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• W4386833319 abstract "Refractive index (RI) of polymers plays a crucial role in the design of optoelectronic devices, including displays and image sensors. We have developed a framework for (1) high-throughput computation of RI values for computationally synthesized amorphous polymer structures based on a generalized polarizable reactive force-field (ReaxPQ+) model, which is orders-of-magnitude faster than quantum-mechanical methods; (2) prediction of composition–structure–RI relationships based on a machine-learning model based on graph attention neural network; and (3) computation of frequency-dependent RI combining ReaxPQ+ and Lorentz-oscillator models. The framework has been tested on a computational database of amorphous polymers." @default.
• W4386833319 created "2023-09-19" @default.
• W4386833319 creator A5029848340 @default.
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• W4386833319 date "2023-09-18" @default.
• W4386833319 modified "2023-09-26" @default.
• W4386833319 title "High-throughput computation and machine learning of refractive index of polymers" @default.
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• W4386833319 doi "https://doi.org/10.1063/5.0161198" @default.
• W4386833319 hasPublicationYear "2023" @default.
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