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

Predicting Reaction Outcomes02:24

Predicting Reaction Outcomes

8.5K
Kinetics describes the rate and path by which a reaction occurs. In contrast, thermodynamics deals with state functions and describes the properties, behavior, and components of a system. It is not concerned with the path taken by the process and cannot address the rate at which a reaction occurs. Although it does provide information about what can happen during a reaction process, it does not describe the detailed steps of what appears on an atomic or a molecular level. On the other hand,...
8.5K
Entropy Change in Reversible Processes01:10

Entropy Change in Reversible Processes

2.7K
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.
2.7K
The Second Law of Thermodynamics01:14

The Second Law of Thermodynamics

5.4K
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...
5.4K
Molecular Kinetic Energy01:21

Molecular Kinetic Energy

5.2K
The word "gas" comes from the Flemish word meaning "chaos," first used to describe vapors by the chemist J. B. van Helmont. Consider a container filled with gas, with a continuous and random motion of molecules. During collisions, the velocity component parallel to the wall is unchanged, and the component perpendicular to the wall reverses direction but does not change in magnitude. If the molecule’s velocity changes in the x-direction, then its momentum is changed.
5.2K
Fundamental Mathematical Principles in Pharmacokinetics: Rate and Order of Reaction01:15

Fundamental Mathematical Principles in Pharmacokinetics: Rate and Order of Reaction

552
In pharmacokinetics, the rates and order of reactions play a crucial role in understanding how the body processes drugs and help us comprehend drug absorption, distribution, metabolism, and elimination. A critical concept in pharmacokinetics is the rate constant, which quantifies the speed of a reaction. It provides valuable information about the kinetics of drug elimination. The rate constant allows us to determine the rate at which drugs are eliminated from the body.
Pharmacokinetic reactions...
552
Entropy02:39

Entropy

30.6K
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...
30.6K

You might also read

Related Articles

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

Sort by
Same author

Differential conformational expansion of NUP98-HOXA9 oncoprotein from nanosized assemblies to macrophases.

Nature communications·2025
Same author

Understanding and Controlling the Colloidal Stability of CdSe Nanoplatelets by Solvation Force Engineering.

Journal of the American Chemical Society·2025
Same author

Salt-Induced Polymorphs Observed in Colloidal Single Crystals.

Journal of the American Chemical Society·2025
Same author

Liquid-Liquid Phase Separation of the Intrinsically Disordered Domain of the Fused in Sarcoma Protein Results in Substantial Slowing of Hydration Dynamics.

The journal of physical chemistry letters·2023
Same author

The Crucial Role of Solvation Forces in the Steric Stabilization of Nanoplatelets.

Nano letters·2022
Same author

Particle analogs of electrons in colloidal crystals.

Science (New York, N.Y.)·2019

Related Experiment Video

Updated: Aug 16, 2025

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
11:03

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids

Published on: December 4, 2017

8.6K

On kinetics and extreme values in systems with random interactions.

Martin Girard1

  • 1Max Planck Institute for Polymer Research, Ackermannweg 10, Mainz 55128, Germany.

Physical Biology
|December 20, 2022
PubMed
Summary

This study explores particle interactions in complex biological environments, revealing a phase transition where components precipitate below a critical temperature. The transition

Keywords:
biophysicsextreme valuesstatistical mechanics

More Related Videos

Author Spotlight: Evaluation of Protein-Condensate Dynamics in Live Human Cells
06:48

Author Spotlight: Evaluation of Protein-Condensate Dynamics in Live Human Cells

Published on: January 5, 2024

4.0K
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

9.1K

Related Experiment Videos

Last Updated: Aug 16, 2025

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
11:03

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids

Published on: December 4, 2017

8.6K
Author Spotlight: Evaluation of Protein-Condensate Dynamics in Live Human Cells
06:48

Author Spotlight: Evaluation of Protein-Condensate Dynamics in Live Human Cells

Published on: January 5, 2024

4.0K
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

9.1K

Area of Science:

  • Statistical mechanics
  • Computational biology
  • Physical chemistry

Background:

  • Biological environments like the cytoplasm contain numerous molecules, making explicit modeling challenging.
  • Mean-field approximations, while efficient, may oversimplify complex molecular interactions.

Purpose of the Study:

  • To investigate particle systems interacting via random potentials beyond mean-field approximations.
  • To characterize the phase transition and its dependence on interaction distributions.

Main Methods:

  • Analysis of systems with random potentials, moving beyond mean-field assumptions.
  • Application of Bethe approximation above the phase transition temperature.
  • Examination of extreme value statistics and relaxation timescales.

Main Results:

  • A phase transition temperature was identified, below which components precipitate.
  • The transition's nature is non-universal, depending on the interaction distribution.
  • Bethe approximation above transition shows dependence on extreme value statistics.

Conclusions:

  • Systems with random interactions exhibit a non-universal phase transition.
  • Relaxation times can be controlled by adjusting particle neighborhood size.