Aftab Farrukh , Ibrahim A. Shaaban , Mohammed A. Assiri , Mudassir Hussain Tahir , Zeinhom M. El-Bahy
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引用次数: 0
Abstract
In this study, UV/visible absorption maxima of organic compounds are predicted with the help of machine learning (ML). Four ML models are evaluated, the gradient boosting model has performed best. We also analyzed feature importance. Using Python-based tools, we generated and visualized a new set of 5,000 organic compounds. These compounds were screened based on their predicted UV/visible absorption maxima, selecting those with red-shifted absorption. The assessment of synthetic accessibility indicated that most of the chosen compounds are relatively easy to synthesize.
期刊介绍：
Spectrochimica Acta, Part A: Molecular and Biomolecular Spectroscopy (SAA) is an interdisciplinary journal which spans from basic to applied aspects of optical spectroscopy in chemistry, medicine, biology, and materials science.
The journal publishes original scientific papers that feature high-quality spectroscopic data and analysis. From the broad range of optical spectroscopies, the emphasis is on electronic, vibrational or rotational spectra of molecules, rather than on spectroscopy based on magnetic moments.
Criteria for publication in SAA are novelty, uniqueness, and outstanding quality. Routine applications of spectroscopic techniques and computational methods are not appropriate.
Topics of particular interest of Spectrochimica Acta Part A include, but are not limited to:
Spectroscopy and dynamics of bioanalytical, biomedical, environmental, and atmospheric sciences,
Novel experimental techniques or instrumentation for molecular spectroscopy,
Novel theoretical and computational methods,
Novel applications in photochemistry and photobiology,
Novel interpretational approaches as well as advances in data analysis based on electronic or vibrational spectroscopy.
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