Recurrence network and recurrence plot: A novel data analytic approach to molecular dynamics in thermal lensing

Abstract

Unwrapping thermal-induced molecular dynamics has always been a fascinating area of research in fluid dynamics. The paper is the first report on the development of recurrence plot (RP) and recurrence network (RN) as a novel tool in data analytics for understanding the molecular/particle dynamics in fluids during transient heat flow by analysing the thermal lens (TL) signal. For the study, the TL signal from ethylene glycol is recorded, segmented into three regions and analysed by constructing RP and RN. The variations of recurrence-based features are correlated with the temporal evolution of enthalpy of the system upon transforming from a less ordered to a more ordered state, which appears as a spread of shorter lines/dots in RP. The increase in the chaoticity of the system appears in the RN as a decrease in edges, graph density, transitivity and an increase in average path length and diameter. The study reveals the possible application of these novel techniques in thermal system design and monitoring.