Explore the emergence of life-like behaviors in chemical networks through an innovative approach to prebiotic chemistry. Delve into untargeted analysis methods that focus on temporal dynamics of product ensembles, allowing for the identification of complex chemical networks with properties such as environmental responsiveness, auto-catalysis, self-sustenance, and evolvability. Learn about the Chemical Ecosystem Selection (CES) experiment and how UPLC-DDA-MS/MS analysis is used to track changes over time in complex prebiotic mixtures. Discover how this approach has led to observations of interesting patterns, such as the truncation of combinatorial explosions in mineral environments. Gain insights into the application of bespoke data analysis tools and algorithms designed to explore different levels of chemical persistence over generations, ultimately aiding in the identification of unique products arising from long-term Chemical Ecosystem Selection.