A neural network model was created to predict how two different substances stick to activated carbon. The model was trained using mostly data from one substance, and only a few data sets were needed for good results. Once trained, the network could accurately predict how two substances would stick to the carbon, even when the system was not ideal. This new approach could help scientists understand and predict how different substances interact with activated carbon in real-world situations.