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Quantitative Fourier transform infrared photoacoustic spectroscopy

M. Choquet, G. Rousset, L. Bertrand

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Abstract

Using a Fourier transform spectrometer equipped with a photoacoustic cell, we have the possibility to combine the multiplex advantages of the first with the capabilities of the second. For example, this permits nondestructive analysis and spectroscopic study of optically opaque samples in the infrared region with a high signal-to-noise ratio. The photoacoustic signal depends strongly on the thermal diffusion length of the sample which, in turn, depends on the frequency modulation of the illuminating beam. In Fourier transform photoacoustic spectroscopy (FTPAS), this frequency dependence induces artificial variations of the relative amplitude bands within the spectrum. A new procedure has been developed to reduce this problem. After correcting for phase errors caused by the optical setup and detection system, the real and imaginary components of the photoacoustic signal are analyzed. Based on the MacDonald and Wetsel model for photoacoustic signal generation, we have therefore performed quantitative spectra of different samples. In this manner, we observe the dichroism of absorption of different serpentine (antigorite and chrysotile) in its raw form. Also, we study the spectrum of a thin film of indium-doped a:Si-H. These spectra demonstrate the advantages of the FTPAS in conjunction with our treatment.

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Using a Fourier transform spectrometer equipped with a photoacoustic cell, we have the possibility to combine the multiplex advantages of the first with the capabilities of the second. For example, this permits nondestructive analysis and spectroscopic study of optically opaque samples in the infrared region with a high signal-to-noise ratio. The photoacoustic signal depends strongly on the thermal diffusion length of the sample which, in turn, depends on the frequency modulation of the illuminating beam. In Fourier transform photoacoustic spectroscopy (FTPAS), this frequency dependence induces artificial variations of the relative amplitude bands within the spectrum. A new procedure has been developed to reduce this problem. After correcting for phase errors caused by the optical setup and detection system, the real and imaginary components of the photoacoustic signal are analyzed. Based on the MacDonald and Wetsel model for photoacoustic signal generation, we have therefore performed quantitative spectra of different samples. In this manner, we observe the dichroism of absorption of different serpentine (antigorite and chrysotile) in its raw form. Also, we study the spectrum of a thin film of indium-doped a:Si-H. These spectra demonstrate the advantages of the FTPAS in conjunction with our treatment.

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Available abstract

Using a Fourier transform spectrometer equipped with a photoacoustic cell, we have the possibility to combine the multiplex advantages of the first with the capabilities of the second. For example, this permits nondestructive analysis and spectroscopic study of optically opaque samples in the infrared region with a high signal-to-noise ratio. The photoacoustic signal depends strongly on the thermal diffusion length of the sample which, in turn, depends on the frequency modulation of the illuminating beam. In Fourier transform photoacoustic spectroscopy (FTPAS), this frequency dependence induces artificial variations of the relative amplitude bands within the spectrum. A new procedure has been developed to reduce this problem. After correcting for phase errors caused by the optical setup and detection system, the real and imaginary components of the photoacoustic signal are analyzed. Based on the MacDonald and Wetsel model for photoacoustic signal generation, we have therefore performed quantitative spectra of different samples. In this manner, we observe the dichroism of absorption of different serpentine (antigorite and chrysotile) in its raw form. Also, we study the spectrum of a thin film of indium-doped a:Si-H. These spectra demonstrate the advantages of the FTPAS in conjunction with our treatment.

Key concepts: Photoacoustic spectroscopy, Materials science, SIGNAL (programming language), Fourier transform, Optics, Fourier transform infrared spectroscopy, Fourier transform spectroscopy, Photoacoustic effect

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