Related Experiment Video
Updated: Apr 24, 2026
11:03
An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
Published on: December 4, 2017
7.6K
Extended temperature-accelerated dynamics: enabling long-time full-scale modeling of large rare-event systems
Vladimir Bochenkov1, Nikolay Suetin2, Sadasivan Shankar3
1Chemistry Department, Lomonosov Moscow State University, 119991 Moscow, Russia and Interdisciplinary Nanoscience Center (iNANO), Aarhus University, 8000 Aarhus, Denmark.
The Journal of Chemical Physics
|September 8, 2014
Summary
A new Extended Temperature-Accelerated Dynamics (XTAD) method models rare events in large systems. XTAD enables atomistic simulations for material science and solid state physics, overcoming previous system size limitations.
Area of Science:
- Computational material science
- Statistical physics
- Molecular dynamics simulations
Background:
- Modeling long-timescale evolution of large rare-event systems is computationally challenging.
- Existing methods often face limitations in system size and handling simultaneous diffusion events.
Purpose of the Study:
- Introduce the Extended Temperature-Accelerated Dynamics (XTAD) method.
- Enable modeling of large rare-event systems with unprecedented scale.
- Facilitate atomistic simulations of complex material processes.
Main Methods:
- Extended Temperature-Accelerated Dynamics (XTAD) based on Temperature-Accelerated Dynamics.
- Full-scale parallel molecular dynamics simulations to probe potential energy surfaces.
- Adaptive on-the-fly system decomposition for rare event energetics analysis.
Main Results:
- XTAD removes feasible system size limitations.
- The method successfully handles simultaneous diffusion events, including concerted and local transitions.
- Demonstrates applicability to solid state physics diffusion mechanisms.
Conclusions:
- XTAD offers a powerful new approach for simulating rare events in large systems.
- Opens new avenues for atomistic simulations in material science, including thin film growth.
- The intrinsically parallel algorithm enhances computational efficiency for complex processes.
Related Concept Videos
02:55Temperature Dependence on Reaction Rate
77.5K
The Collision Theory
Atoms, molecules, or ions must collide before they can react with each other. Atoms must be close together to form chemical bonds. This premise is the basis for a theory that explains many observations regarding chemical kinetics, including factors affecting reaction rates.
The collision theory is based on the postulates that (i) the reaction rate is proportional to the rate of reactant collisions, (ii) the reacting species collide in an orientation allowing contact between...
Atoms, molecules, or ions must collide before they can react with each other. Atoms must be close together to form chemical bonds. This premise is the basis for a theory that explains many observations regarding chemical kinetics, including factors affecting reaction rates.
The collision theory is based on the postulates that (i) the reaction rate is proportional to the rate of reactant collisions, (ii) the reacting species collide in an orientation allowing contact between...
77.5K
01:06Thermodynamic Systems
6.4K
A thermodynamic system is a set of objects whose thermodynamic properties are of interest. The system is considered to be embedded in its surroundings or the environment. The system and its environment can exchange heat and do work on each other through a boundary that separates them. However, the immediate surroundings of the system interact with it directly and therefore have a much stronger influence on its behavior and properties.
Consider an example of tea boiling in a kettle. The...
Consider an example of tea boiling in a kettle. The...
6.4K
01:10Entropy Change in Reversible Processes
2.4K
In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
2.4K
01:21Entropy Changes Accompanying Specific Processes
153
Entropy, a measure of disorder in a system, changes during phase transitions like freezing or boiling. At the transition temperature Ttrs, where two phases are in equilibrium, the phase transition is a reversible process. The entropy change can be calculated from a substance's enthalpy of transition using the equation ΔStrs = ΔtrsH /Ttrs.When a perfect gas expands isothermally from one volume to another, entropy increases logarithmically with volume. Conversely, isothermal compression...
153
01:19Cyclic Processes And Isolated Systems
2.6K
A thermodynamic system with zero heat exchange and work is an isolated system. For these systems, the internal energy remains constant.
In the case of a non-isolated system, the change in the internal energy is zero only if the process is cyclic. A thermodynamic process is considered cyclic if the system undergoes a series of changes and returns to its initial state.
Consider a cyclic process that returns to its initial state, undergoing a four-step process. The heat transfer along each...
In the case of a non-isolated system, the change in the internal energy is zero only if the process is cyclic. A thermodynamic process is considered cyclic if the system undergoes a series of changes and returns to its initial state.
Consider a cyclic process that returns to its initial state, undergoing a four-step process. The heat transfer along each...
2.6K
01:25Modeling with Differential Equations
327
Population dynamics can be described mathematically by considering the population size P(t) as a function of time. The rate of change of the population is then represented by the derivative of P(t). A simple assumption is that the rate of growth is proportional to the size of the population itself. This leads to an exponential growth model, where the population increases rapidly without bound. While this is a useful first approximation, it does not reflect realistic long-term...
327