Abiogenesis as Phase Transition: A Dynamic Framework Based on the Genesis-Integration Principle

The origin of life remains one of the most profound scientific challenges, with competing hypotheses such as the RNA world, metabolism-first, and lipid-world models. This study introduces the Genesis-Integration Principle (GIP), a novel theoretical framework that mathematically formalizes abiogenesis as a dynamic, emergent process governed by universal generative, integrative, and optimizing transitions. The model unifies principles from non-equilibrium thermodynamics, information theory, and evolutionary dynamics to depict how molecular complexity evolves into biological organization. Using stochastic simulations combining kinetic Monte Carlo methods and coarse-grained molecular dynamics, we demonstrate how the GIP model replicates key empirical phenomena—including autocatalytic network growth, protocell stabilization, and scale-invariant adaptation. The model's predictions align with existing experimental data on ribozyme kinetics and vesicle formation with 15–20% accuracy. Furthermore, we propose testable predictions and experimental setups to evaluate the model’s applicability. GIP offers a unifying and falsifiable approach to understanding life’s emergence and may serve as a foundational paradigm in origin-of-life research and beyond.