Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Free Energy

Free Energy

Free energy—abbreviated as G for the scientist Gibbs who discovered it—is a measurement of useful energy that can be extracted from a reaction to do work. It is the energy in a chemical reaction that is available after entropy is accounted for. Reactions that take in energy are considered endergonic and reactions that release energy are exergonic. Plants carry out endergonic reactions by taking in sunlight and carbon dioxide to produce glucose and oxygen. Animals, in turn, break down the...

Free Energy Changes for Nonstandard States

Free Energy Changes for Nonstandard States

The free energy change for a process taking place with reactants and products present under nonstandard conditions (pressures other than 1 bar; concentrations other than 1 M) is related to the standard free energy change according to this equation:

Free Energy and Equilibrium

Free Energy and Equilibrium

The free energy change for a process may be viewed as a measure of its driving force. A negative value for ΔG represents a driving force for the process in the forward direction, while a positive value represents a driving force for the process in the reverse direction. When ΔGrxn is zero, the forward and reverse driving forces are equal, and the process occurs in both directions at the same rate (the system is at equilibrium).
Recall that Q is the numerical value of the mass action expression...

Free Energy and Equilibrium

Free Energy and Equilibrium

The free energy change for a process may be viewed as a measure of its driving force. A negative value for ΔG represents a driving force for the process in the forward direction, while a positive value represents a driving force for the process in the reverse direction. When ΔG is zero, the forward and reverse driving forces are equal, and the process occurs in both directions at the same rate (the system is at equilibrium).
The reaction quotient, Q, is a convenient measure of the status of an...

An Introduction to Free Energy

An Introduction to Free Energy

How can we compare the energy that releases from one reaction to that of another reaction? We use a measurement of free energy to quantitate these energy transfers. Scientists call this free energy Gibbs free energy (abbreviated with the letter G) after Josiah Willard Gibbs, the scientist who developed the measurement. According to the second law of thermodynamics, all energy transfers involve losing some energy in an unusable form such as heat, resulting in entropy. Gibbs free energy...

Energy to Drive Translocation

Energy to Drive Translocation

Mitochondrial protein import is powered by two distinct energy sources: ATP hydrolysis and electrochemical potential across the inner membrane. Newly synthesized precursors are bound by cytosolic chaperones of the Hsp70 family, which guide them to the import receptors on the mitochondrial surface. Utilizing the energy of ATP hydrolysis, Hsp70 chaperones transfer these precursors to the TOM receptors on the mitochondrial outer membrane.
Generally, polypeptides are unfolded by two distinct...

You might also read

Related Articles

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

Sort by

Same author

A centrin-Sfi1 myoneme fishnet powers ultrafast calcium-triggered contraction in the giant ciliate <i>Spirostomum ambiguum</i>.

Proceedings of the National Academy of Sciences of the United States of America·2026

Same author

Unifying theories in high-dimensional biophysics: approaches, challenges and opportunities.

NPJ systems biology and applications·2026

Same author

Light-Induced Ordered Pattern Formation in 2D Copper Halide Perovskites.

Nano letters·2026

Same author

Non-equilibrium active noise enhances generative memory in diffusion models.

Research square·2026

Same author

Trainable computation in molecular networks.

bioRxiv : the preprint server for biology·2026

Same author

Neuromodulation-inspired gated associative memory networks: extended memory retrieval and emergent multistability.

ArXiv·2025

Same journal

Revisiting crossed-correlated baths in open quantum systems simulated by HEOM or T-TEDOPA.

The Journal of chemical physics·2026

Same journal

Vesicle size and membrane composition control monomer transfer pathways in multicomponent lipid vesicles.

The Journal of chemical physics·2026

Same journal

Polaron-mediated exciton dynamics of P(NDI2OD-T2) unveiled by transient absorption spectroscopy under electrochemical conditions.

The Journal of chemical physics·2026

Same journal

Green-Kubo relation in a mesoscale odd fluid model.

The Journal of chemical physics·2026

Same journal

Nitrogenation of microscopic MoS2 surfaces by oxidation scanning probe lithography.

The Journal of chemical physics·2026

Same journal

Molecular structure, binding, and disorder in TDBC-Ag plexcitonic assemblies.

The Journal of chemical physics·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jun 4, 2026

Rapid in-silico Battery Electrolyte Electrochemical Reaction Generation using 3T-VASP Multi-Scale Energy Minimization

Rapid in-silico Battery Electrolyte Electrochemical Reaction Generation using 3T-VASP Multi-Scale Energy Minimization

Published on: August 22, 2025

Escorted free energy simulations.

Suriyanarayanan Vaikuntanathan¹, Christopher Jarzynski

¹Chemical Physics Program, Institute for Physical Science and Technology, University of Maryland, College Park, Maryland 20742, USA. svaikunt@umd.edu

The Journal of Chemical Physics

|February 10, 2011

Summary

This summary is machine-generated.

This study introduces a novel method to enhance free energy calculations in nonequilibrium simulations by minimizing energy dissipation. The approach uses "escorted" trajectories to improve the efficiency of free energy estimates.

More Related Videos

Deciphering the Structural Effects of Activating EGFR Somatic Mutations with Molecular Dynamics Simulation

Deciphering the Structural Effects of Activating EGFR Somatic Mutations with Molecular Dynamics Simulation

Published on: May 20, 2020

Exploring Caspase Mutations and Post-Translational Modification by Molecular Modeling Approaches

Exploring Caspase Mutations and Post-Translational Modification by Molecular Modeling Approaches

Published on: October 13, 2022

Related Experiment Videos

Last Updated: Jun 4, 2026

Rapid in-silico Battery Electrolyte Electrochemical Reaction Generation using 3T-VASP Multi-Scale Energy Minimization

Rapid in-silico Battery Electrolyte Electrochemical Reaction Generation using 3T-VASP Multi-Scale Energy Minimization

Published on: August 22, 2025

Deciphering the Structural Effects of Activating EGFR Somatic Mutations with Molecular Dynamics Simulation

Deciphering the Structural Effects of Activating EGFR Somatic Mutations with Molecular Dynamics Simulation

Published on: May 20, 2020

Exploring Caspase Mutations and Post-Translational Modification by Molecular Modeling Approaches

Exploring Caspase Mutations and Post-Translational Modification by Molecular Modeling Approaches

Published on: October 13, 2022

Area of Science:

Computational physics
Statistical mechanics
Chemical physics

Background:

Estimating free energy differences is crucial in molecular simulations.
Nonequilibrium methods can be inefficient due to significant energy dissipation.
Existing targeted free energy perturbation methods have limitations.

Purpose of the Study:

To develop a strategy for improving the efficiency of free energy estimates in nonequilibrium simulations.
To reduce energy dissipation during simulations.
To generalize existing free energy calculation methods.

Main Methods:

A novel strategy involving artificial, "escorted" trajectories is proposed.
The system's evolution is coupled to external work parameter updates.
This approach generalizes the targeted free energy perturbation method.

Main Results:

A generalized fluctuation theorem for escorted trajectories was derived.
New estimators for free energy differences (ΔF) were developed based on these trajectories.
The method's effectiveness was demonstrated on model systems.

Conclusions:

The proposed strategy effectively improves free energy estimates by reducing dissipation.
Escorted trajectories offer a promising avenue for more efficient nonequilibrium simulations.
This work provides a generalized framework for free energy calculations.