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April 29, 2026Journal of Applied Mechanics2 citations

On the Statistical Mechanics of Active Membranes: Some Selected Results

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SRSreekanth RameshPPPrashant K. PurohitYKY. Kulkarni

Key Points

  • This research aims to understand the mechanical behavior of active membranes using non-equilibrium statistical mechanics.
  • Developed a non-equilibrium statistical mechanics framework for modeling active membranes.
  • Derived analytical expressions for tension–area relation, mean square amplitude of fluctuations, correlation of normal vectors, and persistence length.
  • Focused on the utility of fluctuation spectra in characterizing membrane mechanics.
  • Demonstrated a tension–area relation that highlights how these membranes respond to tension changes.
  • Identified the mean square amplitude of fluctuations, providing insights into membrane stability.
  • Established correlations among vectors that govern membrane behavior, revealing important properties for experimental assays.

Abstract

Abstract Biological membranes and vesicles play a central role in living systems, forming dynamic interfaces that regulate cellular organization and function. Classical descriptions of membrane mechanics that are rooted in equilibrium statistical mechanics and linear elasticity have yielded deep insights into membrane morphology and the role of thermal fluctuations on cellular function. However, real biological membranes operate far from equilibrium, continuously driven by active processes powered by energy-consuming proteins. In this work, we employ a non-equilibrium statistical mechanics framework to model active membranes and derive analytical expressions for four fundamental properties that characterize their mechanical behavior: (a) the tension–area relation, (b) the mean square amplitude of fluctuations, (c) correlation of normal vectors, and (d) the persistence length. These results collectively highlight the utility of fluctuation spectra as a starting point for elucidating membrane mechanics in both passive and active settings. Moreover, these results provide a theoretical basis for analyzing and interpreting fluctuation-based assays of active membrane behavior.

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Cite This Study

Ramesh et al. (2026) studied this question.

synapsesocial.com/papers/69f1a08eedf4b468248071f5https://doi.org/10.1115/1.4071775
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