Related Experiment Video
Updated: Oct 27, 2025

Author Spotlight: Characterizing Porous Materials for Aiding the Development of Robust Metal-Organic Frameworks with Adsorption Behavior
Published on: March 8, 2024
Hydrogen storage in MOFs: Machine learning for finding a needle in a haystack
Lawson T Glasby1, Peyman Z Moghadam1
1Department of Chemical and Biological Engineering, The University of Sheffield, Sheffield S1 3JD, UK.
Abstract:
In recent years, machine learning (ML) has grown exponentially within the field of structure property predictions in materials science. In this issue of Patterns, Ahmed and Siegel scrutinize several redeveloped ML techniques for systematic investigations of over 900,000 metal-organic framework (MOF) structures, taken from 19 databases, to discover new, potentially record-breaking, hydrogen-storage materials.
More Related Videos
Related Concept Videos
Hydrogen Bonds
Hydrogen Bonds
Hydrogen Bonds Control the World!
Because hydrogen has very weak electronegativity when it binds with a strongly electronegative atom, such as oxygen or nitrogen, electrons in the bond are unequally shared....
Predicting Molecular Geometry
Metal-Ligand Bonds
In these complexes, transition metals form coordinate covalent bonds, a kind of Lewis acid-base interaction in which both of the electrons in the bond are contributed by a donor (Lewis base) to an electron acceptor (Lewis acid). The Lewis acid in...

