Could someone help extend my knowledge of Molecular Dynamics?

Hi Daniel,

In addition to molecular dynamics, DFT can simulate the solvation dynamics of various polymers, including but not limited to DMSO, ETHANOL, METHANOL, and WATER. Examples of software cover Gaussian 09 and Biovia Material Studio. For molecular dynamics, you may use LAMMPS or BIOVIA Biovia Material Studio; please be advised that Material Studio software includes many modules that cover both quantum mechanics (e.g., DFT, HF). Quantum mechanics can predict potential and kinetic energies, but I am unsure about temperature, while molecular dynamics can provide them all.

Both approaches do have pros and cons, as well as challenges. Molecular dynamics can speed up the computations, but its accuracy is a function of many other parameters, such as the selection of the size of the unit cell representing the reaction and the full understanding of the reaction sequence and kinetics. Whereas simulation based on quantum mechanics is relatively slower, the reaction size can not exceed a hundred atoms at max – recall that molecular dynamics can have hundreds of thousands of atoms.

I did several computational modelling and simulation for ionic liquids and used both quantum mechanics and molecular dynamics to increase calculation repeatability and reproducibility. You can find in the literature many papers explaining the use of each, but I found a hybrid-based approach can predict results close to experimental results.

Raj Chawla

Hi Daniel,

I have used MD for various science and engineering simulations. Molecular Dynamics (MD) is a powerful computational technique used to simulate the motion and behavior of atoms and molecules over time. It is widely employed in various fields, such as materials science, chemistry, biophysics, and nanotechnology, to study the dynamics and properties of complex systems at the atomic or molecular level. Here are some key points to help extend your knowledge of Molecular Dynamics:

Basic Concept: Molecular Dynamics simulations are based on classical mechanics principles. Atoms and molecules in the system are represented as particles with defined positions, velocities, and forces. The simulation proceeds by numerically solving the equations of motion, which describe how the positions and velocities of the particles change over time.

Force Field: In MD simulations, the interactions between atoms are described by a force field. The force field includes potential energy functions that govern the interatomic forces, such as bonded and non-bonded interactions. Common force fields include CHARMM, AMBER, and OPLS.

Time Integration: To predict the behavior of the system over time, numerical integration techniques like Verlet, Leapfrog, or Runge-Kutta methods are used to propagate the positions and velocities of particles forward in time.

Ensemble Simulations: MD simulations can be performed in different ensembles, such as NVE (constant number of particles, volume, and energy), NVT (constant number of particles, volume, and temperature), and NPT (constant number of particles, pressure, and temperature).

Thermostats and Barostats: To maintain a desired temperature and pressure in the simulation, thermostats and barostats are used. These algorithms control the temperature and pressure of the system during the simulation.

Boundary Conditions: MD simulations are typically performed using periodic boundary conditions. This allows for the simulation of an infinitely repeating system, reducing finite-size effects and enabling the study of bulk properties.

Time Step: The time step used in MD simulations is a critical parameter. A balance must be struck between accuracy and computational efficiency. Smaller time steps improve accuracy but increase the computational cost.

Applications: Molecular Dynamics has diverse applications, such as studying protein folding, molecular interactions, material properties, phase transitions, and diffusion processes.

Challenges: MD simulations face challenges in accurately representing complex interactions, dealing with long simulation times, and accounting for quantum effects at small-length scales.

Visualization and Analysis: Visualization tools like VMD, PyMOL, and OVITO are often used to analyze and visualize the results of MD simulations.

You can refer to this book coauthored by me: Molecular Dynamics Simulation of Nanocomposites Using BIOVIA Materials Studio, Lammps and Gromacs | ScienceDirect

Hope it helps.

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