Библиографическое описание:Predicting Diffusion Coefficients in Nafion Membranes during the Soaking Process Using a Machine Learning Approach : научное издание / I. I. Malashin [et al.]. - Текст : непосредственный // Polymers. - 2024. - Т. 16, № 9. - P. 1204. - ISSN 2073-4360, DOI 10.3390/polym16091204.
Аннотация:<jats:p>Nafion, a versatile polymer used in electrochemistry and membrane technologies, exhibits complex behaviors in saline environments. This study explores Nafion membrane’s IR spectra during soaking and subsequent drying processes in salt solutions at various concentrations. Utilizing the principles of Fick’s second law, diffusion coefficients for these processes are derived via exponential approximation. By harnessing machine learning (ML) techniques, including the optimization of neural network hyperparameters via a genetic algorithm (GA) and leveraging various regressors, we effectively pinpointed the optimal model for predicting diffusion coefficients. Notably, for the prediction of soaking coefficients, our model is composed of layers with 64, 64, 32, and 16 neurons, employing ReLU, ELU, sigmoid, and ELU activation functions, respectively. Conversely, for drying coefficients, our model features two hidden layers with 16 and 12 neurons, utilizing sigmoid and ELU activation functions, respectively.</jats:p>
Держатель оригинала документа:Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia, P.N. Lebedev Physical Institute of the Russian Academy of Sciences, 119991 Moscow, Russia, Scientific Department, Far Eastern Federal University, 690922 Vladivostok, Russia
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