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

The Entropy as a State Function01:14

The Entropy as a State Function

Consider an arbitrary process that moves between two specific states (A and B) in a cyclic manner. This process is reversible and broken down into smaller parts that each follow a Carnot cycle. A Carnot cycle has two isothermal (constant temperature) processes. During these processes, the ratio of the amount of heat transferred to their respective temperature remains constant. The other two processes in the Carnot cycle are also reversible but adiabatic, which means they occur without any heat...
Second Law of Thermodynamics02:49

Second Law of Thermodynamics

In the quest to identify a property that may reliably predict the spontaneity of a process, a promising candidate has been identified: entropy. Processes that involve an increase in entropy of the system (ΔS > 0) are very often spontaneous; however, examples to the contrary are plentiful. By expanding consideration of entropy changes to include the surroundings, a significant conclusion regarding the relation between this property and spontaneity may be reached. In thermodynamic models, the...
Second Law of Thermodynamics00:53

Second Law of Thermodynamics

The Second Law of Thermodynamics states that entropy, or the amount of disorder in a system, increases each time energy is transferred or transformed. Each energy transfer results in a certain amount of energy that is lost—usually in the form of heat—that increases the disorder of the surroundings. This can also be demonstrated in a classic food web. Herbivores harvest chemical energy from plants and release heat and carbon dioxide into the environment. Carnivores harvest the chemical energy...
Path Between Thermodynamics States01:21

Path Between Thermodynamics States

Consider the two thermodynamic processes involving an ideal gas that are represented by paths AC and ABC in Figure 1:
Thermodynamic Processes01:25

Thermodynamic Processes

A thermodynamic process is a path through a sequence of states that takes a system from an initial state to a final state. In a cyclic process, the system returns to its initial state, so the changes in state properties and state functions (ΔT, Δp, ΔV, ΔU, ΔH) over one complete cycle are zero. However, heat and work transfers can still occur during the cycle, and the net heat and net work over the cycle need not be zero.A reversible process occurs when the system is infinitesimally close to...
Gibbs Free Energy02:39

Gibbs Free Energy

One of the challenges of using the second law of thermodynamics to determine if a process is spontaneous is that it requires measurements of the entropy change for the system and the entropy change for the surroundings. An alternative approach involving a new thermodynamic property defined in terms of system properties only was introduced in the late nineteenth century by American mathematician Josiah Willard Gibbs. This new property is called the Gibbs free energy (G) (or simply the free...

You might also read

Related Articles

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

Sort by
Same author

Out-of-equilibrium spinodal-like scaling behaviors at the thermal first-order transitions of three-dimensional q-state Potts models.

Physical review. E·2026
Same author

Out-of-equilibrium spinodal-like scaling behaviors across the magnetic first-order transitions of two-dimensional and three-dimensional Ising systems.

Physical review. E·2026
Same author

A Novel Municipal-Level Approach to Uncover the Hidden Burden of Hepatitis C: A Replicable Model for National Elimination Strategies.

Viruses·2025
Same author

High temperature melting of dense molecular hydrogen from machine-learning interatomic potentials trained on quantum Monte Carlo.

The Journal of chemical physics·2025
Same author

Safety of Sofosbuvir-Based Direct-Acting Antivirals for Hepatitis C Virus Infection and Direct Oral Anticoagulant Co-Administration.

Journal of clinical medicine·2024
Same author

Strong-coupling critical behavior in three-dimensional lattice Abelian gauge models with charged N-component scalar fields and SO(N) symmetry.

Physical review. E·2024
Same journal

DNA conformation determines the size of DNA-histone H1 nanoscale clusters.

The Journal of chemical physics·2026
Same journal

Confinement-controlled phase behavior of charged colloids under gravity.

The Journal of chemical physics·2026
Same journal

Dissociation line of tetrahydrofuran hydrates from NPH molecular dynamics simulations.

The Journal of chemical physics·2026
Same journal

Development of a magnetic interatomic potential for cubic antiferromagnets: The case of NiO.

The Journal of chemical physics·2026
Same journal

Simulations of solvent effects on excited state dynamics of p-DAPA, a red single benzene-based fluorophore.

The Journal of chemical physics·2026
Same journal

Rotational excitation of thioformaldehyde (H2CS) in collisions with molecular hydrogen.

The Journal of chemical physics·2026
See all related articles

Related Experiment Video

Updated: May 10, 2026

Thermochemical Studies of Ni(II) and Zn(II) Ternary Complexes Using Ion Mobility-Mass Spectrometry
16:11

Thermochemical Studies of Ni(II) and Zn(II) Ternary Complexes Using Ion Mobility-Mass Spectrometry

Published on: June 8, 2022

Predicting the thermodynamics by using state-dependent interactions.

Giuseppe D'Adamo1, Andrea Pelissetto, Carlo Pierleoni

  • 1Dipartimento di Scienze Fisiche e Chimiche, Università dell'Aquila, V. Vetoio 10, Loc. Coppito, I-67100 L'Aquila, Italy. giuseppe.dadamo@aquila.infn.it

The Journal of Chemical Physics
|June 28, 2013
PubMed
Summary
This summary is machine-generated.

Coarse-grained models approximate system properties like pressure and chemical potential. Their accuracy depends on the derivation ensemble, requiring careful application for predicting phase behavior.

More Related Videos

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

Submillisecond Conformational Changes in Proteins Resolved by Photothermal Beam Deflection
10:02

Submillisecond Conformational Changes in Proteins Resolved by Photothermal Beam Deflection

Published on: February 18, 2014

Related Experiment Videos

Last Updated: May 10, 2026

Thermochemical Studies of Ni(II) and Zn(II) Ternary Complexes Using Ion Mobility-Mass Spectrometry
16:11

Thermochemical Studies of Ni(II) and Zn(II) Ternary Complexes Using Ion Mobility-Mass Spectrometry

Published on: June 8, 2022

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

Submillisecond Conformational Changes in Proteins Resolved by Photothermal Beam Deflection
10:02

Submillisecond Conformational Changes in Proteins Resolved by Photothermal Beam Deflection

Published on: February 18, 2014

Area of Science:

  • Computational physics
  • Statistical mechanics
  • Materials science

Background:

  • Coarse-graining simplifies complex systems by reducing degrees of freedom.
  • Structure-based coarse-graining aims to reproduce system distribution functions.
  • Accurate thermodynamic properties are crucial for coarse-grained model validation.

Purpose of the Study:

  • To analyze the accuracy of standard thermodynamic expressions in structure-based coarse-grained models.
  • To investigate the impact of ensemble choice on derived potentials.
  • To evaluate approximations for pressure and chemical potential in specific systems.

Main Methods:

  • Applying standard pressure and chemical potential formulas to coarse-grained models.
  • Comparing model predictions with underlying system properties.
  • Analyzing density-dependent interactions and state-dependent potentials.
  • Examining low-density systems and polymer solutions under good-solvent conditions.

Main Results:

  • Standard expressions yield approximate, not exact, pressure and chemical potential for coarse-grained models.
  • Approximations were evaluated for generic low-density systems and polymer solutions.
  • State-dependent potentials are ensemble-dependent, influencing their predictive power.

Conclusions:

  • Structure-based coarse-grained models provide approximations for thermodynamic properties.
  • The choice of ensemble during potential derivation affects model behavior.
  • Caution is needed when using canonical ensemble potentials for phase line predictions in other ensembles.