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

Analyte Adsorption and Distribution01:09

Analyte Adsorption and Distribution

611
In certain chromatographic separations, solutes transfer between the mobile phase and the stationary phase via sorption, which typically refers to the process of adsorption. For many chromatographic systems, the sorption process often depends on the polarity of the compounds—an expression of the overall dipole moment within the molecule. During the separation process, there is competition between the solute and solvent for adsorption to the stationary phase. Highly polar compounds and...
611
Atomic Force Microscopy01:08

Atomic Force Microscopy

3.3K
Atomic force microscopy (AFM) is a type of scanning probe microscopy that can analyze topographic details of various specimens like ceramics, glass, polymers, and biological samples. AFM offers over 1000 times more resolution than the optical imaging system. Images generated from AFM are three-dimensional surface profiles, offering an advantage over the flat, two-dimensional images from other imaging techniques.
The AFM Probe
The probe is regarded as the heart of any AFM setup and comprises the...
3.3K
Atomic Absorption Spectroscopy: Atomization Methods01:25

Atomic Absorption Spectroscopy: Atomization Methods

381
Atomic Absorption Spectroscopy (AAS) atomizes samples through flame atomization or electrothermal atomization. Flame atomization typically involves a nebulizer and spray chamber assembly to combine the sample with a fuel–oxidant mixture, creating a fine aerosol mist that enters a burner. Typically, the fuel and oxidant are combined in an approximately stoichiometric ratio. However, for atoms that are easily oxidized, a fuel-rich mixture may be more advantageous. Only about 5% of the...
381
Molecular Models02:00

Molecular Models

38.0K
Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
38.0K
Atomic Absorption Spectroscopy: Overview01:27

Atomic Absorption Spectroscopy: Overview

1.5K
Atomic absorption spectroscopy (AAS) is a technique used to analyze elements by measuring electromagnetic radiation (EMR) absorbed by atoms, which causes them to transition to a higher-energy orbit. The most crucial step in AAS is atomization, where the analyte is converted into gas-phase atoms, typically through a flame or furnace. Some of these atoms become thermally excited in the flame, while most remain in the ground state.
When irradiated by EMR of a particular wavelength, these...
1.5K
Predicting Molecular Geometry02:27

Predicting Molecular Geometry

34.1K
VSEPR Theory for Determination of Electron Pair Geometries
34.1K

You might also read

Related Articles

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

Sort by
Same author

Determination of Trichomonas vaginalis, certain bacterial and fungal positivity, and risk factors in female patients with urinary and genital complaints.

BMC infectious diseases·2026
Same author

Design and Synthesis of a High-Performance Copper(II) Metal-Organic Framework Featuring Large Surface Area and Enhanced Methane Adsorption Capacity from a Thiophene-Functionalized Diisophthalic Acid Ligand.

Inorganic chemistry·2026
Same author

ReDD-COFFEE under the Lens: Revealing Adsorption and Separation Performances of Hypothetical COFs Using Molecular Simulations and Machine Learning.

Industrial & engineering chemistry research·2026
Same author

Transforming MOF Modeling with Machine-Learned Potentials: Progress and Perspectives.

Journal of chemical information and modeling·2026
Same author

Young plasma transfer enhances antioxidant defense and preserves structural integrity in aged lung tissue.

The journals of gerontology. Series A, Biological sciences and medical sciences·2026
Same author

Molecular Modeling-Based Machine Learning for Accurate Prediction of Gas Diffusivity and Permeability in Metal-Organic Frameworks.

ACS materials Au·2026

Related Experiment Video

Updated: Jun 9, 2025

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
10:52

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

Published on: April 12, 2019

12.7K

Understanding CO adsorption in MOFs combining atomic simulations and machine learning.

Goktug Ercakir1, Gokhan Onder Aksu1, Seda Keskin2

  • 1Department of Chemical and Biological Engineering, Koç University, Rumelifeneri Yolu, Sariyer, 34450, Istanbul, Turkey.

Scientific Reports
|October 22, 2024
PubMed
Summary

This study presents a computational method using molecular simulations and machine learning to predict carbon dioxide (CO) adsorption in metal-organic frameworks (MOFs). The approach efficiently screens thousands of MOFs for optimal CO capture materials.

Keywords:
AdsorptionCarbon monoxide (CO)Machine learningMetal–organic framework (MOF)Molecular simulation

More Related Videos

Investigating Single Molecule Adhesion by Atomic Force Spectroscopy
09:48

Investigating Single Molecule Adhesion by Atomic Force Spectroscopy

Published on: February 27, 2015

10.3K
In situ FTIR Spectroscopy as a Tool for Investigation of Gas/Solid Interaction: Water-Enhanced CO2 Adsorption in UiO-66 Metal-Organic Framework
11:38

In situ FTIR Spectroscopy as a Tool for Investigation of Gas/Solid Interaction: Water-Enhanced CO2 Adsorption in UiO-66 Metal-Organic Framework

Published on: February 1, 2020

15.8K

Related Experiment Videos

Last Updated: Jun 9, 2025

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
10:52

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

Published on: April 12, 2019

12.7K
Investigating Single Molecule Adhesion by Atomic Force Spectroscopy
09:48

Investigating Single Molecule Adhesion by Atomic Force Spectroscopy

Published on: February 27, 2015

10.3K
In situ FTIR Spectroscopy as a Tool for Investigation of Gas/Solid Interaction: Water-Enhanced CO2 Adsorption in UiO-66 Metal-Organic Framework
11:38

In situ FTIR Spectroscopy as a Tool for Investigation of Gas/Solid Interaction: Water-Enhanced CO2 Adsorption in UiO-66 Metal-Organic Framework

Published on: February 1, 2020

15.8K

Area of Science:

  • Materials Science
  • Computational Chemistry
  • Chemical Engineering

Background:

  • Metal-organic frameworks (MOFs) show promise for carbon dioxide (CO) capture.
  • Accurate prediction of CO adsorption capacities is crucial for designing effective MOFs.
  • Experimental and traditional simulation methods are often time-consuming and resource-intensive.

Purpose of the Study:

  • To develop and validate a computational framework combining molecular simulations and machine learning (ML) for assessing CO adsorption in MOFs.
  • To predict the CO adsorption capacities of a large dataset of synthesized and hypothetical MOFs (hMOFs).
  • To identify key MOF features influencing CO uptake at different pressures.

Main Methods:

  • Feature extraction (structural, chemical, energy-based) from MOFs.
  • Molecular simulations to compute CO adsorption in synthesized MOFs.
  • Training ML models using simulation data to predict CO adsorption in hMOFs.

Main Results:

  • CO uptakes ranged from 0.02-2.28 mol/kg for synthesized MOFs and 0.45-3.06 mol/kg for hMOFs at 1 bar, 298 K.
  • Henry's constant dominated CO uptake at low pressures (0.1-1 bar), while surface area and porosity were key at high pressure (10 bar).
  • MOFs with narrow pores (4.4-7.3 Å), aromatic linkers, carboxylic acid groups, and specific metal nodes (Co, Zn, Ni) showed high CO uptake.

Conclusions:

  • The integrated simulation-ML approach provides a robust and efficient alternative to traditional methods for MOF screening.
  • This study evaluated approximately 100,000 MOFs, representing the most extensive dataset for CO capture assessment to date.
  • The findings guide the rational design of MOFs with enhanced CO adsorption properties for carbon capture applications.