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Sandbox Physics
Membrane mechanics

L2 · Chapter 4

Reading bending rigidity from thermal flicker

A membrane that bends easily fluctuates more under thermal motion. Measuring several length scales can separate bending rigidity from tension: short wavelengths pay strongly for bending, and long wavelengths are more sensitive to tension. Temperature supplies the energy scale missing from a static shape.

Decompose a fluctuating surface into ripples

For a nearly spherical membrane of radius RR, divide radial displacement by radius to obtain a small dimensionless deformation u(θ,ϕ)u(\theta,\phi). Spherical harmonics are standard ripple patterns, analogous to sines on a circle. Increasing ℓ\ell gives finer surface structure; mm distinguishes variation around the axis.

The zero mode mainly changes mean radius and first-order modes translate the vesicle. After centering, shape fluctuations begin at ℓ=2\ell=2. The quadratic theory below assumes zero spontaneous curvature, small deformation and uniform tension. Our fluctuation model specifies tension instead of enforcing exactly fixed excess area in every frame.

r(θ,ϕ)=R[1+u(θ,ϕ)],u=∑ℓ,muℓmYℓmr(\theta,\phi)=R[1+u(\theta,\phi)],\qquad u=\sum_{\ell,m}u_{\ell m}Y_{\ell m}
Harmonics are normalized over solid angle. A second-order mean-radius correction can maintain volume; large deformations require the full surface energy.

Source: B. Loubet

Thermal energy in one quadratic degree of freedom

Take one real mode amplitude qq with energy Kqq2/2K_q q^2/2. Equilibrium probability is proportional to exp⁡[−Kqq2/(2kBT)]\exp[-K_q q^2/(2k_BT)]. Comparing this with a centered Gaussian gives variance kBT/Kqk_BT/K_q. Variance is the long-time mean squared amplitude.

Expand the Helfrich energy around a sphere. Orthogonality removes cross terms between different harmonics, leaving independent quadratic degrees of freedom. Curvature penalizes high-order ripples especially strongly. Tension adds a cost to surface undulations.

Eℓ=(ℓ−1)(ℓ+2)[ℓ(ℓ+1)+σˉ],σˉ=σR2κE_\ell=(\ell-1)(\ell+2)[\ell(\ell+1)+\bar\sigma],\qquad \bar\sigma=\frac{\sigma R^2}{\kappa}
The bar marks dimensionless tension. Physical tension still has units of force per length.
F(2)=κ2∑jEℓ(j)qj2,⟨qj2⟩=kBTκEℓ(j)F^{(2)}=\frac{\kappa}{2}\sum_j E_{\ell(j)}q_j^2,\qquad \langle q_j^2\rangle=\frac{k_BT}{\kappa E_{\ell(j)}}
The index enumerates normalized real harmonic degrees of freedom. Each retained quadratic coefficient must be positive for a finite equilibrium variance.

Source: B. Loubet

Worked example at two tensions

Set κ=20kBT\kappa=20k_BT. For ℓ=2\ell=2 and zero dimensionless tension, E2=24E_2=24. One normalized real coefficient has variance 1/480≃0.002081/480\simeq0.00208 and root-mean-square amplitude 0.04560.0456. This is a harmonic coefficient; local radial displacement also includes the radius and the local harmonic value.

Raise dimensionless tension to σˉ=6\bar\sigma=6. Then E2=48E_2=48 and the variance halves. For ℓ=10\ell=10, the bracket increases only from 110110 to 116116. Measuring several scales helps identify which suppression comes from tension.

Over a narrow mode range, rigidity and tension can compensate. More frames reduce random uncertainty; separating the parameters also requires a sufficiently broad scale range.

One equatorial wave contains several spherical modes

Tracking an equatorial contour means taking θ=π/2\theta=\pi/2 and Fourier-decomposing along azimuth. A single circular harmonic can receive contributions from several spherical orders. Treating it as one spherical harmonic changes the fitted model.

Write its normalized cosine amplitude as Am=∑ℓ≥mwℓmqℓmA_m=\sum_{\ell\geq m}w_{\ell m}q_{\ell m}, where wℓm=2NℓmPℓm(0)w_{\ell m}=\sqrt2N_{\ell m}P_\ell^m(0). Independent mode variances add to give the spectrum below. Sine amplitudes have the same variance. A finite-order model sums only its retained terms.

An objective also collects information over a finite focal depth, so real optical observation need not equal an infinitesimally thin equatorial section. We separate this issue from angular pixel averaging and exposure. The next chapter follows the measurement from membrane to image to estimate.

⟨Am2⟩=∑ℓ≥max⁡(2,m)wℓm2kBTκEℓ\langle A_m^2\rangle=\sum_{\ell\geq\max(2,m)}w_{\ell m}^2\frac{k_BT}{\kappa E_\ell}
Weights are the harmonic values on the equator. Parity makes some vanish. Surface order, contour mode number and observation geometry play distinct roles.

Source: S. A. Rautu et al. · J. Pécréaux et al.

Try the reasoning

Use several fluctuation scales

  1. Predict how rigidity changes the full flicker amplitude and which part of the spectrum responds most to tension.
  2. Change one parameter at a time. Compare the ideal contour with the spectrum derived from saved observations.
  3. As an advanced offline exercise, export the record and compare a low-mode-only fit with the full spectrum. Explain why a narrow scale range couples the parameters more strongly.

Exercises and explanations

  1. At fixed temperature and dimensionless tension, double rigidity. What happens to variance and root-mean-square amplitude?

    Read the explanation

    Variance halves and root-mean-square amplitude falls by the square root of two. Keeping dimensionless tension fixed requires adjusting physical tension with rigidity; the two fixed conditions differ.

  2. A first-order harmonic drifts. Does this indicate an exceptionally soft shape mode?

    Read the explanation

    First-order harmonics mainly translate the vesicle. Track and correct the center before interpreting shape fluctuations. Center-localization error can also contaminate low contour modes.

  3. A high-mode spectrum flattens. Must the membrane have become softer?

    Read the explanation

    First examine localization noise, pixels and focal depth. A noise floor can flatten a descending physical spectrum. The next chapter includes camera effects in the observation model.

Sources and calculated scope

  1. J. Pécréaux et al., Refined contour analysis of giant unilamellar vesicles, European Physical Journal E 13, 277–290 (2004)

    Contour fluctuation spectroscopy, camera integration and the observation plane. The course constructs its own seeded finite-mode records and derives its own exposure integral. Numerical fits here concern those synthetic records, not the paper’s lipid measurements.

  2. S. A. Rautu et al., The role of optical projection in the analysis of membrane fluctuations, Soft Matter 13, 3480–3483 (2017)

    Equations (1)–(3), Figure 1 and the finite focal-depth measurement problem. The ideal equatorial slice in our model has zero focal depth. Finite angular averaging and exposure are modeled separately; the full optical projection operator is discussed as an extension.

  3. B. Loubet, U. Seifert and M. A. Lomholt, Effective tension and fluctuations in active membranes, arXiv:1112.2919v2; Physical Review E 85, 031913 (2012)

    Version 2, 14 December 2011: quadratic quasi-spherical modes and a direct active force with exponential temporal correlations. Our equal-variance response comparison is an explicitly specified finite linear model. We do not reproduce the paper’s self-consistent excess-area tension curves or permeation and curvature-force cases.

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