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

Standard Enthalpy of Formation

Standard Enthalpy of Formation

Enthalpy changes are typically tabulated for reactions in which both the reactants and products are at the same conditions. A standard state is a commonly accepted set of conditions used as a reference point for the determination of properties under other different conditions. For chemists, the IUPAC standard state refers to materials under a pressure of 1 bar and solutions at 1 M and does not specify a temperature. Many thermochemical tables list values with a standard state of 1 atm. Because...

Enthalpies of Reaction

Enthalpies of Reaction

Hess’s law can be used to determine the enthalpy change of any reaction if the corresponding enthalpies of formation of the reactants and products are available. The main reaction may be divided into stepwise reactions : (i) decompositions of the reactants into their component elements, for which the enthalpy changes are proportional to the negative of the enthalpies of formation of the reactants, −ΔHf°(reactants), followed by (ii) re-combinations of the elements (obtained...

Thermodynamic Potentials

Thermodynamic Potentials

Thermodynamic potentials are state functions that are extremely useful in analyzing a thermodynamic system. They have dimensions of energy. The four important thermodynamic potentials are internal energy, enthalpy, Helmholtz free energy, and Gibbs free energy. These thermodynamic potentials can be expressed using two of the following variables: pressure, volume, temperature, and entropy. These two variables are expressed as the rate of change of the thermodynamic potential with respect to other...

Thermochemical Equations

Thermochemical Equations

For a chemical reaction (the system) carried out at constant pressure – with the only work done caused by expansion or contraction – the enthalpy of reaction (also called the heat of reaction, ΔHrxn) is equal to the heat exchanged with the surroundings (qp).

Maxwell's Thermodynamic Relations

Maxwell's Thermodynamic Relations

Maxwell's thermodynamic relations are very useful in solving problems in thermodynamics. Each of Maxwell's relations relates a partial differential between quantities that can be hard to measure experimentally to a partial differential between quantities that can be easily measured. These relations are a set of equations derivable from the symmetry of the second derivatives and the thermodynamic potentials.
All thermodynamic potentials are exact differentials. Therefore, their second-order...

Hess's Law

Hess's Law

There are two ways to determine the amount of heat involved in a chemical change: measure it experimentally, or calculate it from other experimentally determined enthalpy changes. Some reactions are difficult, if not impossible, to investigate and make accurate measurements for experimentally. And even when a reaction is not hard to perform or measure, it is convenient to be able to determine the heat involved in a reaction without having to perform an experiment.

You might also read

Related Articles

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

Sort by

Same author

Leveraging Mechanistic Insights into Stereoretentive ROMP for Precision Synthesis of Poly(<i>p</i>-phenylene vinylene)s.

Journal of the American Chemical Society·2026

Same author

Pathophysiological roles of monocytes and macrophages in cancer.

Nature reviews. Immunology·2026

Same author

Accurate prediction of tensorial spectra using equivariant graph neural network.

Nature communications·2026

Same author

Detailed kinetic model for combustion of NH<sub>3</sub>/H<sub>2</sub> blends.

Physical chemistry chemical physics : PCCP·2026

Same author

Two-Phase Distributed Genetic-Based Algorithm for Time-Aware Shaper Scheduling in Industrial Sensor Networks.

Sensors (Basel, Switzerland)·2026

Same author

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials.

ACS nano·2025

Search research articles

Related Experiment Video

Updated: Aug 26, 2025

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Published on: April 8, 2020

Deep Learning-Based Increment Theory for Formation Enthalpy Predictions.

Lung-Yi Chen¹, Ting-Wei Hsu¹, Tsai-Chen Hsiung¹

¹Department of Chemical Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei10617, Taiwan.

The Journal of Physical Chemistry. A

|October 11, 2022

Summary

A new graph-based deep learning model accurately predicts molecular formation enthalpy for large molecules. This machine learning approach overcomes data limitations, offering a significant improvement over traditional methods for chemical thermodynamics.

More Related Videos

Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

Published on: September 17, 2021

Protocol for Measuring the Thermal Properties of a Supercooled Synthetic Sand-water-gas-methane Hydrate Sample

Protocol for Measuring the Thermal Properties of a Supercooled Synthetic Sand-water-gas-methane Hydrate Sample

Published on: March 21, 2016

Related Experiment Videos

Last Updated: Aug 26, 2025

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Published on: April 8, 2020

Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

Published on: September 17, 2021

Protocol for Measuring the Thermal Properties of a Supercooled Synthetic Sand-water-gas-methane Hydrate Sample

Protocol for Measuring the Thermal Properties of a Supercooled Synthetic Sand-water-gas-methane Hydrate Sample

Published on: March 21, 2016

Area of Science:

Computational Chemistry
Machine Learning
Chemical Thermodynamics

Background:

Accurate prediction of molecular thermochemistry, like formation enthalpy, is crucial for reaction thermodynamics and kinetic modeling.
Existing machine learning methods struggle with large, complex molecules due to limited training data.

Purpose of the Study:

To develop a novel graph-based deep learning approach for predicting molecular formation enthalpy.
To enable accurate predictions for large and complex molecules beyond the training dataset.

Main Methods:

A graph-based deep learning architecture was employed.
The model learns atomic enthalpy contributions within their local chemical environments.
The approach incorporates the influence of overall molecular structure, inspired by increment theory.

Main Results:

The model successfully predicts formation enthalpy for molecules up to 42 heavy atoms.
Achieved a mean absolute error of 2 kcal/mol, outperforming conventional increment theory by over 50%.
Demonstrated generalizability to larger, unseen molecular structures.

Conclusions:

The graph-based deep learning method offers a powerful and generalizable tool for predicting molecular formation enthalpy.
This approach significantly advances the prediction of thermochemical properties for large molecules.
Potential applications include rapid property prediction for molecules challenging for experimental or ab initio methods.