Integrating Kinetics into Synthetic Studies via Adaptable Concentration-Dependent Yield Analysis

When inversion of optical rotation was discovered during the hydrolysis of sucrose, the name "invert sugar" was coined for this sweetener. The inversion process sparked the field of chemical kinetics by introducing time-course analyses and differential rate equations as important tools for studying reaction mechanisms and rates. These tools have become indispensable in kinetic studies and have also advanced other fields, including biochemistry and the chemical industry. In this study, chemical kinetics are integrated into synthetic studies. The modeling approaches in this study, i.e., machine-learning (ML) modeling of yield distributions and Euler-integration-based modeling of kinetics, are found to be sufficiently versatile and adaptable to accommodate chemical and operational considerations, allowing concentration-dependent yield analysis (CYAN) to reveal kinetics hidden behind synthetic yield data. Importantly, the ML+CYAN approach reveals unexpected aspects of metal-templated oligomeric macrocyclization, particularly the retardation of oligomer-oligomer coupling. The versatility of the approach is further demonstrated through kinetic analysis of existing yield datasets reported in Wilhelmy's classic 1850 paper on chemical kinetics. This approach is practical enough to be integrated into synthetic studies as an add-on module that provides mechanistic and kinetic insights.