Jove
Visualize
Contact Us

Related Concept Videos

Entropy02:39

Entropy

33.6K
Salt particles that have dissolved in water never spontaneously come back together in solution to reform solid particles. Moreover, a gas that has expanded in a vacuum remains dispersed and never spontaneously reassembles. The unidirectional nature of these phenomena is the result of a thermodynamic state function called entropy (S). Entropy is the measure of the extent to which the energy is dispersed throughout a system, or in other words, it is proportional to the degree of disorder of a...
33.6K
Entropy01:18

Entropy

3.2K
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...
3.2K
Entropy Change in Reversible Processes01:10

Entropy Change in Reversible Processes

3.0K
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.
3.0K
Entropy and the Second Law of Thermodynamics01:20

Entropy and the Second Law of Thermodynamics

3.9K
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...
3.9K
Third Law of Thermodynamics02:38

Third Law of Thermodynamics

20.9K
A pure, perfectly crystalline solid possessing no kinetic energy (that is, at a temperature of absolute zero, 0 K) may be described by a single microstate, as its purity, perfect crystallinity,and complete lack of motion means there is but one possible location for each identical atom or molecule comprising the crystal (W = 1). According to the Boltzmann equation, the entropy of this system is zero.
20.9K
The Second Law of Thermodynamics01:14

The Second Law of Thermodynamics

6.3K
In the quest to identify a property that may reliably predict the spontaneity of a process, a promising candidate has been identified: entropy. Scientists refer to the measure of randomness or disorder within a system as entropy. High entropy means high disorder and low energy. To better understand entropy, think of a student’s bedroom. If no energy or work were put into it, the room would quickly become messy. It would exist in a very disordered state, one of high entropy. Energy must be...
6.3K

You might also read

Related Articles

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

Sort by
Same author

Temporal Exploration of Chronic Obstructive Pulmonary Disease Phenotypes: Insights from the COPDGene and SPIROMICS Cohorts.

American journal of respiratory and critical care medicine·2024
Same author

Missing data in emergency care: a pitfall in the interpretation of analysis and research based on electronic patient records.

Emergency medicine journal : EMJ·2024
Same author

Domain Adaptation Principal Component Analysis: Base Linear Method for Learning with Out-of-Distribution Data.

Entropy (Basel, Switzerland)·2023
Same author

Corrigendum to: COVID-19 vaccination uptake amongst ethnic minority communities in England: a linked study exploring the drivers of differential vaccination rates.

Journal of public health (Oxford, England)·2022
Same author

A population-based cohort study of obesity, ethnicity and COVID-19 mortality in 12.6 million adults in England.

Nature communications·2022
Same author

COVID-19 vaccination uptake amongst ethnic minority communities in England: a linked study exploring the drivers of differential vaccination rates.

Journal of public health (Oxford, England)·2022
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 Experiment Video

Updated: Nov 27, 2025

Experimental Investigation of Secondary Flow Structures Downstream of a Model Type IV Stent Failure in a 180° Curved Artery Test Section
11:00

Experimental Investigation of Secondary Flow Structures Downstream of a Model Type IV Stent Failure in a 180° Curved Artery Test Section

Published on: July 19, 2016

11.8K

Universal Gorban's Entropies: Geometric Case Study.

Evgeny M Mirkes1,2

  • 1School of Mathematics and Actuarial Science, University of Leicester, Leicester LE1 7HR, UK.

Entropy (Basel, Switzerland)
|December 8, 2020
PubMed
Summary

New universal Lyapunov functions for reaction networks offer insights into chemical kinetics. Their difference from classical thermodynamic functions is most pronounced far from equilibrium.

Keywords:
Lyapunov functionfree entropylevel setpartial equilibrium

More Related Videos

Unraveling Entropic Rate Acceleration Induced by Solvent Dynamics in Membrane Enzymes
09:42

Unraveling Entropic Rate Acceleration Induced by Solvent Dynamics in Membrane Enzymes

Published on: January 16, 2016

9.3K
Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
09:23

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans

Published on: August 16, 2017

8.4K

Related Experiment Videos

Last Updated: Nov 27, 2025

Experimental Investigation of Secondary Flow Structures Downstream of a Model Type IV Stent Failure in a 180° Curved Artery Test Section
11:00

Experimental Investigation of Secondary Flow Structures Downstream of a Model Type IV Stent Failure in a 180° Curved Artery Test Section

Published on: July 19, 2016

11.8K
Unraveling Entropic Rate Acceleration Induced by Solvent Dynamics in Membrane Enzymes
09:42

Unraveling Entropic Rate Acceleration Induced by Solvent Dynamics in Membrane Enzymes

Published on: January 16, 2016

9.3K
Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
09:23

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans

Published on: August 16, 2017

8.4K

Area of Science:

  • Chemical kinetics
  • Theoretical chemistry
  • Non-linear dynamics

Background:

  • A rich family of universal Lyapunov functions for reaction networks was recently presented by A.N. Gorban.
  • These functions utilize partial equilibria and convex envelopes, aiming to explain differences in Lyapunov functions between linear and non-linear systems.
  • Classical thermodynamic Lyapunov functions, like Boltzmann-Gibbs-Shannon entropy, have limitations for non-linear networks.

Purpose of the Study:

  • To review and analyze Gorban's universal Lyapunov functions for chemical reaction networks.
  • To compare these new functions with classical thermodynamic Lyapunov functions.
  • To investigate the behavior of these functions in relation to reaction equilibria and kinetic trajectories.

Main Methods:

  • Review of A.N. Gorban's construction algorithm for universal Lyapunov functions.
  • Comparative analysis of Gorban's functions and classical Lyapunov functions (e.g., Boltzmann-Gibbs-Shannon entropy).
  • Analysis of level sets and dynamics along kinetic trajectories for various chemical reaction mechanisms.

Main Results:

  • Gorban's universal Lyapunov functions were analyzed for linear and non-linear reaction networks.
  • Significant differences between Gorban's functions and classical thermodynamic Lyapunov functions were observed.
  • The divergence between the new and classical functions is most pronounced when systems are far from partial equilibria.

Conclusions:

  • The study highlights the distinct behavior of Gorban's universal Lyapunov functions compared to classical ones.
  • The difference between these Lyapunov functions diminishes as reactions approach equilibrium.
  • Gorban's functions provide a more comprehensive framework for analyzing complex reaction networks, especially under non-equilibrium conditions.