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Related Concept Videos

Thermodynamic Potentials01:26

Thermodynamic Potentials

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Thermodynamic potentials are state functions that are extremely useful in analyzing a thermodynamic system. They have dimensions of energy. The four important thermodynamic potentials are internal energy, enthalpy, Helmholtz free energy, and Gibbs free energy. These thermodynamic potentials can be expressed using two of the following variables: pressure, volume, temperature, and entropy. These two variables are expressed as the rate of change of the thermodynamic potential with respect to other...
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Thermodynamics: Activity Coefficient01:24

Thermodynamics: Activity Coefficient

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Activity is the measure of the effective concentration of the species in solution. It can be expressed as the product of the molar concentration of the species and its activity coefficient. The activity coefficient is a dimensionless quantity and depends on the total ionic strength of the solution.
The activity coefficient is a measure of the deviation from ideal behavior. When the ionic strength of the solution is minimal, the activity coefficient of an ionic species is close to unity, making...
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Adiabatic Processes for an Ideal Gas01:18

Adiabatic Processes for an Ideal Gas

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When an ideal gas is compressed adiabatically, that is, without adding heat, work is done on it, and its temperature increases. In an adiabatic expansion, the gas does work, and its temperature drops. Adiabatic compressions actually occur in the cylinders of a car, where the compressions of the gas-air mixture take place so quickly that there is no time for the mixture to exchange heat with its environment. Nevertheless, because work is done on the mixture during the compression, its...
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Thermal Sigmatropic Reactions: Overview01:16

Thermal Sigmatropic Reactions: Overview

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Sigmatropic rearrangements are a class of pericyclic reactions in which a σ bond migrates from one part of a π system to another. These are intramolecular rearrangements where the total number of σ and π bonds remain unchanged.
Sigmatropic shifts are classified based on an order term [i, j ], where i and j indicate the number of atoms across which each end of the σ bond migrates. Below are examples of a [3,3] sigmatropic shift in...
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Chemical Equilibria: Systematic Approach to Equilibrium Calculations01:21

Chemical Equilibria: Systematic Approach to Equilibrium Calculations

734
Equilibrium calculations for systems involving multiple equilibria are often complex. For example, to calculate the solubility of a sparingly soluble salt in an aqueous solution in the presence of a common ion, one must consider all the equilibria in this solution. Calculations for these systems can be complicated and tedious, so a systematic approach with a series of steps is often helpful. The process is detailed below.
The first step is to identify all the chemical reactions involved, The...
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Maxwell's Thermodynamic Relations01:23

Maxwell's Thermodynamic Relations

2.8K
Maxwell's thermodynamic relations are very useful in solving problems in thermodynamics. Each of Maxwell's relations relates a partial differential between quantities that can be hard to measure experimentally to a partial differential between quantities that can be easily measured. These relations are a set of equations derivable from the symmetry of the second derivatives and the thermodynamic potentials.
All thermodynamic potentials are exact differentials. Therefore, their second-order...
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Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
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Thermodynamic calculations using reverse Monte Carlo: Simultaneously tuning multiple short-range order parameters for

Suhail Haque1, Abhijit Chatterjee1

  • 1Department of Chemical Engineering, Indian Institute of Technology Bombay, Mumbai 400076, India.

The Journal of Chemical Physics
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A new computational method using reverse Monte Carlo (RMC) and short-range order (SRO) parameters offers a faster, accurate approach to lattice thermodynamic calculations. This efficient technique excels in complex adsorption problems, outperforming traditional Monte Carlo methods.

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Area of Science:

  • Computational materials science
  • Surface science
  • Thermodynamics

Background:

  • Lattice simulations are crucial for understanding crystalline solids, alloys, and surface phenomena.
  • Traditional methods like Metropolis Monte Carlo (MC) can be computationally intensive, requiring millions of configurations.

Purpose of the Study:

  • To introduce a computationally efficient method for lattice thermodynamic calculations.
  • To compare the accuracy and speed of the new method against established techniques.

Main Methods:

  • Utilized reverse Monte Carlo (RMC) simulations combined with multiple short-range order (SRO) parameters.
  • Employed Newton-Raphson iterations to solve nonlinear algebraic SRO growth rate equations for equilibrium configurations.

Main Results:

  • The RMC-based method achieves accuracy comparable to Metropolis Monte Carlo (MC).
  • Equilibrium configurations are determined rapidly within 5-10 iterations, significantly faster than MC.
  • The RMC approach effectively handles geometric frustration in interacting 2D adsorption systems.

Conclusions:

  • The RMC method provides a computationally superior alternative for lattice thermodynamic calculations.
  • This technique accurately predicts ordered adlayer configurations, such as Cl on Cu(100), outperforming grand canonical MC.