Deformation propagation in responsive polymer network films.

نویسندگان

  • Surya K Ghosh
  • Andrey G Cherstvy
  • Ralf Metzler
چکیده

We study the elastic deformations in a cross-linked polymer network film triggered by the binding of submicron particles with a sticky surface, mimicking the interactions of viral pathogens with thin films of stimulus-responsive polymeric materials such as hydrogels. From extensive Langevin Dynamics simulations we quantify how far the network deformations propagate depending on the elasticity parameters of the network and the adhesion strength of the particles. We examine the dynamics of the collective area shrinkage of the network and obtain some simple relations for the associated characteristic decay lengths. A detailed analysis elucidates how the elastic energy of the network is distributed between stretching and compression modes in response to the particle binding. We also examine the force-distance curves of the repulsion or attraction interactions for a pair of sticky particles in the polymer network film as a function of the particle-particle separation. The results of this computational study provide new insight into collective phenomena in soft polymer network films and may, in particular, be applied to applications for visual detection of pathogens such as viruses via a macroscopic response of thin films of cross-linked hydrogels.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Unified Material Description for Light Induced Deformation in Azobenzene Polymers

Complex light-matter interactions in azobenzene polymers have limited our understanding of how photoisomerization induces deformation as a function of the underlying polymer network and form of the light excitation. A unified modeling framework is formulated to advance the understanding of surface deformation and bulk deformation of polymer films that are controlled by linear or circularly pola...

متن کامل

Cell Deformation Modeling Under External Force Using Artificial Neural Network

Embryogenesis, regeneration and cell differentiation in microbiological entities are influenced by mechanical forces. Therefore, development of mechanical properties of these materials is important. Neural network technique is a useful method which can be used to obtain cell deformation by the means of force-geometric deformation data or vice versa. Prior to insertion in the needle injection pr...

متن کامل

Submicrometric Films of Surface-Attached Polymer Network with Temperature-Responsive Properties.

Temperature-responsive properties of surface-attached poly(N-isopropylacrylamide) (PNIPAM) network films with well-controlled chemistry are investigated. The synthesis consists of cross-linking and grafting preformed ene-reactive polymer chains through thiol-ene click chemistry. The formation of surface-attached and cross-linked polymer films has the advantage of being well-controlled without a...

متن کامل

Prediction of Permanent Earthquake-Induced Deformation in Earth Dams and Embankments Using Artificial Neural Networks

This research intends to develop a method based on the Artificial Neural Network (ANN) to predict permanent earthquake-induced deformation of the earth dams and embankments. For this purpose, data sets of observations from 152 published case histories on the performance of the earth dams and embankments, during the past earthquakes, was used. In order to predict earthquake-induced deformation o...

متن کامل

A theory for large deformation and damage of interpenetrating polymer networks

Elastomers and gels can be formed by interpenetrating two polymer networks on a molecular scale. This paper develops a theory to characterize the large deformation and damage of interpenetrating polymer networks. The theory integrates an interpenetrating network model with the network alteration theory. The interpenetration of one network stretches polymer chains in the other network and reduce...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • The Journal of chemical physics

دوره 141 7  شماره 

صفحات  -

تاریخ انتشار 2014