GC and GCMS webinars - Week 29

Su, 18.7.2021
| Original article from: LabRulezGCMS Webinars
This week, a total of 6 interesting webinars are waiting for you in the field of GC and GC/MS.
LabRulez: GC and GCMS webinars - Week 29

LabRulez: GC and GCMS webinars - Week 29

In the week from July 19, 2021, the following webinars await you in the field of GC and GCMS. More details and registration can be found in the WEBINARS section.:

Search and filter in more than 1 000 GC and LC webinars.

1. Phenomenex: How to do a Successful SPE Method Development & Optimization

What to be considered? Various phases of SPE. How to run a successful SPE method. Optimizing the methods after development.

2. SCION Instruments: Compass CDS: Plugins

In this webinar John MacKenzie reviews and demonstrates some of the Compass CDS Plugins. This is one of the strengths of the Compass, as it makes it an easier and more versatile product.

3. C&EN/MilliporeSigma: Synthetic Carbon Adsorbents for challenging separations & purifications

This webinar compares performance of several Carboxen® Synthetic Carbons against granular activated carbon (GAC).

4. Separation Science/Agilent Technologies: Fatty Acid Esters in Infant Formula - Determination of 2-MCPD and 3-MCPD Using an Agilent 8890 GC System with an Agilent 5977B GC/MSD

Separation Science, in collaboration with Agilent, offers an upcoming webinar providing a total solution for determining the fatty acid esters of 3-MCPD and 2-MCPD in infant formula.

5. Agilent Technologies: Decisions Decisions: How to Select the Correct GC Column for your Application

This talk will discuss how the various stationary phases influence selectivity, as well as how column dimensions effect peak behavior and resolution.

6. Agilent Technologies: A Standard Workflow and Troubleshooting Process to Maintain and Troubleshoot the Flow Paths of Intuvo and Conventional GCs

The webinar focuses on what constitutes a good QC test mix, what data features to review, the steps to maintain data quality, and what to do when data quality decreases or fails the customer’s QC guidelines.

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