Charged Soft Matter

In many systems consisting of soft and biological matter, electrostatic interactions play an important role. For example, synthetic polyelectrolytes (charged polymers), as well as biopolymers such as DNA and many proteins, are highly charged. We develop and employ various coarse-grained simulation methodologies to understand the behavior of charged soft matter systems. A particular focus is the study of weak polyelectrolytes, i.e. polyelectrolytes consisting of weak acid or base groups.

Algorithms for Long-Range Interactions

The long-range nature of the Coulomb interaction requires specialized algorithms to calculate electrostatic forces and energies in simulation boxes with periodic boundary conditions. We have implemented multiple electrostatics solvers, including the P3M method, in the ESPResSo software. Furthermore, we have developed new algorithms, including methods for 2D- and 1D-periodic systems and dielectric interfaces. We have also contributed to the ScaFaCoS library of Coulomb solvers.

Relevant references: 10.1063/1.477414, 10.1063/1.477415, 10.1063/1.1491955, 10.1063/1.1491954, 10.1063/1.3376011, 10.1103/PhysRevE.88.063308 

Weak Polyelectrolytes and Charge Regulation

Many polyelectrolytes are of a "weak" nature, i.e. they contain weak acid or base groups. The presence of such weak groups means that the charge of these molecules is not fixed, but determined by a chemical (acid-base) equilibrium, a phenomenon referred to as "charge-regulation". Accordingly, the charge and thus many physical characteristics of charge-regulating systems can be tuned by adjusting external parameters such as the pH-value or the salt concentration. To model charge-regulation effects in coarse-grained simulations, non-standard Monte Carlo techniques are required. We have implemented several such algorithms in the ESPResSo software and also invented a new method, the grand-reaction ensemble, which enables the simulation of charge-regulating two-phase systems. Moreover, we have also recently developed the Python-base Molecule Builder for ESPResSo (pyMBE), which enables a convenient setup of charge-regulating systems with complex molecular architectures.

Relevant references: 10.1039/C8SM02085J, 10.1021/acs.macromol.0c00260, 10.1063/5.0216389

Polyelectrolyte Hydrogels

Polyelectrolyte hydrogels are chemically cross-linked networks consisting of charged polymer chains. Their tremendous swelling capability in water makes these materials interesting candidates for various technological and medical applications, including desalination and drug delivery. We have used coarse-grained simulations to develop simplified, mean-field like models to predict the swelling of hydrogels. Furthermore, we have also applied mean-field approaches to microgels, which are promising materials for targeted drug delivery. For hydrogels consisting of weak polyelectrolyte chains, the swelling can be controlled by the pH-value. To model this phenomenon in simulations, we have applied our grand-reaction methods in several simulation studies.

Relevant references: 10.1016/j.desal.2017.03.027, 10.1103/PhysRevLett.122.208002, 10.1063/5.0205608, 10.1021/acs.macromol.1c02489, 10.1021/acs.macromol.2c01916 

Polyelectrolyte Brushes

Weak polyelectrolyte brushes consist of pH-responsive polymer chains that are densely grafted to a flat surface. The reversible response of these systems to changes in the pH-value allows for their use in protein binding and purification applications. Simulations can aid in the understanding of the microscopic details of this process. We have applied coarse-grained simulations to study the behavior of weak polyelectrolyte brushes in the presence of mono- and divalent salts as well as charge-regulating ampholytes. Ongoing investigations are concerned with the binding characteristics of realistic protein models with various charge distributions.

Relevant references: 10.1103/PhysRevLett.131.168101, 0.26434/chemrxiv-2024-xxjr1-v2, 10.26434/chemrxiv-2024-b10lj 

Contacts

This image shows David Beyer

David Beyer

 

PhD Student

This image shows Somesh Kurahatti

Somesh Kurahatti

 

PhD Student

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