Monte Carlo simulations of patch models with applications to soft matter
S K Gaughran1, J M Rickman2, J Haaga1
1Department of Physics, Lehigh University, Bethlehem, PA 18015, USA. jmr6@lehigh.edu.
Soft Matter
|August 27, 2020
Summary
This study unified patch models for protein and colloid self-assembly. Particle clustering and phase behavior were explored in monodisperse and polydisperse systems, revealing insights into soft matter interactions.
Area of Science:
- Soft Matter Physics
- Computational Chemistry
- Biophysics
Background:
- Patch models are crucial for understanding anisotropic interactions in soft matter.
- Self-assembly is a fundamental process in both biological and synthetic systems.
Purpose of the Study:
- To present a unified study of a patch model for particle self-assembly.
- To explore self-assembly in both monodisperse and polydisperse systems.
- To compare and contrast self-assembly in protein and colloidal systems.
Main Methods:
- Utilized Monte Carlo simulations to generate a temperature-density phase diagram for polyglutamine.
- Employed a coarse-grained PLUM model for comparative analysis.
- Investigated the impact of size polydispersity on binary colloidal mixtures.
Main Results:
- Obtained a phase diagram for polyglutamine, identifying gas-phase clusters within the supersaturation region.
- Demonstrated that increasing polydispersity broadens gas-liquid phase coexistence in colloidal mixtures.
- Observed small particles decorating large particles, forming bridges in polydisperse colloidal systems.
Conclusions:
- The patch model provides a unified framework for studying self-assembly across diverse soft matter systems.
- Polydispersity significantly influences phase behavior and structural organization in colloidal mixtures.
- This research offers a comparative perspective on self-assembly mechanisms in proteins and colloids.
Related Concept Videos
01:29Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
202
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
202
01:34The Fluid Mosaic Model
174.6K
The fluid mosaic model was first proposed as a visual representation of research observations. The model comprises the composition and dynamics of membranes and serves as a foundation for future membrane-related studies. The model depicts the structure of the plasma membrane with a variety of components, which include phospholipids, proteins, and carbohydrates. These integral molecules are loosely bound, defining the cell’s border and providing fluidity for optimal function.
174.6K
01:18Patch Clamp
6.1K
Many fundamental cell functions such as muscle contraction and nerve transmission rely on the electrical signals produced by the movement of positively and negatively charged ions across the cell membrane. One competent method to record current flowing across the whole cell or single ion channel is the patch-clamp technique.
In this method, a glass micropipette containing electrolyte solution is tightly sealed against a small portion of the cell membrane. As a result, a patch of the cell...
In this method, a glass micropipette containing electrolyte solution is tightly sealed against a small portion of the cell membrane. As a result, a patch of the cell...
6.1K
02:00Molecular Models
43.1K
Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
43.1K
01:21Mechanistic Models: Overview of Compartment Models
278
Mechanistic models, a category encompassing both physiological and compartmental modeling, differ from empirical models' approaches to incorporating known factors about the systems being modeled. Empirical models describe data with minimal assumptions, while mechanistic models aim to provide a robust description of available data by specifying assumptions and integrating known factors about the system. Compartmental analysis is a key example of a mechanistic model in pharmacokinetics and...
278