A domain-specific compiler theory based framework for automated reaction network generation

Catalytic chemical reaction networks are often very complicated because of the numerous species and reactions involved. Hence, automating the network generation process is necessary as it is quite labor intensive and error prone to write down all the reactions manually. We present an automated integrated framework for reaction network generation based on domain-specific compiler theory using a knowledge base of chemistry rules. The chemistry rules represent basic reaction mechanisms that the reactants can undergo. The system's domain-specific compiler takes the rules and initial reactants as inputs, parses the rule text, generates the intermediate representation, and finally produces the reaction network by interpreting the intermediate representation. We chose the Abstract Syntax Tree (AST) as the intermediate representation because of its transparency and ease of search. The system executes the AST using the initial reactants, and generates the reaction network. The Reaction Description Language (RDL) has been extended to describe the chemistry rules for catalytic systems, and the molecules are represented by Simplified Molecular Input Line Entry System (SMILES). This framework separates the molecules and the behavior of catalysts, represented by the chemistry rules. This approach accelerates the speed of generating hypotheses for building the kinetic models for catalytic systems.