4-NEMD
Non-Equilibrium Molecular Dynamics (NEMD)
Non-Equilibrium Molecular Dynamics (NEMD) is a computational simulation technique used to study the behavior of molecular systems under non-equilibrium conditions. Unlike equilibrium molecular dynamics, which examines systems in a state of thermodynamic equilibrium, NEMD focuses on systems where external forces or gradients are applied, driving the system away from equilibrium.
Principles of NEMD
NEMD simulations are based on the principles of classical mechanics, where the motion of atoms and molecules is described by Newton's laws of motion. In NEMD, external perturbations such as temperature gradients, pressure differences, or electric fields are applied to the system. These perturbations induce non-equilibrium states, allowing researchers to study transport properties like thermal conductivity, viscosity, and diffusion coefficients.
Applications of NEMD
NEMD is widely used in the field of materials science and chemical engineering to investigate the microscopic mechanisms of transport processes. It is particularly useful for studying systems where experimental measurements are challenging, such as at the nanoscale or under extreme conditions.
Thermal Conductivity
One of the primary applications of NEMD is in calculating the thermal conductivity of materials. By imposing a temperature gradient across a material, NEMD can simulate heat flow and provide insights into the material's ability to conduct heat.
Viscosity
NEMD is also used to study the viscosity of fluids. By applying shear forces to a fluid system, researchers can observe the resulting flow and calculate the fluid's viscosity, which is crucial for understanding fluid dynamics in various industrial processes.
Diffusion
Diffusion processes can be studied using NEMD by applying concentration gradients. This allows for the investigation of how molecules move through different media, which is important for fields such as pharmacology and biochemistry.
Advantages and Limitations
NEMD offers several advantages, including the ability to directly simulate non-equilibrium processes and obtain detailed molecular-level insights. However, it also has limitations, such as the need for significant computational resources and the challenge of accurately modeling complex systems.
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Contributors: Prab R. Tumpati, MD