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Predicting Diffusion Coefficients in Nafion Membranes during the Soaking Process Using a Machine Learning Approach

Описание

Тип публикации: статья из журнала

Год издания: 2024

Идентификатор 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, diffusПоказать полностьюion 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>

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Издание

Журнал: Polymers

Выпуск журнала: Т. 16, № 9

Номера страниц: 1204

ISSN журнала: 20734360

Место издания: Basel

Издатель: MDPI

Персоны

  • Malashin Ivan (Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia)
  • Daibagya Daniil (P.N. Lebedev Physical Institute of the Russian Academy of Sciences, 119991 Moscow, Russia)
  • Tynchenko Vadim (Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia)
  • Gantimurov Andrei (Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia)
  • Nelyub Vladimir (Scientific Department, Far Eastern Federal University, 690922 Vladivostok, Russia)
  • Borodulin Aleksei (Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia)

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