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MassHunter Qualitative Analysis: Learn Tricks for Faster Analysis of Unit and Accurate Mass Data

RECORD | Already taken place Tu, 25.1.2022
We will cover Setting up a “workflow” to process data efficiently & Creating a library from your data and using for identifications & Demonstrate the additional tools when accurate mass data is analyzed.
Go to the webinar
Agilent Technologies: GC/MS MassHunter Virtual Workshop
Agilent Technologies: GC/MS MassHunter Virtual Workshop

MassHunter Qualitative Analysis 10 is feature-rich mass spectrometry screening software for the confirmation of target or suspect compounds, and for the identification of unknown analytes. The software combines feature-finding algorithms, library searching, and elemental composition calculations (accurate mass data). These advanced data mining and processing options let you rapidly and accurately find all detectable compounds and easily confirm targets or identify unknowns. The workflow method setup allows data files to be automatically and reproducibly analyzed with the user-selected parameters to minimize mouse clicking and data processing time. Results can be displayed using fast, flexible data reporting with preconfigured reports that simplify basic analyses.

Key Learning Objectives:

  • Setting up a “workflow” to process data efficiently
  • Creating a library from your data and using for identifications
  • Demonstrate the additional tools when accurate mass data is analyzed

Who Should Attend:

Anyone using MassHunter Qualitative Analysis but might not know al the features or think they could be more efficient.

Presenter: Matt Curtis (GC/MS Applications Scientist, Agilent Technologies, Inc.)

Matt joined Agilent in 2013 as a GC/MS applications scientist in the Santa Clara, CA Center of Excellence, with GC/MS experience starting as an undergraduate. His primary responsibility is focused on providing instrument demos for customer interested in each technology Agilent offers; the GC/MS single quadrupole, triple quadrupole and the quadrupole Time-of-Flight. The variety of different applications submitted to the demo lab provide a unique knowledge of optimizing parameters for each experiment.

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