opt 54(31):9200–920410.1364/AO.54.009200 ↗
10. Hernández DM, Velázquez-González JS, Luna-Moreno D, Torres-Cisneros M, Hernández-Romano I (2018) Prism-based surface plasmon resonance for dual-parameter sensing. IEEE Sensors J 18(10):4030–4037. https://doi.org/10.1109/JSEN.2018.281806410.1109/JSEN.2018.2818064 ↗
11. Homola J, Koudela I, Yee SS (1999) Surface plasmon resonance sensors based on diffraction gratings and prism couplers: sensitivity comparison. Sensors Actuators B Chem 54(1-2):16–2410.1016/S0925-4005(98)00322-0 ↗
12. Homola J, Yee SS, Gauglitz G (1999) Surface plasmon resonance sensors: review. Sensors Actuators B Chem 54(1-2):3–1510.1016/S0925-4005(98)00321-9 ↗
13. Hughes A, Liu Z, Reeves ME (2015) Pame: plasmonic assay modeling environment. PeerJ Computer Science 1:e17. https://doi.org/10.7717/peerj-cs.1710.7717/peerj-cs.17 ↗
14. Jamil NA, Menon PS, Shaari S, Mohamed MA, Majlis BY (2018) Taguchi optimization of surface plasmon resonance-kretschmann biosensor using fdtd. In: IEEE International Conference on Semiconductor Electronics (ICSE), pp 65–68. https://doi.org/10.1109/SMELEC.2018.848121610.1109/SMELEC.2018.8481216 ↗
15. Jiang W, Dunham ST (2011) 3d optical and device simulation of surface plasmonic effects on organic solar cells using silver nano prisms. In: IEEE Photovoltaic Specialists Conference, pp 889–893. https://doi.org/10.1109/PVSC.2011.618609510.1109/PVSC.2011.6186095 ↗
16. Kaneoka Y, Nishigaki K, Mizutani Y, Iwata T (2015) Precise measurement of the thickness of a dielectric layer on a metal surface by use of a modified otto optical configuration. Int J Optomechatronics 9(1):48–61. https://doi.org/10.1080/15599612.2014.98838610.1080/15599612.2014.988386 ↗
17. Kanso M, Cuenot S, Louarn G (2008) Sensitivity of optical fiber sensor based on surface plasmon resonance: modeling and experiments. Plasmonics 3(2-3):49–57. https://doi.org/10.1007/s11468-008-9055-110.1007/s11468-008-9055-1 ↗
18. Kretschmann E, Raether H (1968) Notizen: Radiative decay of non radiative surface plasmons excited by light. Zeitschrift für Naturforschung A 23:2135–2136. https://doi.org/10.1515/zna-1968-124710.1515/zna-1968-1247 ↗
19. Lee Y, Sim S, dos Santos MRN, Fernandes GDF, Cavalcanti GO, Llamas-Garro I, Fontana E, Kim J (2018) Reflectance analysis of the otto chip using an automated reflectometer. In: 2018 International Conference on Optical MEMS and Nanophotonics (OMN), pp 1–2. https://doi.org/10.1109/OMN.2018.845456910.1109/OMN.2018.8454569 ↗
20. Ma K, Liu L, Zhang P, He Y, Peng Q (2019) Optimization of angle-pixel resolution for angular plasmonic biosensors. Sensors Actuators B Chem 283:188–197. https://doi.org/10.1016/j.snb.2018.12.02310.1016/j.snb.2018.12.023 ↗
21. Maier SA (2007) Plasmonics: Fundamentals and Applications. Springer Science & Business Media, Berlin10.1007/0-387-37825-1 ↗
22. Meshginqalam B, Barvestani J (2018) Aluminum and phosphorene based ultrasensitive spr biosensor. Opt Mater 86:119–125. https://doi.org/10.1016/j.optmat.2018.10.00310.1016/j.optmat.2018.10.003 ↗
23. Oliveira LC, Herbster A, da Silva Moreira C, Neff FH, Lima AMN (2017) Surface plasmon resonance sensing characteristics of thin aluminum films in aqueous solution. IEEE Sensors J 17(19):6258–6267. https://doi.org/10.1109/JSEN.2017.274158310.1109/JSEN.2017.2741583 ↗
24. Otto A (1968) Excitation of nonradiative surface plasma waves in silver by the method of frustrated total reflection. Zeitschrift für Physik A Hadrons and nuclei 216(4):398–410. https://doi.org/10.1007/BF0139153210.1007/BF01391532 ↗
25. Polyanskiy MN Refractive index database. https://refractiveindex.info . Accessed on December 1st, 2018
26. Rahman MS, Anower MS, Hasan MR, Hossain MB, Haque MI (2017) Design and numerical analysis of highly sensitive au-mos2-graphene based hybrid surface plasmon resonance biosensor. Opt Commun 396:36–43. https://doi.org/10.1016/j.optcom.2017.03.03510.1016/j.optcom.2017.03.035 ↗
27. Sarid D, Challener W (2010) Modern introduction to surface plasmons: theory, mathematica modeling, and applications. Modern Introduction to Surface Plasmons: Theory, Mathematica Modeling, and Applications pp 1–371. https://doi.org/10.1017/CBO978113919484610.1017/CBO9781139194846 ↗
28. Tran NHT, Phan BT, Yoon WJ, Khym S, Ju H (2017) Dielectric metal-based multilayers for surface plasmon resonance with enhanced quality factor of the plasmonic waves. J Elec Materi 46(6):3654–365910.1007/s11664-017-5375-2 ↗
29. Vahed H, Nadri C (2019) Sensitivity enhancement of spr optical biosensor based on graphene–mos2 structure with nanocomposite layer. Opt Mater 88:161–166. https://doi.org/10.1016/j.optmat.2018.11.03410.1016/j.optmat.2018.11.034 ↗
30. Yan H, Lai-xu G, Song-quan L, Wen-ling S, Hong-an Y (2011) Research on surface plasmon resonance sensor based on wavelength modulation by using theoretical simulation. In: International Conference on Measuring Technology and Mechatronics Automation, vol 3. pp 83–86. https://doi.org/10.1109/ICMTMA.2011.59210.1109/ICMTMA.2011.592 ↗
31. Zhang J, Zhang L, Xu W (2012) Surface plasmon polaritons: Physics and applications. Journal of Physics D-applied Physics - J PHYS-D-APPL PHYS 45. https://doi.org/10.1088/0022-3727/45/11/11300110.1088/0022-3727/45/11/113001 ↗