The time response of plasmonic sensors due to binary adsorption: analytical versus numerical modeling
Само за регистроване кориснике
2020
Аутори
Jakšić, OlgaJokić, Ivana
Jakšić, Zoran
Mladenović, Ivana
Radulović, Katarina
Frantlović, Miloš
Чланак у часопису (Објављена верзија)
,
Springer Nature
Метаподаци
Приказ свих података о документуАпстракт
In order to allow for multiscale modeling of complex systems we focus on various approaches to modeling binary adsorption. We consider multiple methods of modeling the temporal response of general plasmonic sensors. We start from the analytical approach. The kinetics of adsorption and desorption is modeled both as a first order reaction and as a second order reaction. The criteria for their validity and the choice between them in the case of two-component adsorption are established. Due to the nonlinearities of the second order reactions and the lack of their analytical solutions, computer aided modeling is considered next, also in multiple ways: the employment of numerical solvers, fitting of experimental results, the stochastic simulation algorithms and the employment of artificial neural networks (ANN). The examples we present illustrate the advantages and disadvantages of the particular approaches. The goal is to aid the concurrent multiscale modeling of adsorption-based devices. ...Machine learning in ANN performed here is used to estimate the equilibrium values of adsorbed quantities. The obtained results show that to train an ANN for the estimation of the equilibrium adsorption quantities the Levenberg-Marquardt and the Bayesian regularization algorithms are less efficient than the quasi-Newton BFGS (Broyden-Fletcher-Goldfarb-Shanno) algorithm.
Кључне речи:
adsorption kinetics / machine learning algorithms / plasmonic sensing / stochastic simulation algorithmsИзвор:
Applied Physics A, 2020, 126, 342-Издавач:
- Springer Nature
Финансирање / пројекти:
- Микро, нано-системи и сензори за примену у електропривреди, процесној индустрији и заштити животне средине (RS-MESTD-Technological Development (TD or TR)-32008)
Напомена:
- The peer-reviewed version: http://cer.ihtm.bg.ac.rs/handle/123456789/3493
DOI: 10.1007/s00339-020-03524-3
ISSN: 0947-8396
WoS: 000526931900003
Scopus: 2-s2.0-85083375372
Институција/група
IHTMTY - JOUR AU - Jakšić, Olga AU - Jokić, Ivana AU - Jakšić, Zoran AU - Mladenović, Ivana AU - Radulović, Katarina AU - Frantlović, Miloš PY - 2020 UR - https://cer.ihtm.bg.ac.rs/handle/123456789/3494 AB - In order to allow for multiscale modeling of complex systems we focus on various approaches to modeling binary adsorption. We consider multiple methods of modeling the temporal response of general plasmonic sensors. We start from the analytical approach. The kinetics of adsorption and desorption is modeled both as a first order reaction and as a second order reaction. The criteria for their validity and the choice between them in the case of two-component adsorption are established. Due to the nonlinearities of the second order reactions and the lack of their analytical solutions, computer aided modeling is considered next, also in multiple ways: the employment of numerical solvers, fitting of experimental results, the stochastic simulation algorithms and the employment of artificial neural networks (ANN). The examples we present illustrate the advantages and disadvantages of the particular approaches. The goal is to aid the concurrent multiscale modeling of adsorption-based devices. Machine learning in ANN performed here is used to estimate the equilibrium values of adsorbed quantities. The obtained results show that to train an ANN for the estimation of the equilibrium adsorption quantities the Levenberg-Marquardt and the Bayesian regularization algorithms are less efficient than the quasi-Newton BFGS (Broyden-Fletcher-Goldfarb-Shanno) algorithm. PB - Springer Nature T2 - Applied Physics A T1 - The time response of plasmonic sensors due to binary adsorption: analytical versus numerical modeling VL - 126 SP - 342 DO - 10.1007/s00339-020-03524-3 ER -
@article{ author = "Jakšić, Olga and Jokić, Ivana and Jakšić, Zoran and Mladenović, Ivana and Radulović, Katarina and Frantlović, Miloš", year = "2020", abstract = "In order to allow for multiscale modeling of complex systems we focus on various approaches to modeling binary adsorption. We consider multiple methods of modeling the temporal response of general plasmonic sensors. We start from the analytical approach. The kinetics of adsorption and desorption is modeled both as a first order reaction and as a second order reaction. The criteria for their validity and the choice between them in the case of two-component adsorption are established. Due to the nonlinearities of the second order reactions and the lack of their analytical solutions, computer aided modeling is considered next, also in multiple ways: the employment of numerical solvers, fitting of experimental results, the stochastic simulation algorithms and the employment of artificial neural networks (ANN). The examples we present illustrate the advantages and disadvantages of the particular approaches. The goal is to aid the concurrent multiscale modeling of adsorption-based devices. Machine learning in ANN performed here is used to estimate the equilibrium values of adsorbed quantities. The obtained results show that to train an ANN for the estimation of the equilibrium adsorption quantities the Levenberg-Marquardt and the Bayesian regularization algorithms are less efficient than the quasi-Newton BFGS (Broyden-Fletcher-Goldfarb-Shanno) algorithm.", publisher = "Springer Nature", journal = "Applied Physics A", title = "The time response of plasmonic sensors due to binary adsorption: analytical versus numerical modeling", volume = "126", pages = "342", doi = "10.1007/s00339-020-03524-3" }
Jakšić, O., Jokić, I., Jakšić, Z., Mladenović, I., Radulović, K.,& Frantlović, M.. (2020). The time response of plasmonic sensors due to binary adsorption: analytical versus numerical modeling. in Applied Physics A Springer Nature., 126, 342. https://doi.org/10.1007/s00339-020-03524-3
Jakšić O, Jokić I, Jakšić Z, Mladenović I, Radulović K, Frantlović M. The time response of plasmonic sensors due to binary adsorption: analytical versus numerical modeling. in Applied Physics A. 2020;126:342. doi:10.1007/s00339-020-03524-3 .
Jakšić, Olga, Jokić, Ivana, Jakšić, Zoran, Mladenović, Ivana, Radulović, Katarina, Frantlović, Miloš, "The time response of plasmonic sensors due to binary adsorption: analytical versus numerical modeling" in Applied Physics A, 126 (2020):342, https://doi.org/10.1007/s00339-020-03524-3 . .