Publications by authors named "Yudhajit Pal"
Article Synopsis
- A deep learning method is developed to predict the emission spectra of phosphorescent Ir(III) complexes, aiding the discovery of novel chromophores for applications like organic light-emitting diodes and solar fuel cells.
- The models use graph neural networks to account for the structural features of the complexes, leading to efficient training and accurate predictions of emission spectra, even with low-quality experimental data.
- This approach not only enhances the accuracy over traditional methods but also facilitates exploring a vast chemical space with limited experimental data, minimizing the need for extensive high-throughput screening efforts.
Diol radicals (DRs) are important intermediates in biocatalysis, atmospheric chemistry, and biomass combustion. They are particularly generated from photolysis of halogenated diols and addition of hydroxyl radical to a double bond of unsaturated alcohols, such as lignols. The energized DRs further isomerize/decompose to form products, including water.
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