What Data is Required for Neural Networks in Catalysis?
Neural networks require substantial amounts of data to train effectively. In catalysis, this data can include experimental results, computational simulations, and literature data. Key parameters such as reaction rates, activation energies, and by-product formation are essential. The quality and quantity of data significantly influence the accuracy and reliability of the neural network models.