Details

Autor(en) / Beteiligte

• Djordjevic, К. Lj
• Galovic, S. P.
• Jordovic-Pavlovic, M. I.
• Nesic, M. V.
• Popovic, M. N.
• Cojbasic, Z. M.
• Markushev, D. D.

Titel

Photoacoustic optical semiconductor characterization based on machine learning and reverse-back procedure

Ist Teil von

• Optical and quantum electronics, 2020-05, Vol.52 (5), Article 247

Ort / Verlag

New York: Springer US

Erscheinungsjahr

2020

Quelle

SpringerLink Journals - AutoHoldings

Beschreibungen/Notizen

• This paper introduces the possibility of the determination of optical absorption and reflexivity coefficient of silicon samples using neural networks and reverse-back procedure based on the photoacoustics response in the frequency domain. Differences between neural network predictions and parameters obtained with standard photoacoustic signal correction procedures are used to adjust our experimental set-up due to the instability of the optical excitation source and the state (contamination) of the illuminated surface. It has been shown that the changes of the optical absorption values correspond to the light source wavelength fluctuations, while changes in the reflexivity coefficient, obtained in this way, correspond to the small effect of the ultrathin layer formation of SiO 2 due to the natural process of surface oxidation.