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Related Concept Videos

Chromatographic Resolution01:15

Chromatographic Resolution

In chromatography, a solute moves through a chromatographic column and tends to spread, forming a Gaussian-shaped band. The longer the solute spends in the column, the broader the band becomes. The broadening can lead to overlaps within the column, affecting separation effectiveness.
The effectiveness of separation can be evaluated by determining the level of separation between two neighboring peaks in a chromatogram, which represents the individual components of a sample.
In chromatography,...
Optimizing Chromatographic Separations01:15

Optimizing Chromatographic Separations

Optimizing chromatographic separations is crucial for obtaining clean separations in a minimum amount of time. Optimization is required for several factors, including kinetic effects related to band broadening, plate height, capacity factor, and separation factor.
Band broadening refers to spreading solute bands as they travel through the column. This broadening can impact resolution. Plate height (H) represents the length required for one theoretical plate. A lower plate height corresponds to...
Mass Analyzers: Overview01:13

Mass Analyzers: Overview

The mass analyzer is a crucial component of the mass spectrometer. In the ionization chamber, the vaporized sample is bombarded with a high-energy electron beam to generate a radical cation and further fragment into neutral molecules, radicals, and cations. A series of negatively charged accelerator plates accelerate the cations into the mass analyzer. The mass analyzer separates ions according to their mass-to-charge (m/z) ratios and then directs them to the detector. The common types of mass...
High-Resolution Mass Spectrometry (HRMS)01:15

High-Resolution Mass Spectrometry (HRMS)

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 example, the mass of helium...
Size-Exclusion Chromatography01:08

Size-Exclusion Chromatography

In size-exclusion chromatography (SEC), also known as molecular-exclusion or gel-permeation chromatography, molecules are separated based on their sizes. This technique is important for separating large molecules such as polymers and biomolecules. The two classes of micron-sized stationary phases encountered in SEC are silica particles and cross-linked polymer resin beads. Both materials are porous, but their pore sizes vary significantly.
Silica particles offer advantages such as rigidity,...
Gas Chromatography: Overview of Detectors01:13

Gas Chromatography: Overview of Detectors

Detectors in gas chromatography (GC) help identify and quantify the components of a mixture by translating chemical properties into measurable signals, which are displayed on a chromatogram. Detectors can be categorized into two main types: destructive and non-destructive.
A non-destructive detector allows a sample to be analyzed without altering or consuming it, meaning the sample can be collected after detection for further analysis. Examples include thermal conductivity detectors and...

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Related Experiment Video

Updated: May 30, 2026

Direct Comparison of Hyperspectral Stimulated Raman Scattering and Coherent Anti-Stokes Raman Scattering Microscopy for Chemical Imaging
09:46

Direct Comparison of Hyperspectral Stimulated Raman Scattering and Coherent Anti-Stokes Raman Scattering Microscopy for Chemical Imaging

Published on: April 28, 2022

Relationship between selectivity and average resolution in comprehensive two-dimensional separations with

Joe M Davis1, Sarah C Rutan, Peter W Carr

  • 1Southern Illinois University at Carbondale, Department of Chemistry and Biochemistry, 1245 Lincoln Drive, Carbondale, IL 62901-4409, USA. chimicajmd@ec.rr.com

Journal of Chromatography. A
|July 23, 2011
PubMed
Summary
This summary is machine-generated.

Multivariate selectivity (SEL) predicts singlet peaks in separations, enabling a new metric for 2D chromatography performance. This metric improves with spectral data, enhancing peak resolution and quantification accuracy.

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Multiplex Chemical Imaging Based on Broadband Stimulated Raman Scattering Microscopy
09:57

Multiplex Chemical Imaging Based on Broadband Stimulated Raman Scattering Microscopy

Published on: July 25, 2022

Area of Science:

  • Analytical Chemistry
  • Chromatography
  • Chemometrics

Background:

  • Comprehensive two-dimensional (2D) separations are crucial for analyzing complex mixtures.
  • Statistical-overlap theory (SOT) predicts peak overlap and resolution in separations.
  • Multivariate selectivity (SEL) quantifies the precision of peak quantification using methods like PARAFAC.

Purpose of the Study:

  • To establish a new metric for 2D separation performance based on multivariate selectivity (SEL).
  • To evaluate the impact of ancillary spectroscopic data on this performance metric.
  • To compare SEL predictions with statistical-overlap theory (SOT).

Main Methods:

  • Simulated 2D separations with randomly positioned peaks.
  • Calculation of multivariate selectivity (SEL) for individual and averaged peaks.
  • Computation of average minimum resolution with and without multi-wavelength UV-vis spectral data.

Main Results:

  • Average SEL equals the average fraction of singlet peaks, validating SOT predictions.
  • A new metric, average minimum resolution, was computed, showing improvement with spectral data.
  • Required resolution decreased significantly with spectral assistance, especially under high peak crowding.

Conclusions:

  • Multivariate selectivity (SEL) provides a robust metric for 2D separation performance.
  • Ancillary spectral data substantially enhances resolution and quantification accuracy.
  • SEL simplifies the optimization of peak capacity in online 2D separations.