Although relatively new in the scientific domain, these tools have already demonstrated their utility in materials science and other scientific fields by creating datasets , providing insights into synthesis routes , and developing materialsand chemistry-aware language models . Thus, we employed these NLP tools to gain insights from the scientific literature pertaining to CO 2 RR and CORR. By selecting relevant articles through a query in the Web of Science, we were able to uncover valuable details about commonly used catalyst elements, their combinations in materials, faradaic efficiencies reported in the literature for each element-based catalyst, the relationship between catalyst composition and reaction selectivity, frequently used electrolytes in CO 2 electro-reduction reaction (CO 2 ER), and how these electrolytes are utilized in combination with the previously identified catalyst elements. Furthermore, by tracking the use of these materials over the years, we could identify trends in the literature and also prominent compositions that have gained the attention of researchers in recent times.