"Molecular dynamics (MD) is a computer simulation method for analyzing the physical movements of atoms and molecules."
The study of the motion of molecules in a system, and how their movement affects the system as a whole.
Classical Mechanics: This is the foundation for Molecular Dynamics simulations, and it describes how particles move in response to forces.
Statistical Mechanics: This branch of physics provides a theoretical framework for understanding how the behavior of large collections of particles can be predicted from the properties of individual particles.
Thermodynamics: This field studies the relationship between heat and energy, and is important in Molecular Dynamics simulations because many processes involve the transfer of energy from one particle to another.
Potential Energy Surfaces: This is a mathematical representation of the energy of a collection of particles as a function of the positions of those particles.
Force Fields: These are used in Molecular Dynamics simulations to describe the forces between particles, and can be derived from experimental results or from theoretical calculations.
Numerical Methods: These are used to solve the equations that describe the dynamics of particles in a Molecular Dynamics simulation.
Molecular Simulation Techniques: These are methods used in Molecular Dynamics simulations to generate initial configurations, control the temperature and pressure of the system, and analyze the results.
Molecular Dynamics Algorithms: These are the computational methods used in Molecular Dynamics simulations to calculate the motion of particles over time.
Sampling Theory: This is the study of how to generate a representative sample of the possible outcomes in a Molecular Dynamics simulation.
Molecular Dynamics Applications: This includes applications of Molecular Dynamics simulations in fields such as chemistry, physics, biology, and materials science.
Classical Molecular Dynamics: This type of simulation uses classical mechanics to model the motion of atoms and molecules.
Ab Initio Molecular Dynamics: An approach in which the electronic structure is calculated at each step of the simulation to obtain the forces needed to move the atoms.
Coarse-Grained Molecular Dynamics: It refers to a technique that reduces the number of degrees of freedom in the system.
Quantum Molecular Dynamics: This type of simulation uses quantum mechanics to model the motion of atoms and molecules.
Force-Field Molecular Dynamics: It is a simulation that uses a potential energy surface and a set of empirical equations to represent the interatomic forces.
Hybrid Molecular Dynamics: It is a simulation that combines quantum mechanics with classical mechanics to model systems that require both levels of theory to be accurately represented.
Accelerated Molecular Dynamics: A technique designed to accelerate molecular dynamics simulations by biasing their potential energy surfaces.
Metadynamics: A technique that can be used to explore energy landscapes and overcome the limitations of standard molecular dynamics simulations.
Umbrella Sampling: A technique used to calculate free energy profiles of molecular systems.
Monte Carlo Molecular Dynamics: A simulation method that combines the principles of both molecular dynamics and Monte Carlo methods to model the behavior of molecular systems.
"The atoms and molecules are allowed to interact for a fixed period of time, giving a view of the dynamic 'evolution' of the system."
"The trajectories of atoms and molecules are determined by numerically solving Newton's equations of motion for a system of interacting particles."
"Forces between the particles and their potential energies are often calculated using interatomic potentials or molecular mechanical force fields."
"The method is applied mostly in chemical physics, materials science, and biophysics."
"Because molecular systems typically consist of a vast number of particles, it is impossible to determine the properties of such complex systems analytically; MD simulation circumvents this problem by using numerical methods."
"Long MD simulations are mathematically ill-conditioned, generating cumulative errors in numerical integration."
"The cumulative errors in numerical integration can be minimized with proper selection of algorithms and parameters, but not eliminated."
"For systems that obey the ergodic hypothesis, the evolution of one molecular dynamics simulation may be used to determine the macroscopic thermodynamic properties of the system."
"The time averages of an ergodic system correspond to microcanonical ensemble averages."
"MD has also been termed 'statistical mechanics by numbers'."
"MD [provides] insight into molecular motion on an atomic scale."
"The objective of MD simulations is to observe the physical movements and interactions of atoms and molecules."
"MD simulation circumvents [the problem of determining complex system properties] by using numerical methods."
"MD is applied in chemical physics, materials science, and biophysics to gain insights into molecular behavior."
"Trajectories of atoms and molecules are determined by numerically solving Newton's equations of motion."
"Cumulative errors in numerical integration can be minimized with proper selection of algorithms and parameters."
"MD simulation allows atoms and molecules to interact for a fixed period of time."
"Forces between the particles and their potential energies are often calculated using interatomic potentials or molecular mechanical force fields."
"MD is primarily applied in chemical physics, materials science, and biophysics."