Predictive Modeling of Breast Anticancer Activity of a Series of Coumarin Derivatives using Quantum Descriptors

The performance of an organic solar cell is strongly influenced by the structure of the photosensitizer. In this work, the open-circuit voltage (VOC) and conversion efficiency (η) of a series of coumarin dyes are quantitatively related to the structure of nine coumarin derivatives. The Quantitative Structure Property Relationship (QSPR) is performed using the statistical method of multiple linear regression. In addition, descriptors determined from the ground state at the Cam_B3lyp/6-31G(d, p) level of theory and from the 2D structure of the molecules are mathematically related to the photovoltaic properties. These VOC and η models are accredited with very good statistical indicators (R2 = 0.906 and 0.918; Qcv2= 0.845 and 0.849; S= 0.045 and 0.112; F = 14.524 and 16.846). These statistical indicators confirm the robustness and performance of the models developed. The results show that Voc improves with decreasing surface tension (ts) and increasing number of cycles (cycle). As for the conversion efficiency of light radiation into electrical energy, it is optimal when the light harvesting efficiency (LHEth) and the excited state lifetime (τth) are high. In conclusion, these models have good predictive capabilities and can be used to predict and explain the open-circuit voltage and efficiency of coumarin derivatives that belong to the same field of application.

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Predictive Modeling of Breast Anticancer Activity of a Series of Coumarin Derivatives using Quantum Descriptors

Cited by 3 publications

References 21 publications

Dipole moment in medicinal research: Green and sustainable approach

Dipole moment in medicinal research: Green and sustainable approach

Dipole moment in medicinal research: green and sustainable approach

Quantitative Structure Photovoltaic Properties Relationship of Coumarin Dyes Derived

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