Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Entropy01:18

Entropy

2.6K
The first law of thermodynamics is quantitatively formulated via an equation relating the internal energy of a system, the heat exchanged by it, and the work done on it. A quantitative formulation of the second law of thermodynamics leads to defining a state function, the entropy.
When an ideal gas expands isothermally, the disorder in the gas increases. From the molecular perspective, the gas molecules have more volume to move around in.
Consider an infinitesimal step in the expansion, which...
2.6K
Joule-Thomson Effect01:21

Joule-Thomson Effect

3.8K
The Joule-Thomson effect, also known as the Joule-Kelvin effect, describes the temperature change of a fluid when it is forced through a valve or porous plug while keeping it in a thermally insulated environment. This experiment is called a throttling process. This is an important effect widely used in refrigeration and the liquefaction of gases.
This experiment forces high-pressure gas through a throttle valve or a porous plug to a lower-pressure region. The gas expands as it passes through to...
3.8K
Entropy and the Second Law of Thermodynamics01:20

Entropy and the Second Law of Thermodynamics

2.8K
The second law of thermodynamics can be stated quantitatively using the concept of entropy. Entropy is the measure of disorder of the system.
The relation  between entropy and disorder can be illustrated with the example of the phase change of ice to water. In ice, the molecules are located at specific sites giving a solid state, whereas, in a liquid form, these molecules are much freer to move. The molecular arrangement has therefore become more randomized. Although the change in average...
2.8K
Efficiency of The Carnot Cycle01:16

Efficiency of The Carnot Cycle

2.6K
The hypothetical Carnot cycle consists of an ideal gas subjected to two isothermal and two adiabatic processes. Since the internal energy of an ideal gas depends only on its temperature, which is the same before and after the completion of the Carnot cycle, there is no change in its internal energy. Hence, using the first law of thermodynamics, the total heat exchanged by the ideal gas equals the total work done. Thus, we can quantify the efficiency of the Carnot cycle via the heat exchanged...
2.6K
Thermodynamics: Activity Coefficient01:24

Thermodynamics: Activity Coefficient

1.4K
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...
1.4K
Entropy Change in Reversible Processes01:10

Entropy Change in Reversible Processes

2.5K
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.
2.5K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Møller-Plesset and Density-Fixed Adiabatic Connections for a Model Diatomic System at Different Correlation Regimes.

Journal of chemical theory and computation·2023
Same author

Comparing correlation components and approximations in Hartree-Fock and Kohn-Sham theories via an analytical test case study.

The Journal of chemical physics·2022
Same author

Using projection operators with maximum overlap methods to simplify challenging self-consistent field optimization.

Journal of computational chemistry·2021
See all related articles

Related Experiment Video

Updated: Jun 28, 2025

Experimental Methodology for Estimation of Local Heat Fluxes and Burning Rates in Steady Laminar Boundary Layer Diffusion Flames
10:29

Experimental Methodology for Estimation of Local Heat Fluxes and Burning Rates in Steady Laminar Boundary Layer Diffusion Flames

Published on: June 1, 2016

11.8K

Exchange-correlation entropy from the generalized thermal adiabatic connection.

Brittany P Harding1, Zachary Mauri2, Vera W Xie1

  • 1University of California, Merced, 5200 North Lake Road, Merced, California 95343, USA.

The Journal of Chemical Physics
|April 17, 2024
PubMed
Summary

A new generalized thermal adiabatic connection (GTAC) formula was developed to calculate exchange-correlation entropy in warm dense matter. This method enables better simulations of this energetic quantum phase.

More Related Videos

Characterization of Thermal Transport in One-dimensional Solid Materials
05:20

Characterization of Thermal Transport in One-dimensional Solid Materials

Published on: January 26, 2014

17.4K
Non-equilibrium Microwave Plasma for Efficient High Temperature Chemistry
07:17

Non-equilibrium Microwave Plasma for Efficient High Temperature Chemistry

Published on: August 1, 2017

12.6K

Related Experiment Videos

Last Updated: Jun 28, 2025

Experimental Methodology for Estimation of Local Heat Fluxes and Burning Rates in Steady Laminar Boundary Layer Diffusion Flames
10:29

Experimental Methodology for Estimation of Local Heat Fluxes and Burning Rates in Steady Laminar Boundary Layer Diffusion Flames

Published on: June 1, 2016

11.8K
Characterization of Thermal Transport in One-dimensional Solid Materials
05:20

Characterization of Thermal Transport in One-dimensional Solid Materials

Published on: January 26, 2014

17.4K
Non-equilibrium Microwave Plasma for Efficient High Temperature Chemistry
07:17

Non-equilibrium Microwave Plasma for Efficient High Temperature Chemistry

Published on: August 1, 2017

12.6K

Area of Science:

  • Condensed Matter Physics
  • Quantum Mechanics
  • Computational Physics

Background:

  • Warm dense matter (WDM) is an energetic state with strong correlations and quantum effects.
  • Simulating WDM relies on thermal density functional theory (TDFT).
  • Accurate TDFT requires temperature-dependent exchange-correlation approximations.

Purpose of the Study:

  • To introduce a generalized thermal adiabatic connection (GTAC) formula for WDM.
  • To enable extraction of exchange-correlation entropy (SXC) using simulated interaction strength scaling.
  • To provide a new framework for studying WDM properties.

Main Methods:

  • Development of the generalized thermal adiabatic connection (GTAC) formula with a fictitious temperature parameter.
  • Application of simulated interaction strength scaling.
  • Utilizing a Hellmann-Feynman approach to derive SXC from the exchange-correlation potential.

Main Results:

  • The GTAC formula successfully extracts exchange-correlation entropy (SXC).
  • SXC analysis as a function of interaction strength suggests new approximation forms.
  • The GTAC framework facilitates exploration of temperature, density, and interaction strength interplay.

Conclusions:

  • The proposed GTAC formula offers a novel method for calculating SXC in WDM.
  • GTAC provides a versatile framework for developing improved TDFT approximations.
  • This work advances the understanding and simulation of warm dense matter.