Developing the techniques for solving the inverse problem in photoacoustics.

Фотоакустичке мерне методе се интензивно развијају у последње четири децeније и налазе све разноврснију примену у науци, техници, медицини и стоматологији: од истраживања везе између структуре материје и њених термалних, еластичних, оптичких, електричних и других физичких особина, посебно на ниској временској (испод 0,1 милисекунде) и просторној скали (субмикронској), преко карактеризације наноелектронских направа и фотонских кристала, па све до in vivo дијагностике у медицини...Photoacoustic (PA) measurement methods have been intensively developed in the last four decades and have found versatile application in science, technique, medicine and dentistry: from explorations of the relationship between structure of matter and its thermal, elastic, optical, electrical and other physical properties (especially at low timescale – under 0.1 ms and small space-frame – submicron), through characterization of nanoelectronic devices and photon crystals, all the way to in vivo diagnostics in medicine..

Developing the Techniques for Solving the Inverse Problem in Photoacoustics

In this work, theoretically/mathematically simulated models are derived for the photoacoustic (PA) frequency response of both volume and surface optically-absorbing samples in a minimum volume PA cell. In the derivation process, the thermal memory influence of both the sample and the air of the gas column are accounted for, as well as the influence of the measurement chain. Within the analysis of the TMS model, the influence of optical, thermal, and elastic properties of the sample was investigated. This analysis revealed that some of the processes, characterized by certain sample properties, exert their dominance only in limited modulation frequency ranges, which are shown to be dependent upon the choice of the sample material and its thickness. Based on the described analysis, two methods are developed for TMS model parameter determination, i.e., sample properties which dominantly influence the PA response in the measurement range: a self-consistent procedure for solving the exponential problems of mathematical physics, and a well-trained three-layer perceptron with back propagation, based upon theory of neural networks. The results of the application of both inverse problem solving methods are compared and discussed. The first method is shown to have the advantage in the number of properties which are determined, while the second one is advantageous in gaining high accuracy in the determination of thermal diffusivity, explicitly. Finally, the execution of inverse PA problem is implemented on experimental measurements performed on macromolecule samples, the results are discussed, and the most important conclusions are derived and presented

Photoacoustic Response of Thin Films - Thermal Memory Influence

On the basis of the generalized photoacoustic response model, which includes the influence of thermal memory on both thermoconducting and thermoelastic components, photoacoustic response of thin films is analysed. It is demonstrated that the influence of thermal memory is manifested at frequencies above certain boundary frequency, which depends on thermal memory properties of the sample and its depth. A linear relation, linking heat propagation velocity and measured signal, is derived. Taking into account the confinement of the frequency range imposed by the measuring system, it is indicated that thermal memory properties of non-cristaline thin films can be determined in a photoacoustic experiment

Еvaluation of Thermophysical Properties of Semiconductors by Photoacoustic Phase Neural Network

The idea of this paper is to develop a method for determination thermal diffusivity, linear expansion coefficient and thickness of a semiconductor sample from photoacoustic phase measurement by using neural network. The neural network has been trained on photoacoustic phases obtained from a theoretical model of measured signal for Si n-type in the range of 20Hz to 20kHz. For the analysis of parameter determination from phases, we trained phase neural networks on a large database obtained from numerical experiments in the expected range of parameter changes. An analysis of a theoretical photoacoustic model with a phase neural network is demonstrated. The advantages of using a phase neural network with high accuracy and precision in prediction depending on the number of epochs are presented, as well as analyzes of the application of random Gaussian noise to the network in order to better predict the experimental photoacoustic signal.BPU11 : 11th International Conference of the Balkan Physical Union : Proceedings book; Aug 11 - Sep 1, 2022S07-OP Optics and Photonic

Computationally intelligent characterization of a photoacoustic detector

Artificial neural networks as machine learning techniques have proven to be suitable tools for intelligent decision making. This paper presents the application of artificial neural networks for fast and precise characterization of electret microphones by photoacoustic measurements based on optical generation of sound. The transfer function of this type of devices is usually not determined precisely enough by the producers, especially phase transfer function, because such detectors are not widely applied in scientific experiments but are rather used in audio techniques where amplitude transfer function is more important. The distorted photoacoustic experimental signal, influenced by the measurement set-up in a non-linear manner, represents the input of our model, while the outputs are the detector characteristics. The model consists of two neural networks: the first one for the classification of the detector type and the second one for the determination of the detector parameters, related to its electronic and geometric features. Based on this approach and the theoretical model, relying on the acoustics of small volumes, the parameters and transfer characteristics for several microphones are obtained and compared to the characteristics provided by their producers. It has been shown that the suggested method results in much better detector characterization than the one provided in the official specifications. This could be significant not only for scientific applications of microphones but also for their design and applications in audio techniques.VII International School and Conference on Photonics : PHOTONICA2019 : Abstracts of Tutorial, Keynote, Invited Lectures, Progress Reports and Contributed Papers; August 26-30; Belgrad

Developing the techniques for solving the inverse problem in photoacoustics.

Фотоакустичке мерне методе се интензивно развијају у последње четири децeније и налазе све разноврснију примену у науци, техници, медицини и стоматологији: од истраживања везе између структуре материје и њених термалних, еластичних, оптичких, електричних и других физичких особина, посебно на ниској временској (испод 0,1 милисекунде) и просторној скали (субмикронској), преко карактеризације наноелектронских направа и фотонских кристала, па све до in vivo дијагностике у медицини...Photoacoustic (PA) measurement methods have been intensively developed in the last four decades and have found versatile application in science, technique, medicine and dentistry: from explorations of the relationship between structure of matter and its thermal, elastic, optical, electrical and other physical properties (especially at low timescale – under 0.1 ms and small space-frame – submicron), through characterization of nanoelectronic devices and photon crystals, all the way to in vivo diagnostics in medicine..

Influence of thermal memory on the thermoelastic bending component of photoacoustic response

In this work, thermoelastic component of the photoacoustic response is derived, including thermal memory of the material. The comparison between this model and the classic one, which does not account for the influence of thermal memory is made. It has been noticed that the two models tend to overlap at very high and very low frequencies of the light modulation spectrum, while in the middle range some deviations become more apparent, which proves that thermal memory must be taken into account. It has also been shown that the limits of this range are the function of heat propagation velocity and thickness of the sample. Based upon the processing of obtained data, it has been concluded that the characteristics of the output signal, in the range of the interest, are highly influenced by thermal dynamic qualities, like heat diffusivity and thermal relaxation time, as well as the sample thickness

The influence of multiple optical reflexions on the photoacoustic frequency response

The influence of multiple optical reflexions on optically generated surface temperature variations has scarcely been considered throughout the literature. In this work, a model of optically generated heat sources in the sample with low optical absorption coefficient is derived. Multiple optical reflexions are considered at both surfaces of the sample exposed to the intensity-modulated laser beam. The impacts of the reflexion coefficient, the absorption coefficient and the thickness of the sample on the amplitude characteristics of photothermal responses are discussed

Testing the best matrix/analyte combination for MALDI TOF mass spectrometric detection of steroid hormones, amino acids, vitamins and carbohydrates

41st FEBS Congress on Molecular and Systems Biology for a Better Life, Sep 03-08, 2016, Kusadasi, Turke