Jove
Visualize
Contact Us

Related Concept Videos

IR Spectroscopy: Hooke's Law Approximation of Molecular Vibration01:16

IR Spectroscopy: Hooke's Law Approximation of Molecular Vibration

2.0K
A covalently bonded heteronuclear diatomic molecule can be modeled as two vibrating masses connected by a spring. The vibrational frequency of the bond can be expressed using an equation derived from Hooke's law, which describes how the force applied to stretch or compress a spring is proportional to the displacement of the spring. In this case, the atoms behave like masses, and the bond acts like a spring.
According to Hooke's law, the vibrational frequency is directly proportional to...
2.0K
¹H NMR of Conformationally Flexible Molecules: Temporal Resolution00:52

¹H NMR of Conformationally Flexible Molecules: Temporal Resolution

958
At room temperature, the chair conformer of cyclohexane undergoes rapid ring flipping between two equivalent chair conformers at a rate of approximately 105 times per second. These two chair conformers are in equilibrium. The rapid ring flipping results in the interconversion of the axial proton to an equatorial proton and an equatorial to the axial proton. Such interconversions are too rapid and cannot be detected on the NMR timescale. Hence, the NMR spectrometer cannot distinguish between the...
958
IR Spectroscopy: Molecular Vibration Overview01:24

IR Spectroscopy: Molecular Vibration Overview

3.4K
When Infrared (IR) radiation passes through a covalently bonded molecule, the bonds transition from lower to higher vibrational levels. The fundamental vibrational motions that result in infrared absorption can be classified as stretching or bending vibrations.
Stretching vibrations are vibrational motions that occur along the bond line, changing the bond length or distance between two bonded atoms. They are further distinguished as symmetric or asymmetric. In symmetric stretching, the...
3.4K
¹H NMR of Conformationally Flexible Molecules: Variable-Temperature NMR01:15

¹H NMR of Conformationally Flexible Molecules: Variable-Temperature NMR

1.2K
The axial and equatorial protons in cyclohexane can be distinguished by performing a variable-temperature NMR experiment. In this process, except for one proton, the remaining eleven protons are replaced by deuterium. The deuterium substitution avoids the possible peak splitting caused by the spin-spin coupling between the adjacent protons. The remaining proton flips between the axial and equatorial positions.
1.2K
UV–Vis Spectroscopy: Woodward–Fieser Rules01:29

UV–Vis Spectroscopy: Woodward–Fieser Rules

26.4K
UV–Visible absorption spectra of conjugated dienes arise from the lowest energy π → π* transitions. The light-absorbing part of the molecule is called the chromophore, and the substituents directly attached to the chromophore are called auxochromes. A strong correlation exists between the absorption maxima, λmax, and the structure of a conjugated π system. The Woodward–Fieser rules predict the value of λmax for a given...
26.4K
IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations01:08

IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations

1.3K
Identical bonds within a polyatomic group can stretch symmetrically (in-phase) or asymmetrically (out-of-phase). Similar to hydrogen bonding, these vibrations also influence the shape of the IR peak. Generally, asymmetric stretching frequencies are higher than symmetric stretching frequencies. For example, primary amines exhibit two distinct IR peaks between 3300–3500 cm−1 corresponding to the symmetric and asymmetric N-H stretching, while secondary amines exhibit a single...
1.3K

You might also read

Related Articles

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

Sort by
Same author

Absolute quantification of enantiomeric purity of sorted carbon nanotubes by correlating hyperspectral fluorescence microscopy with ensemble chiroptical spectroscopy.

Nature communications·2026
Same author

Toy Models Reveal Intrinsic Biases in NICS: Insights to Verify NICS Interpretations.

Journal of computational chemistry·2026
Same author

The role of the parameter landscape in Hartree-Fock quantum computing benchmarks.

The Journal of chemical physics·2026
Same author

MolAgent: Biomolecular Property Estimation in the Agentic Era.

Journal of chemical information and modeling·2025
Same author

Asymmetric Hydrogenation of Triazolo[1,5-<i>a</i>]-, Imidazo[1,2-<i>a</i>]-, and Pyrazolo[1,5-<i>a</i>]pyridines.

Organic letters·2025
Same author

Spin-generator coordinate method for electronic structure.

The Journal of chemical physics·2025
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 Experiment Video

Updated: Oct 20, 2025

Coulomb Explosion Imaging as a Tool to Distinguish Between Stereoisomers
08:51

Coulomb Explosion Imaging as a Tool to Distinguish Between Stereoisomers

Published on: August 18, 2017

10.5K

Exploring machine learning methods for absolute configuration determination with vibrational circular dichroism.

Tom Vermeyen1,2, Jure Brence3,4, Robin Van Echelpoel1

  • 1Department of Chemistry, University of Antwerp, Groenenborgerlaan 171, B-2020 Antwerp, Belgium. wouter.herrebout@uantwerpen.be.

Physical Chemistry Chemical Physics : PCCP
|September 15, 2021
PubMed
Summary

Supervised Machine Learning (ML) methods, specifically Random Forest and Feedforward Neural Networks, accurately determine a compound's Absolute Configuration (AC) from Vibrational Circular Dichroism (VCD) spectra. Optimizing spectral sampling reduces computational costs without sacrificing prediction accuracy.

More Related Videos

Vibrational Spectra of a N719-Chromophore/Titania Interface from Empirical-Potential Molecular-Dynamics Simulation, Solvated by a Room Temperature Ionic Liquid
08:54

Vibrational Spectra of a N719-Chromophore/Titania Interface from Empirical-Potential Molecular-Dynamics Simulation, Solvated by a Room Temperature Ionic Liquid

Published on: January 25, 2020

5.8K
CD Spectroscopy to Study DNA-Protein Interactions
06:48

CD Spectroscopy to Study DNA-Protein Interactions

Published on: February 10, 2022

7.1K

Related Experiment Videos

Last Updated: Oct 20, 2025

Coulomb Explosion Imaging as a Tool to Distinguish Between Stereoisomers
08:51

Coulomb Explosion Imaging as a Tool to Distinguish Between Stereoisomers

Published on: August 18, 2017

10.5K
Vibrational Spectra of a N719-Chromophore/Titania Interface from Empirical-Potential Molecular-Dynamics Simulation, Solvated by a Room Temperature Ionic Liquid
08:54

Vibrational Spectra of a N719-Chromophore/Titania Interface from Empirical-Potential Molecular-Dynamics Simulation, Solvated by a Room Temperature Ionic Liquid

Published on: January 25, 2020

5.8K
CD Spectroscopy to Study DNA-Protein Interactions
06:48

CD Spectroscopy to Study DNA-Protein Interactions

Published on: February 10, 2022

7.1K

Area of Science:

  • Spectroscopy
  • Computational Chemistry
  • Machine Learning

Background:

  • Vibrational Circular Dichroism (VCD) spectroscopy is a powerful tool for determining the Absolute Configuration (AC) of chiral molecules.
  • Traditional methods for AC determination can be complex and time-consuming.
  • Machine Learning (ML) offers a potential avenue for automating and enhancing AC determination from VCD spectra.

Purpose of the Study:

  • To evaluate the effectiveness of supervised ML methods for AC determination using VCD spectra.
  • To compare the performance of different ML algorithms in predicting AC.
  • To identify strategies for optimizing ML model efficiency and computational cost.

Main Methods:

  • Exploration of various supervised Machine Learning (ML) algorithms.
  • Focus on Random Forest (RF) and Feedforward Neural Network (FNN) models.
  • Analysis of VCD spectral data with varying sampling intervals.

Main Results:

  • Random Forest (RF) and Feedforward Neural Network (FNN) demonstrated superior performance in AC determination.
  • FNN achieved near-perfect prediction accuracy (up to 0.995).
  • RF provided high accuracy (up to 0.940) and identified key spectral regions for AC identification.
  • Reducing spectral sampling interval effectively lowered data dimensionality and computational cost without performance loss.

Conclusions:

  • Supervised ML, particularly FNN and RF, offers significant added value for AC determination from VCD spectra.
  • Optimizing spectral sampling is an effective strategy to reduce computational demands.
  • These ML approaches provide accurate and efficient methods for chiral molecule analysis.