Autonomous Discovery of Unknown Reaction Pathways from Data by Chemical Reaction Neural Network

Understand

Chemical reactions occur in energy, environmental, biological, and many other natural systems, and the inference of the reaction networks is essential to understand and design the chemical processes in engineering and life sciences.

• Yet, revealing the reaction pathways for complex systems and processes is still challenging due to the lack of knowledge of the involved species and reactions.
• Here, we present a neural network approach that autonomously discovers reaction pathways from the time-resolved species concentration data.
• The proposed Chemical Reaction Neural Network (CRNN), by design, satisfies the fundamental physics laws, including the Law of Mass Action and the Arrhenius Law.