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Principal component analysis for Imidazo[4,5-b]pyridine linear and nonlinear optical properties description.

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Title: Principal component analysis for Imidazo[4,5-b]pyridine linear and nonlinear optical properties description.
Authors: Marbello, O.D.1 (AUTHOR), De Boni, L.1 (AUTHOR), Mendonça, C.R.1 (AUTHOR) crmendon@ifsc.usp.br
Source: Optical Materials. Feb2025, Vol. 159, pN.PAG-N.PAG. 1p.
Subjects: Fluorescence yield, Nonlinear optical materials, Principal components analysis, Big data, Dipole moments
Abstract: The two-photon absorption efficiency in materials depends on numerous factors, including the type of material, electronic structure, solvent, thermical and chemical properties, etc. In addition, when analyzing optical systems using nonlinear spectroscopy, a significant amount of data and variables that are not easily interpretable or correlated are involved. Quantum chemical calculations and other methods have been used to describe the nonlinear optical properties of materials. However, such approaches require a high level of understanding of the material's electronic structure, molecular geometry, etc. Yet, the experimental conditions can significantly affect the two-photon absorption cross-section. Some studies use multivariate analysis techniques to simplify the treatment and interpretation of large data sets without a high computational cost. Principal Component Analysis (PCA) is a common method for reducing and exploring large databases. In addition, PCA results can be interpreted as a new dependent variable for regression models. This paper uses the PCA as a multivariate analysis technique to simplify and interpret the two-photon absorption and photophysical properties obtained in the nonlinear characterization of six Imidazo[4,5- b ]Pyridine, as a case of study. Linear regression using principal component scores was used to investigate the dependence of the two-photon absorption cross-section intensity on photophysical parameters (descriptor variables). This was achieved by projecting the values of each variable into the component space and comparing them to the values obtained for the two-photon absorption cross-section. The results revealed that PCA can reproduce the experimental results separating the sample studied based on their electronic structure, with a cumulative variance higher to 80 %. The regression model indicates that the first and second excited state transition dipole moments, permanent dipole moment, and fluorescence quantum yield dominate the behavior of the two-photon absorption cross-section, showing high correspondence with the experimental data. • PCA simplifies interpretation of two-photon absorption (2 PA) data for imidazo[4,5- b ]pyridine derivatives studied. • PCA effectively categorized imidazo[4,5- b ]pyridine derivatives by electronic structure. • PCA modeling explained over 80 % variance in nonlinear optical properties data. • Key optical properties influencing 2 PA cross-section was identified via PCA. • First and second excited state dipole moments strongly influence 2 PA behavior. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:The two-photon absorption efficiency in materials depends on numerous factors, including the type of material, electronic structure, solvent, thermical and chemical properties, etc. In addition, when analyzing optical systems using nonlinear spectroscopy, a significant amount of data and variables that are not easily interpretable or correlated are involved. Quantum chemical calculations and other methods have been used to describe the nonlinear optical properties of materials. However, such approaches require a high level of understanding of the material's electronic structure, molecular geometry, etc. Yet, the experimental conditions can significantly affect the two-photon absorption cross-section. Some studies use multivariate analysis techniques to simplify the treatment and interpretation of large data sets without a high computational cost. Principal Component Analysis (PCA) is a common method for reducing and exploring large databases. In addition, PCA results can be interpreted as a new dependent variable for regression models. This paper uses the PCA as a multivariate analysis technique to simplify and interpret the two-photon absorption and photophysical properties obtained in the nonlinear characterization of six Imidazo[4,5- b ]Pyridine, as a case of study. Linear regression using principal component scores was used to investigate the dependence of the two-photon absorption cross-section intensity on photophysical parameters (descriptor variables). This was achieved by projecting the values of each variable into the component space and comparing them to the values obtained for the two-photon absorption cross-section. The results revealed that PCA can reproduce the experimental results separating the sample studied based on their electronic structure, with a cumulative variance higher to 80 %. The regression model indicates that the first and second excited state transition dipole moments, permanent dipole moment, and fluorescence quantum yield dominate the behavior of the two-photon absorption cross-section, showing high correspondence with the experimental data. • PCA simplifies interpretation of two-photon absorption (2 PA) data for imidazo[4,5- b ]pyridine derivatives studied. • PCA effectively categorized imidazo[4,5- b ]pyridine derivatives by electronic structure. • PCA modeling explained over 80 % variance in nonlinear optical properties data. • Key optical properties influencing 2 PA cross-section was identified via PCA. • First and second excited state dipole moments strongly influence 2 PA behavior. [ABSTRACT FROM AUTHOR]
ISSN:09253467
DOI:10.1016/j.optmat.2024.116620