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

Quantum Numbers02:43

Quantum Numbers

52.3K
It is said that the energy of an electron in an atom is quantized; that is, it can be equal only to certain specific values and can jump from one energy level to another but not transition smoothly or stay between these levels.
52.3K
The Quantum-Mechanical Model of an Atom02:45

The Quantum-Mechanical Model of an Atom

59.7K
Shortly after de Broglie published his ideas that the electron in a hydrogen atom could be better thought of as being a circular standing wave instead of a particle moving in quantized circular orbits, Erwin Schrödinger extended de Broglie’s work by deriving what is now known as the Schrödinger equation. When Schrödinger applied his equation to hydrogen-like atoms, he was able to reproduce Bohr’s expression for the energy and, thus, the Rydberg formula governing hydrogen spectra.
59.7K
Chemistry of the Cell02:58

Chemistry of the Cell

48.4K
The cell is chemically composed of water, organic molecules and inorganic ions.
Water
The polarity of the water molecule and its resulting hydrogen bonding makes water a unique substance with special properties that are intimately tied to the processes of life. Life originally evolved in an aqueous environment, and most of an organism’s cellular chemistry and metabolism occur inside the aqueous contents of the cell’s cytoplasm. Special properties of water are its high heat capacity...
48.4K
Chemistry of the Cell02:58

Chemistry of the Cell

9.6K
9.6K
Machines01:19

Machines

581
Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. One example of a machine is the cutting plier, which is used to cut wires by applying forces to its handles. When equal and opposite forces are exerted on the handles of the cutting plier, they cause the cutting edges to come together and apply equal and opposite reaction forces on the wire, which are greater than the applied forces.
A free-body diagram of the...
581
Chemistry of Carbohydrates03:25

Chemistry of Carbohydrates

91.0K
Carbohydrates are an essential part of the diet in humans and animals. Grains, fruits, and vegetables are natural sources of carbohydrates that provide energy to the body, particularly through glucose, a simple sugar that is a component of starch and an ingredient in many staple foods. The stoichiometric formula (CH2O)n, where n is the number of carbons in the molecule represents carbohydrates. In other words, the ratio of carbon to hydrogen to oxygen is 1:2:1 in carbohydrate molecules. This...
91.0K

You might also read

Related Articles

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

Sort by
Same author

Enzyme-Catalyzed Stereoselective C(sp<sup>3</sup>)-S Bond Formation via a Dichotomic Carbene Transfer Mechanism.

Journal of the American Chemical Society·2026
Same author

Origins of the selectivity of late transition metals of Group 9 and Group 10 for oxidative addition of C-H <i>vs.</i> C-Cl bonds.

Chemical science·2026
Same author

Mechanistic Studies of Oxidative Degradation in Diamine-Appended Metal-Organic Frameworks Exhibiting Cooperative CO<sub>2</sub> Capture.

Journal of the American Chemical Society·2025
Same author

Nickel-Catalyzed Branched Hydroalkylation of Alkenes with Diazo Compounds.

Journal of the American Chemical Society·2025
Same author

Beyond Strain Release: Delocalization-Enabled Organic Reactivity.

The Journal of organic chemistry·2024
Same author

Integrated Study on Methane Activation: Exploring Main Group Frustrated Lewis Pairs through Density Functional Theory, Machine Learning, and Machine-Learned Force Fields.

Journal of chemical theory and computation·2024

Related Experiment Video

Updated: Feb 12, 2026

Analyzing Mitochondrial Morphology Through Simulation Supervised Learning
12:06

Analyzing Mitochondrial Morphology Through Simulation Supervised Learning

Published on: March 3, 2023

4.8K

ChemRefine: An Open-Source Automated and Interoperable Platform for Machine Learning and Quantum Chemistry

Ignacio Migliaro1, Markus G S Weiss1,2, Alistair J Sterling1

  • 1Department of Chemistry and Biochemistry, The University of Texas at Dallas, 800 W Campbell Road, Richardson, Texas 75080, United States.

Journal of Chemical Theory and Computation
|February 10, 2026
PubMed
Summary

ChemRefine integrates machine-learned interatomic potentials (MLIPs) into computational chemistry workflows, accelerating simulations. A custom large language model, ChemRefineGPT, simplifies workflow creation using natural language descriptions.

More Related Videos

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
09:34

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data

Published on: September 25, 2021

4.5K
Asthma Detection Research Based on Voice Signal Processing and Machine Learning
04:04

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Published on: July 22, 2025

1.0K

Related Experiment Videos

Last Updated: Feb 12, 2026

Analyzing Mitochondrial Morphology Through Simulation Supervised Learning
12:06

Analyzing Mitochondrial Morphology Through Simulation Supervised Learning

Published on: March 3, 2023

4.8K
A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
09:34

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data

Published on: September 25, 2021

4.5K
Asthma Detection Research Based on Voice Signal Processing and Machine Learning
04:04

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Published on: July 22, 2025

1.0K

Area of Science:

  • Computational Chemistry
  • Machine Learning
  • Scientific Software Development

Background:

  • Machine learning is increasingly used in computational chemistry to speed up tasks and improve predictions.
  • Integrating new machine-learned interatomic potentials (MLIPs) into existing quantum mechanics (QM) workflows presents a significant challenge.

Purpose of the Study:

  • Introduce ChemRefine, a modular platform for automating computational chemistry workflows.
  • Enable seamless integration of advanced MLIPs into complex and high-throughput computational tasks.
  • Simplify workflow creation using natural language processing.

Main Methods:

  • Developed ChemRefine, a modular automated computational chemistry platform.
  • Integrated MLIPs for automated training, fine-tuning, and deployment within workflows.
  • Utilized ChemRefineGPT, a custom large language model, for generating input and configuration files from natural language descriptions.

Main Results:

  • Successfully road-tested ChemRefine on diverse tasks: host-guest binding, property prediction, conformational sampling, and transition state finding.
  • Demonstrated accelerated simulations with maintained prediction accuracy using MLIPs.
  • Condensed multiple computational tasks into single, reproducible workflows.

Conclusions:

  • ChemRefine provides a robust solution for integrating next-generation MLIPs into computational chemistry.
  • The platform enhances efficiency and reproducibility for various scientific applications.
  • ChemRefineGPT significantly lowers the barrier to entry for utilizing complex computational workflows.