Abstract: Examples are disclosed that relate to using natural language processing (NLP) to determine a recipe for a chemical synthesis described in a text to create a life cycle inventory (LCI). One example provides a method comprising receiving an input of a text from a publication comprising a description of a chemical product, and analyzing the text using NLP to determine a recipe for the chemical synthesis, the recipe comprising and action and action metadata, the action metadata comprising a reactant. The method further discloses obtaining LCI information for the reactant, determining an energy utilized for the action, and creating an estimate of an environmental impact for the product.

Abstract: A computing system is provided. The computing system comprises a processor, and memory comprising instructions executable by the processor to receive a chemical structure input, obtain retrosynthetic step data based on the chemical structure input, determine a chemical structure of a primary chemical in the retrosynthetic step data, the primary chemical being a chemical used as a starting material in a retrosynthetic step, when the structure of the primary chemical is not available in a life-cycle inventory (LCI), input the primary chemical into a trained proxy chemical selection model to select a proxy chemical for which an LCI is available, and obtain proxy chemical LCI data to include in an estimated LCI for a life cycle assessment (LCA).