Machine Learning Model for Assessing Melting Pressure Conditions of the TTG Genesis: Implications for the Timing of the Onset of Global Plate Tectonics

Abstract Understanding the pressure conditions of the formation of tonalite‐trondhjemite‐granodiorite (TTG) series rocks is important, as these rocks are key constituents of the Archean continental crust. However, the detailed pressure history of Archean TTG gneisses remains ambiguous due to uncertainties surrounding their sources and the effects of fractional crystallization. To address this problem, we developed a machine learning‐based tool to predict the melting pressures of Archean TTG gneisses from their major element compositions. This method provides high accuracy, supports batch processing, and incorporates the effects of fractional crystallization, mineral segregation, and other factors, making it suitable for application to global data sets. Our results indicate that the Earth's oldest rocks record two key transitions from low to medium pressure conditions, suggesting that the formation of the earliest continental crust may not have required deep subduction‐related geodynamic processes. High‐pressure rocks and melting conditions first emerged around 3.8 Ga (up to 1.5 GPa), becoming more extensive globally after 3.5 Ga (up to 1.9–2.0 GPa). Fractional crystallization, source, and other petrogenetic factors significantly influence the identification of high‐pressure TTGs, suggesting that true global high‐pressure TTGs may make up only ∼8% of the total rock record, much lower than earlier estimates. Our findings suggest that after 3.5 Ga, increased crustal rigidity likely facilitated widespread high‐pressure melting and plate tectonic activity across numerous terranes. This research provides new insights into Archean geodynamic processes and demonstrates the power of machine learning in advancing our understanding of ancient Earth systems.