Hydrogen Generation by Methanolysis of NaBH4 via Efficient CuFe2O4 Nanoparticle Catalyst: A Kinetic Study and DNN Model

Abstract

In this work, CuFe2O4 nanoparticles (NPs) were created using a hydrothermal process. The form and size of the obtained CuFe2O4 NPs were characterized using XRD and TEM techniques. The Scherrer equation and XRD measurements revealed that the crystal size of nanoparticles was 10.79 nm. The TEM study of nanoparticles with an average size of 7.673.75 nm revealed a distinctive core–shell structure. The methanolysis on NaBH4 at various parameters was used to assess the catalytic activity of NPs. The results showed that CuFe2O4 NPs are an effective catalyst for the methanolysis of NaBH4 in alkaline solutions, as demonstrated by the activation energy of 33.31 kJ/mol and turnover frequency (TOF), which was estimated as 2774.61 min−1 under ambient circumstances. These obtained NPs also showed an excellent (92%) reusability. A deep neural network architecture was determined using a neuro-evolutive approach based on a genetic algorithm to model the process and predict the catalyst performance in changing operating conditions. The determined models had a correlation > 0.9 and a mean squared error in the testing phase < 7.5%, indicating their capacity to capture the process dynamic effectively. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.