Thermo-physical properties prediction of carbon-based magnetic nanofluids based on an artificial neural network

Nanostructured magnetic suspensions have superior thermophysical properties, which attracted widespread attention owing to their industrial applications for heat transfer enhancement and thermal management. However, experimental measurements of the properties magnetic-based nanofluids, especially under an external field, are significantly complicated, expensive, time consuming. Currently, method predicting summarizing material through machine learning has accelerated development materials practical applications. This study aims predict nanofluids by establishing artificial neural network (ANN) using data on viscosity, conductivity, specific heat. The results based ANN model agree with according different evaluation criteria. Different previous theoretical models reviewed, is proven be more accurate comparing values models, can also provide a basis explaining nanofluids. In present study, was developed informatics functional materials.