Improving the prediction of bitumen’s density and thermal expansion by optimizing artificial neural networks with Optuna and TensorFlow

>0.99, MSEs below 0.1 %, and maximum absolute errors below 5 % on test data. In addition to reducing computational cost, the models exhibit improved interpolation and extrapolation capabilities, enabling reliable predictions for properties, ranges, and compositions not explicitly simulated. Key aspects of our approach include:•Transitioning from RFRs to ANNs, improving generalization, interpolation, and predictive accuracy.•Automated hyperparameter optimization, leveraging Optuna to maximize model efficiency.•Expanding applicability, enabling property prediction for unseen compositions without additional MD simulations.