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Updated: 13 hours 31 min ago

For an informal discussion

Sat, 2022-11-26 04:32

In reply to DEM CFD Postdoc position - Munster Technological University - Ireland

For an informal discussion about the position, please contact Dr Sandra Lenihan or Dr Alexander Krok at

I am highly interested in the position

Thu, 2022-11-24 11:47

In reply to Post-doc 18 months - highly competitive European Space Agency - EMTD Lab post-doc position - Interdisciplinary Centre for Security and Trust

I have been focusing on micromechanical characterization by instrumented indentation and scratch methods, have education background in materials science and engineering, have experience in finite element modeling by Abaqus, and am wondering if I am suitable for the position. My published articles can be downloaded via the link  with the passcode 3408


The abstract extended

Mon, 2022-11-21 14:35

In reply to ASME SSDM Conference

The paper abstract deadline is extended to Nov. 28th. Looking forward to your contribution!

Dear Yashashree,

Mon, 2022-11-21 13:09

In reply to statistical mechanics of membranes

Dear Yashashree,

Thank for your interest in this discussion and raising very important questions... 


Surface tension of biological membranes has been introduced in biophysics and cell mechanics literature through three totally different concepts: 1) a Lagrange multiplier to ensure the area is fixed under deformation, 2) simply a mechanical stiffness for producing in-plane stretch (in this case area is not necessarily fixed.), 3) Entropic tension, which is the derivative of the total free energy (as opposed to the ground state elastic energy) with respect to the area. The technical descriptions of these types of surface tension are also different, but yes, they all result in a reduction in thermal fluctuatuions. In pure lipid membranes, the entropic characteristics of a tension less membrane is expected to be stronger than that of a tense membrane. Real cell membranes are however, heterogeneous structures due to the presence of various proteins and domains and the interplay between these components are regulated by membrane surface tension. One example is the role of entropic surface tension on the gating of the mechanosensitive ion channels [R1]. In short, although the presence of surface tension reduce the fluctuations of the membrane, the resulting entropic effects in real biological cases are not always trivial and demand extensive continuum and statistical mechanics research.


I cannot agree with you more on the nessecitiy of accounting for nonequilibrium entropic effects, particularly in cell mechanics research. Currenlty, the majority of studies on cell mechanics are focused on using continuum mechanics modeling to understand the role of these active forces on biological phenomena. On the other hand, the study of entropic effects are limitted to equilibrium cases where there is no active force. Indeed, these two aspects should be studied within a unified continnum and nonequilibrium statistical mechanics framework to provide us with a comprehensive knowledge of the mechanics and physics of biological systems. 



R1: Lindén, Martin, Pierre Sens, and Rob Phillips. "Entropic tension in crowded membranes." PLoS computational biology8.3 (2012): e1002431.

statistical mechanics of membranes

Wed, 2022-11-16 23:49

In reply to Journal Club for November 2022: Entropy-driven mechanics of crystalline and biological membranes

Dear Fatemeh,

Thank you for the stimulating and timely article on the topic of statistical mechanics of membranes. Indeed, combining tools from equilibrium statistical mechanics with continuum mechanics models can furnish valuable insights into many interesting problems in biology and materials science. You have provided excellent examples of biological phenomena and processes where thermal fluctuations are known to play a vital role. I have two questions in the context of biological membranes. 

1. It is known that surface tension can significantly impact the thermal fluctuations of membranes. That is, a tensionless membrane shows larger fluctuations than a tense membrane. Yet, surface tension is often neglected in many studies based on statistical mechanics of biological membranes. I was curious if you or other researchers have looked into estimating the contribution from surface tension in some of the phenomena where thermal fluctuations are important, such as entropy-driven instabilities or vesicle size distributions. 

2. Most studies on biological membranes focus on modeling their equilibrium thermal fluctuations. However, in many phenomena such as pore formation or membrane fusion, the membrane may be driven away from equilibrium by non-thermal or 'active' forces which would require us to go beyond equilibrium statistical mechanics. Using tools from non-equilibrium statistical mechanics to understand some of the biophysics problems that you have mentioned would be a rich area of study. I was wondering if you could share your thoughts on this. 

Hello Wei,

Wed, 2022-11-02 22:19

In reply to Dear Fatemeh,

Hello Wei,

Thanks for your interest in this post. Yes, in fact your 2014 paper on thermomechanics of graphene [10] was our motivation to develop a statistical mechanics model that includes the nonlinear elasticity of crystalline membranes [9]. 

About the application of nonlinear statistical mechanics model for biological membranes, there are several cases where the linearized version of Helfrich energy does not give us a reliable model of the mechanics of biomembranes. Here I am only pointing to two of them as examples:

1) Biological vesicles are curved surfaces and deformation of the membrane is coupled with the pre-exisiting curvature field on the membrane. As a result, the mean curvature of the deformed surface will be highly nonlinear in terms of the out-of-plane displacement field. In addition to the geometric nonlinearity, the elasticity of membranes could be constitutively nonlinear as well. The constitutive nonlinearity is typically small and neglected in classical continuum mechanics models, but can result in remarkable entropic effects. One example is the size distribution of the vesicles that we studied in [27].

2) The elasticity of red blood cells membranes is typically studied using a coupled solid-fluid (polymerized) membrane system, where the interaction of phospholipid membrane with the underlying skeleton leads to a shear resistance [R1]. The kinematic of the deformation in this case is best described within nonlinear von-Karman plate theory... much like graphene and other crystalline membranes. Such nonlinearity is suggested to describe the mechanics of viral capsid [R2] and actin-supported biological shells as well [58].


R1: Discher, D.E., Boal, D.H. and Boey, S.K., 1998. Simulations of the erythrocyte cytoskeleton at large deformation. II. Micropipette aspiration. Biophysical Journal75(3), pp.1584-1597.

R2: May, E.R. and Brooks III, C.L., 2011. Determination of viral capsid elastic properties from equilibrium thermal fluctuations. Physical review letters106(18), p.188101.

Dear Fatemeh,

Wed, 2022-11-02 17:46

In reply to Journal Club for November 2022: Entropy-driven mechanics of crystalline and biological membranes

Dear Fatemeh,

Thanks for leading the discussion on this interesting topic! I got interested in the thermal rippling of graphene during my PhD work about 10 years ago. Along with Prof. Rui Huang, we studied the thermal rippling with statistical mechanics and molecular dynamics simulation and found considerable entropic contribution to the thermomechanical behavior of graphene due to the rippling [10]. Harmonic approximation was applied in our analysis, and we found the difference between the theory and MD because of the anharmonic coupling between bending and stretching modes. I'm very impressed by your later work [9] in which the anharmonic effect was included in the analysis to the first order approximation. Can you provide some comments on how this anharmonic effect plays important role in biological system? Thanks!  


Thank you Roy!

Wed, 2022-11-02 06:00

In reply to Very nice work AGAIN!

Thank you Roy!



Very nice work AGAIN!

Wed, 2022-11-02 01:32

In reply to Chiral topographic instability in shrinking spheres

To Fan,


From Roy

Zheng, Thank you so much! 

Sat, 2022-10-29 15:59

In reply to A great opportunity! I will

Zheng, Thank you so much! 

A great opportunity! I will

Sat, 2022-10-29 08:37

In reply to Postdoc and PhD positions at Texas A&M University

A great opportunity! I will forward the ad to the ZJU students.

Research environment: The

Tue, 2022-10-25 14:15

In reply to Postdoc positions supported by ERC Grant from Prof. Zhuang's lab in Hannover, Germany

Research environment: The postdocs will be placed at the Chair of Computational Science and Simulation Technology, Faculty of Mathematics and Physics at Leibniz-University Hannover (LUH). 

When to start?

Thu, 2022-10-20 07:15

In reply to PhD position related to Industry 4.0


Starting date: 01/12/2022


Robustness of virtual forming for multi-step process

Thu, 2022-10-20 07:14

In reply to PhD position related to Industry 4.0


Starting date: 01/12/2022


Very interesting review

Fri, 2022-09-30 23:53

In reply to Journal Club for October 2022: A Mechanical Approach to Shape, Flow, and Mechanoperception in Plants

Jean-François, thank you for discussing such an intriguing topic.  I enjoyed very much reading your brief review. 

Re: Great Summary

Sat, 2022-09-17 05:12

In reply to Great Summary

Dear Lifeng,

Many thanks for your kind words and comments!  Please see my replies below:

1. The booming of the light-based 3D techniques has attracted lots of attention in the precise fabrication of active-soft network materials at different length scales.  For instance, Prof. Qi Ge's group has used the digital light processing (DLP) based 3D-printing technique to fabricate shape-memory polymers (SMPs), liquid crystal elastomer (LCE), and hydrogel-based active soft network materials at microscale, where the width of microstructure ranges from 100 μm to 1 mm (see Advanced Materials, 2021, 33: 2101298; Advanced Materials, 2020, 32: 2000797; Science Advances, 2021, 7: eaba4261).  Prof. Rayne Zeng’s group used the projection stereolithography systems to fabricate the polymer-based soft network piezoelectric materials, where the width of microstructure is around 100 μm (see Natural Materials, 2019, 18: 234).  Buckling-guided 3D assembly could also be exploited to transform 2D active network materials into well-ordered 3D structures (see Nature Communications, 2022, 13: 524).

2. Existing studies showed the possibility of forming soft network materials with ordered microstructure in nano/micro-scale through electrospinning technique.  For example, the fixed metallic receiver always resulted in randomly distributed microstructures, due to the irregular spraying, but if the fixed receiver turns to the rotated metallic receiver, the aligned nano/micro-scale fibers can be obtained (see Advanced Materials Interfaces, 2022, 9: 2101808; ACS Applied Materials Interfaces, 2021, 13: 26339).  To obtain ordered nano/microstructures with more complex geometries, it might still remain challenging. 

Warm regards!


Great Summary

Thu, 2022-09-15 11:25

In reply to Journal Club for September 2022: Mechanics of soft network materials

Dear Yihui,

Thanks for this excellent and timely discussion. I am involved in some studies in 2D soft network materials and believe that these materials have remarkable futures. I have some thoughts in this topic.

1) To be active - soft network materials in response to various external stimuli. There are many active materials available in bulk material state, and are there any convenient methods to structure them in to a network state at different length scale? 

2) Randomly distributed vs highly ordered - To have well controlled macroscopic material properties, clearly highly-ordered network materials are desired. Electrospinning provides a convenient way to fabricate randomly distributed network materials in mesoscale. Is it possible to convert them into highly ordered nano-/micro-structures?  


Best wishes,



A new machine learning-based

Tue, 2022-09-13 02:54

In reply to Problem-independent machine learning (PIML)-based topology optimization—A universal approach

A new machine learning-based approach for topology optimization

 Problem-independent machine

Tue, 2022-09-13 02:53

In reply to Problem-independent machine learning (PIML)-based topology optimization—A universal approach

 Problem-independent machine learning (PIML)-based topology optimization—A universal approach


Tue, 2022-09-13 02:53

In reply to Problem-independent machine learning (PIML)-based topology optimization—A universal approach


Problem-independent machine learning (PIML)-based topology optimization—A universal approach


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