Tips and Tricks: GPC/SEC Dos and Don'ts For Data Analysis

Article

The Column

ColumnThe Column-02-04-2013
Volume 9
Issue 2

The requirements for GPC/SEC data analysis to obtain precise, reproducible and accurate results are very specialized. Therefore, often dedicated software tools offering flow-rate correction or different calibration options need to be employed. This instalment of Tips & Tricks looks at these requirements.

The requirements for GPC/SEC data analysis to obtain precise, reproducible and accurate results are very specialized. Therefore, often dedicated software tools offering flow-rate correction or different calibration options need to be employed. This instalment of Tips & Tricks looks at these requirements.

Click here for the full article in The Column

Articles in this issue
Prehistoric cheese
"Sigma" Approaches to Maintain Quality and Reduce Variations when Performing Chromatography Analysis
"Sigma" Approaches to Maintain Quality and Reduce Variations when Performing Chromatography Analysis
Cockroaches could help human hygiene
MT&A-804625-1408548296496.jpg
Market Profile: Ion Chromatography
Upping the Ante: Food Safety Training
Upping the Ante: Food Safety Training
Tips and Tricks: GPC/SEC Dos and Don'ts For Data Analysis
Tips and Tricks: GPC/SEC Dos and Don'ts For Data Analysis
Related Content
Rethinking Chromatography Workflows with AI and Machine Learning

Rethinking Chromatography Workflows with AI and Machine Learning

Isabel Kolinko
April 1st 2025
Article

Interest in applying artificial intelligence (AI) and machine learning (ML) to chromatography is greater than ever. In this article, we discuss data-related barriers to accomplishing this goal and how rethinking chromatography data systems can overcome them.

Neural network 3D illustration. Big data and cybersecurity. Data stream. Global database and artificial intelligence. Bright, colorful background with bokeh effect: © Siarhei - stock.adobe.com

Improving Suspect Compound Identification in Comprehensive Two-Dimensional Liquid Chromatography High-Resolution Mass Spectrometry Data Workflows

Kate Jones
March 20th 2025
Article

A two-step workflow to extract pure mass spectra from comprehensive two-dimensional liquid chromatography high-resolution mass spectrometry (LC×LC–HRMS) data has been created and tested.

robot with glass laptop | Image Credit: © phonlamaiphoto - stock.adobe.com

Improving LC Method Development Using Machine Learning

Aaron Acevedo
March 17th 2025
Article

Reinforcement learning was tested as a means of improving liquid chromatography method development.

Illustration of IT roadmap modern technology and innovative processes, networking and big data: © Johannes - stock.adobe.com

Improved Machine Learning Workflow for Predicting Oligonucleotide Separation

Kate Jones
March 14th 2025
Article

A research group has developed an improved workflow for constructing machine learning (ML) models in oligonucleotide separation.

Abstract flying dragons on a dark blue background. Technological background for design on the topic of artificial intelligence, neural networks, big data | Image Credit: © LariBat - stock.adobe.com

Predicting Concentration Profiles in Gradient LC Using Neural Networks

Aaron Acevedo
March 13th 2025
Article

Physics-informed neural networks were tested for their capabilities in predicting concentration profiles in gradient liquid chromatography.

Laptop computer displaying logo of Agilent Technologies | Image Credit: © monticellllo - stock.adobe.com

Agilent Reports Financial Results from Q1 of 2025

Aaron Acevedo
March 11th 2025
Article

The company reported $1.68 billion in revenue at a 25.1% operating margin across its businesses in America, Europe, and Asia.