Sum Decomposition Method for Gaussian Functions Comprising an Experimental Photoluminescence Spectrum

Коваленко, А. В.; Вовк, С. М.; Plakhtii, Ye. G.

doi:10.1007/s10812-021-01182-8

Cited by 7 publications

(5 citation statements)

References 18 publications

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“…The method of decomposition of the sum of Gaussian functions has been tested on the example of solving the problem of identifying the parameters of individual bands in the photoluminescence spectrum. The parameters of individual bands are close to those obtained by the Alentsev-Fock and derivative spectroscopy methods [22].…”

Section: Methodssupporting

confidence: 79%

Determination of Main Spectral and Luminescent Characteristics of Winter Wheat Seeds Infected with Pathogenic Microflora

et al. 2021

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In connection with the constant growth of demand for high-quality food products, there is a need to develop effective methods for storing agricultural products, and the registration and predicting infection in the early stages. The studying of the physical properties of infected plants and seeds has fundamental importance for determining crop losses, conducting a survey of diseases, and assessing the effectiveness of their control (assessment of the resistance of crops and varieties, the effect of fungicides, etc.). Presently, photoluminescent methods for diagnosing seeds in the ultraviolet and visible ranges have not been studied. For research, seeds of winter wheat were selected, and were infected with one of the most common and dangerous diseases for plants—fusarium. The research of luminescence was carried out based on a hardware–software complex consisting of a multifunctional spectrofluorometer “Fluorat-02-Panorama”, a computer with software “Panorama Pro” installed, and an external camera for the samples under study. Spectra were obtained with a diagnostic range of winter wheat seeds of 220–400 nm. Based on the results obtained for winter wheat seeds, it is possible to further develop a method for determining the degree of fusarium infection.

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Section: Methodssupporting

confidence: 79%

Determination of Main Spectral and Luminescent Characteristics of Winter Wheat Seeds Infected with Pathogenic Microflora

et al. 2021

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“…Since the fitting of PL decays with exponential functions resulted in a higher accuracy of temperature sensing, with accuracies of up to 0.70 K, this approach was also tested for steady-state PL spectra. PL spectra can be decomposed into Gaussian peaks representing the individual bands, using an expression f ( λ ) = A exp ( − false( λ − m false) 2 2 σ 2 ) , with three parameters, the amplitude A , the position of the emission maximum m, and the standard deviation σ which relates to fwhm as FWHM = 2 2 ln false( 2 false) σ . Optical spectra g (λ) can be fitted as g (λ) = f 1 (λ) + f 2 (λ) + ... + f n (λ).…”

Section: Resultsmentioning

confidence: 99%

“…, with three parameters, the amplitude A, the position of the emission maximum m, and the standard deviation σ which relates to f whm as = FWHM 2 2ln(2) . 55 Optical spectra g(λ) can be fitted as g(λ) = f 1 (λ) + f 2 (λ) + ... + f n (λ). In Figure 5a, a twocomponent Gauss fit for p-CDs at 30 °C is shown.…”

Section: ■ Results and Discussionmentioning

confidence: 99%

Improving the Accuracy of Carbon Dot Temperature Sensing Using Multi-Dimensional Machine Learning

Döring,

Qiu,

Rogach

2024

ACS Appl. Nano Mater.

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Optical sensing methods offer a convenient noncontact approach to monitor different environmental parameters with a high spatial resolution and fast response times. Temperature monitoring can benefit from optical sensing using luminescent nanoprobes, but many of those substances are toxic or expensive. Carbon dots are a class of luminescent colloidal nanoparticles that have recently gained recognition as optical probes, which are easy to produce by environmentally friendly synthesis, nontoxic, and stable. While carbon dots show temperature-dependent optical properties, their broad emission profiles may constitute a challenge for optical sensing. In this study, three types of carbon dots with different emission profiles were tested as optical probes for intensity-, spectral-shift-, intensity-ratio-, bandwidth-, and lifetime-based temperature sensing. Depending on the optical characteristics of the specific probe, either intensity-or lifetime-based sensing was shown to be the most accurate, with accuracies of up to 1.65 and 0.70 K, respectively. Employing Gaussian fits improved accuracies of the intensity-ratio-based sensing to 1.24 K, with the additional benefit of greater stability against excitation fluctuations. Finally, a multiple linear regression model combining steady-state and time-resolved luminescence data of carbon dots has been applied to further increase the sensing accuracies with carbon dots to 0.54 K. Our study demonstrates how multidimensional machine learning methods can greatly improve temperature sensing with optical probes.

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“…To date, more than a thousand papers have been published in which the term "derivative spectroscopy" is mentioned in the title. The theory and practice of derivative spectroscopy are covered in detail in many books [2][3][4], reviews [5][6][7][8][9][10][11], and studies [7,[12][13][14][15][16][17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

“…It is clear that even semi-classical calculations are time consuming, and it can be difficult to use them directly with spectrometric instruments. One of the possible simplifications is to apply an approach when the optical spectra of dye molecules are approximated by a set of bell-shaped Gaussian curves [12,14,23,[36][37][38]. It must be stressed that from the point of view of quantum theory, such presentation can be considered as a rough approximation.…”

Section: Introductionmentioning

confidence: 99%

Gaussian Decomposition vs. Semiclassical Quantum Simulation: Obtaining the High-Order Derivatives of a Spectrum in the Case of Photosynthetic Pigment Optical Properties Studying

Razjivin,

Kozlovsky,

Ashikhmin

et al. 2023

Sensors

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In this paper, a procedure for obtaining undistorted high derivatives (up to the eighth order) of the optical absorption spectra of biomolecule pigments has been developed. To assess the effectiveness of the procedure, the theoretical spectra of bacteriochlorophyll a, chlorophyll a, spheroidene, and spheroidenone were simulated by fitting the experimental spectra using the differential evolution algorithm. The experimental spectra were also approximated using sets of Gaussians to calculate the model absorption spectra. Theoretical and model spectra can be differentiated without smoothing (high-frequency noise filtering) to obtain high derivatives. Superimposition of the noise track on the model spectra allows us to obtain test spectra similar to the experimental ones. Comparison of the high derivatives of the model spectra with those of the test spectra allows us to find the optimal parameters of the filter, the application of which leads to minimal differences between the high derivatives of the model and test spectra. For all four studied pigments, it was shown that smoothing the experimental spectra with optimal filters makes it possible to obtain the eighth derivatives of the experimental spectra, which were close to the eighth derivatives of their theoretical spectra.

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Sum Decomposition Method for Gaussian Functions Comprising an Experimental Photoluminescence Spectrum

Cited by 7 publications

References 18 publications

Determination of Main Spectral and Luminescent Characteristics of Winter Wheat Seeds Infected with Pathogenic Microflora

Determination of Main Spectral and Luminescent Characteristics of Winter Wheat Seeds Infected with Pathogenic Microflora

Improving the Accuracy of Carbon Dot Temperature Sensing Using Multi-Dimensional Machine Learning

Gaussian Decomposition vs. Semiclassical Quantum Simulation: Obtaining the High-Order Derivatives of a Spectrum in the Case of Photosynthetic Pigment Optical Properties Studying

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