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

High-Resolution Mass Spectrometry (HRMS)01:15

High-Resolution Mass Spectrometry (HRMS)

1.5K
The resolution of a mass spectrometer depends on the efficiency of separating ions with different ion masses. The mass of an atom is approximated to the sum of the masses of protons and neutrons inside, considering the masses of protons and neutrons as equal. However, the masses of the proton (1.6726 × 10−24 g) and neutron (1.6749 × 10−24 g) are not truly equal. There is a minor error in the expression of atomic masses relative to the simplest atom of hydrogen. For...
1.5K
Mass Spectrometry: Complex Analysis01:21

Mass Spectrometry: Complex Analysis

878
Mass spectrometry is an important technique for the identification of pure compounds. However, it has some limitations for the analysis of complex mixtures, often due to excessive fragmentation making the spectrum too complicated to decipher. Mass spectrometry can be combined with suitable separation methods in sequence, forming hyphenated methods, which are useful in the analysis of complex mixtures.
GC–MS is a powerful hyphenated method commonly used in forensics and environmental...
878
Mass Spectrum: Interpretation01:24

Mass Spectrum: Interpretation

1.6K
An unknown compound can be established by identifying the molecular ion peak in the mass spectrum. The molecular ion peak is often weak or absent due to the predominance of fragmentation in high-energy electron beams. In such cases, a low-energy electron beam can be used to scan the spectrum to enhance the intensity of the molecular ion peak. Additionally, chemical ionization, field ionization, and desorption ionization spectra are used to obtain a relatively intense molecular ion peak.
To...
1.6K
NMR Spectroscopy and Mass Spectrometry of Aldehydes and Ketones01:15

NMR Spectroscopy and Mass Spectrometry of Aldehydes and Ketones

4.3K
In aldehydes, the hydrogen atom connected to the carbonyl carbon helps distinguish aldehydes from other carbonyl compounds using ¹H NMR spectroscopy. The closeness of aldehydic hydrogen to the electrophilic carbonyl carbon highly deshields the hydrogen atom causing its signal to appear around 10 ppm in the ¹H NMR spectra. α hydrogens split the aldehydic proton signal, which helps identify the number of α hydrogens in the molecule. For instance, one α hydrogen creates a...
4.3K

You might also read

Related Articles

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

Sort by
Same author

Calibration for Quantitative Chemical Analysis in IR Microscopic Imaging.

Analytical chemistry·2025
Same author

Increased interpretation of deep learning models using hierarchical cluster-based modelling.

PloS one·2023
Same author

Metamodelling of a two-population spiking neural network.

PLoS computational biology·2023
Same author

Crude Oil Density Prediction Improved by Multiblock Analysis of Fourier Transform Ion Cyclotron Resonance Mass Spectrometry, Fourier Transform Infrared, and Near-Infrared Spectroscopy Data.

Applied spectroscopy·2023
Same author

Combined Approach to Evaluate Hydrate Slurry Transport Properties through Wetting and Flow Experiments.

ACS omega·2023
Same author

Deep learning-enabled Inference of 3D molecular absorption distribution of biological cells from IR spectra.

Communications chemistry·2023
Same journal

Analysis of strength degradation of coal and rock masses and stability of mined areas under long term immersion environment.

PloS one·2026
Same journal

Biogenic Silver-Selenium nanocomposite with anticancer activity and potent efficacy against vancomycin-resistant Staphylococcus aureus.

PloS one·2026
Same journal

Preparation and physicochemical characterization of a biodegradable chitosan/carboxymethyl cellulose hydrogel synthesized in NaOH/urea medium.

PloS one·2026
Same journal

Action-guilt, survivor-guilt, and depression in combat-related PTSD.

PloS one·2026
Same journal

Explainable machine learning for predicting activities of daily living at discharge in stroke patients: A retrospective study using SHAP interpretability.

PloS one·2026
Same journal

Deep learning based two-way feature depiction model for brain tumor detection.

PloS one·2026
See all related articles

Related Experiment Video

Updated: Sep 1, 2025

Single-throughput Complementary High-resolution Analytical Techniques for Characterizing Complex Natural Organic Matter Mixtures
09:38

Single-throughput Complementary High-resolution Analytical Techniques for Characterizing Complex Natural Organic Matter Mixtures

Published on: January 7, 2019

8.7K

Using machine learning-based variable selection to identify hydrate related components from FT-ICR MS spectra.

Elise Lunde Gjelsvik1, Martin Fossen2, Anders Brunsvik2

  • 1Norwegian University of Life Sciences, Faculty of Science and Technology, Aas, Norway.

Plos One
|August 17, 2022
PubMed
Summary
This summary is machine-generated.

This study identifies key crude oil components that cause gas hydrate agglomeration in pipelines. Advanced mass spectrometry and machine learning pinpointed asphaltenes and naphthenic acids as potential hydrate-active compounds.

More Related Videos

Identifying Per- and Polyfluorinated Chemical Species with a Combined Targeted and Non-Targeted-Screening High-Resolution Mass Spectrometry Workflow
09:04

Identifying Per- and Polyfluorinated Chemical Species with a Combined Targeted and Non-Targeted-Screening High-Resolution Mass Spectrometry Workflow

Published on: April 18, 2019

12.6K
Standardized Identification of Compound Structure in Tibetan Medicine Using Ion Trap Mass Spectrometry and Multiple-Stage Fragmentation Analysis
09:24

Standardized Identification of Compound Structure in Tibetan Medicine Using Ion Trap Mass Spectrometry and Multiple-Stage Fragmentation Analysis

Published on: March 17, 2023

972

Related Experiment Videos

Last Updated: Sep 1, 2025

Single-throughput Complementary High-resolution Analytical Techniques for Characterizing Complex Natural Organic Matter Mixtures
09:38

Single-throughput Complementary High-resolution Analytical Techniques for Characterizing Complex Natural Organic Matter Mixtures

Published on: January 7, 2019

8.7K
Identifying Per- and Polyfluorinated Chemical Species with a Combined Targeted and Non-Targeted-Screening High-Resolution Mass Spectrometry Workflow
09:04

Identifying Per- and Polyfluorinated Chemical Species with a Combined Targeted and Non-Targeted-Screening High-Resolution Mass Spectrometry Workflow

Published on: April 18, 2019

12.6K
Standardized Identification of Compound Structure in Tibetan Medicine Using Ion Trap Mass Spectrometry and Multiple-Stage Fragmentation Analysis
09:24

Standardized Identification of Compound Structure in Tibetan Medicine Using Ion Trap Mass Spectrometry and Multiple-Stage Fragmentation Analysis

Published on: March 17, 2023

972

Area of Science:

  • Petroleum Engineering
  • Analytical Chemistry
  • Computational Chemistry

Background:

  • Gas hydrate agglomeration poses a significant flow assurance challenge in oil and gas pipelines.
  • Naturally occurring crude oil components are suspected to modify gas hydrate surface properties, but their identity remains unknown.

Purpose of the Study:

  • To identify specific crude oil components responsible for gas hydrate formation and agglomeration.
  • To understand the surface modification mechanisms of gas hydrate particles in crude oil.

Main Methods:

  • Successive accumulation and spiking of hydrate-active crude oil fractions to concentrate relevant compounds.
  • Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT-ICR MS) for detailed chemical analysis of oil samples.
  • Machine learning algorithms, including Partial Least Squares Discriminant Analysis (PLS-DA), for variable selection and identification of key components.

Main Results:

  • PLS-DA identified 23 critical variables related to hydrate formation from FT-ICR MS spectra.
  • Principal Component Analysis (PCA) demonstrated distinct compositional changes in oil samples with increasing hydrate-active component concentration.
  • Identified compounds include potential asphaltenes and naphthenic acids, correlating with a positive wetting index.

Conclusions:

  • Specific molecular components, likely asphaltenes and naphthenic acids, are implicated in promoting gas hydrate formation and agglomeration.
  • The study provides a methodology for identifying hydrate-active components in crude oil using advanced analytical and computational techniques.
  • Understanding these components is crucial for developing effective flow assurance strategies in the oil and gas industry.