Photoacoustic Measurements of the Thermal and Elastic Properties of n-Type Silicon Using Neural Networks
Само за регистроване кориснике
2020
Чланак у часопису (Објављена верзија)
,
© 2019, Springer Nature B.V.
Метаподаци
Приказ свих података о документуАпстракт
In this paper, a simple multilayer perceptron neural network with forward signal propagation was designed and used to simultaneously determine the main physical parameters, such as: the thermal diffusivity, thermal expansion coefficient and thickness, from the transmission, frequency-modulated photoacoustic response of the sample. The amplitude and phase responses of the transmission open-cell photoacoustic signals were calculated in n-type silicon plates using a theoretical model and were used to train and test a neural network. The simulation was done in the modulation frequency range from 20 Hz to 20 kHz and using a wide range of expected values of thermal diffusivity and the thermal coefficient of expansion for semiconductor samples as well as their thickness. The advantages and disadvantages of neural networks utilization as an appropriate mathematical tool designated for semiconductor measurement-oriented purposes are analyzed. Network reliability, precision, and the possibility ...of operation in real time have been verified on an independent set of signals, establishing photoacoustics as a competitive and powerful technique assigned for material characterization. © 2019, Springer Nature B.V.
Кључне речи:
Photoacoustic / Semiconductors / Thermal diffusion / Thermal expansion / Artificial neural networksИзвор:
Silicon, 2020, 12, 6, 1289-1300Финансирање / пројекти:
- Атомски сударни процеси и фотоакустичка спектрометрија молекула и чврстих тела (RS-MESTD-Basic Research (BR or ON)-171016)
- Функционални, функционализовани и усавршени нано материјали (RS-MESTD-Integrated and Interdisciplinary Research (IIR or III)-45005)
Напомена:
- This article has been corrected. Link to the corrected article: https://vinar.vin.bg.ac.rs/handle/123456789/9667
Повезане информације:
- Повезани садржај
https://vinar.vin.bg.ac.rs/handle/123456789/9667
DOI: 10.1007/s12633-019-00213-6
ISSN: 1876-990X
WoS: 000541079400003
Scopus: 2-s2.0-85071093712
Колекције
Институција/група
VinčaTY - JOUR AU - Đorđević, Katarina Lj. AU - Markushev, Dragan D. AU - Ćojbašić, Žarko М. PY - 2020 UR - https://vinar.vin.bg.ac.rs/handle/123456789/8759 AB - In this paper, a simple multilayer perceptron neural network with forward signal propagation was designed and used to simultaneously determine the main physical parameters, such as: the thermal diffusivity, thermal expansion coefficient and thickness, from the transmission, frequency-modulated photoacoustic response of the sample. The amplitude and phase responses of the transmission open-cell photoacoustic signals were calculated in n-type silicon plates using a theoretical model and were used to train and test a neural network. The simulation was done in the modulation frequency range from 20 Hz to 20 kHz and using a wide range of expected values of thermal diffusivity and the thermal coefficient of expansion for semiconductor samples as well as their thickness. The advantages and disadvantages of neural networks utilization as an appropriate mathematical tool designated for semiconductor measurement-oriented purposes are analyzed. Network reliability, precision, and the possibility of operation in real time have been verified on an independent set of signals, establishing photoacoustics as a competitive and powerful technique assigned for material characterization. © 2019, Springer Nature B.V. T2 - Silicon T1 - Photoacoustic Measurements of the Thermal and Elastic Properties of n-Type Silicon Using Neural Networks VL - 12 IS - 6 SP - 1289 EP - 1300 DO - 10.1007/s12633-019-00213-6 ER -
@article{ author = "Đorđević, Katarina Lj. and Markushev, Dragan D. and Ćojbašić, Žarko М.", year = "2020", abstract = "In this paper, a simple multilayer perceptron neural network with forward signal propagation was designed and used to simultaneously determine the main physical parameters, such as: the thermal diffusivity, thermal expansion coefficient and thickness, from the transmission, frequency-modulated photoacoustic response of the sample. The amplitude and phase responses of the transmission open-cell photoacoustic signals were calculated in n-type silicon plates using a theoretical model and were used to train and test a neural network. The simulation was done in the modulation frequency range from 20 Hz to 20 kHz and using a wide range of expected values of thermal diffusivity and the thermal coefficient of expansion for semiconductor samples as well as their thickness. The advantages and disadvantages of neural networks utilization as an appropriate mathematical tool designated for semiconductor measurement-oriented purposes are analyzed. Network reliability, precision, and the possibility of operation in real time have been verified on an independent set of signals, establishing photoacoustics as a competitive and powerful technique assigned for material characterization. © 2019, Springer Nature B.V.", journal = "Silicon", title = "Photoacoustic Measurements of the Thermal and Elastic Properties of n-Type Silicon Using Neural Networks", volume = "12", number = "6", pages = "1289-1300", doi = "10.1007/s12633-019-00213-6" }
Đorđević, K. Lj., Markushev, D. D.,& Ćojbašić, Ž. М.. (2020). Photoacoustic Measurements of the Thermal and Elastic Properties of n-Type Silicon Using Neural Networks. in Silicon, 12(6), 1289-1300. https://doi.org/10.1007/s12633-019-00213-6
Đorđević KL, Markushev DD, Ćojbašić ŽМ. Photoacoustic Measurements of the Thermal and Elastic Properties of n-Type Silicon Using Neural Networks. in Silicon. 2020;12(6):1289-1300. doi:10.1007/s12633-019-00213-6 .
Đorđević, Katarina Lj., Markushev, Dragan D., Ćojbašić, Žarko М., "Photoacoustic Measurements of the Thermal and Elastic Properties of n-Type Silicon Using Neural Networks" in Silicon, 12, no. 6 (2020):1289-1300, https://doi.org/10.1007/s12633-019-00213-6 . .