The Quantum-to-Classical Transducer: A Thermodynamic and Quantum Mechanical Framework for the Emergence of Bioenergetics

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Authors: Prasanth S. Ariyannur
Cited by: 1
References: 10

Abstract

The universal conservation of the Proton-Motive Force (PMF) indicates that chemiosmotic coupling was a primary requisite for abiogenesis. However, the mechanism governing Kinetic State Selection (KSS)—the process by which specific metabolic pathways were identified within high-dimensional prebiotic chemical spaces—remains a fundamental challenge in evolutionary biology. This paper proposes the Quantum-to-Classical Transducer (QCT) framework, positioning the PMF as the emergent outcome of a scale-transduction cascade at mineral-organic interfaces. Driven by persistent non-equilibrium electrostatic potentials in the Hadean environment, semi-conductive mineral clusters facilitated electron transfer governed by non-adiabatic quantum kinetics. We demonstrate that nuclear tunneling provided a significant rate enhancement, enabling the sampling of dissipative pathways characterized by high reorganization energies that are kinetically inhibited in classical regimes. The transition from coherent sub-atomic tunneling to stable ionic gradients is modeled as an environmental decoherence event, where the aqueous medium functions as an implicit measurement apparatus that rectifies high-frequency electronic search into a classical steady state. This mechanism joins rapid electron flux to slow proton translocation, utilizing the mass-anisotropy between the two carriers to generate a stable electrochemical potential. The QCT framework suggests that the PMF served as a pre-Darwinian filter, favoring metabolic routes with optimal dissipative efficiency and providing a deterministic physical resolution to the statistical improbabilities identified in stochastic prebiotic models.​

Fields of Study & Subjects

Origins and Evolution of Life Earth Systems and Cosmic Evolution ATP Synthase and ATPases Research

Publication details

Journal / source
SSRN Electronic Journal
Publisher
Elsevier BV
Publication date
1 January 2026
Document type
Preprint