Entropy-Guided Detection of Chaos Transitions in Electrochemical Transport Systems

Abstract

Electrochemical transport systems can shift from ordered oscillation to chaotic behavior when diffusion, migration, and interfacial reaction kinetics interact under strong nonlinear forcing, affecting transport stability and response reliability. Recent studies on nonlinear reaction-diffusion dynamics, electrochemical oscillation, and entropy-based signal analysis show that instability often develops through intermediate regimes, but a unified entropy-based framework for detecting chaos onset in electrochemical transport systems remains limited. This gap is important because such systems often pass through transition-sensitive operating windows where early detection can improve control and diagnostics. In this article, a time-dependent transport model is analyzed using composite transport entropy, divergence behavior, regime mapping, and delay-embedded state-space density reconstruction. The results show that entropy increases systematically as the system moves from ordered to chaotic transport, accompanied by wider occupation of reconstructed electrochemical state space. The study demonstrates that entropy can serve as a physically meaningful indicator of chaos onset and offers a useful framework for identifying instability-prone regimes in transport-limited electrochemical devices.