Webinars LabRulezICPMS Week 6/2025

LabRulez: Webinars LabRulezICPMS Week 6/2025
In the week from February 3, the following webinars await you in the field of atomic and molecular spectroscopy and spectrometry
👉 DETAILS AND REGISTRATION IN THE WEBINARS SECTION
👉 Search and filter in the largest global database with over 4 000 GC, LC, MS and spectroscopy webinars.
1. Mettler-Toledo: Improve Dairy Processing
- Tu, 4.2.2025 09:00 CET
The impact of pH on dairy production, issues with lab pH measurement, the value of continuous pH data and how the latest pH measurement systems can improve dairy processing.
2. Anton Paar: Optimizing Animal Feed Production: Mixing, Extrusion, Texture, and Tribology
- Tu, 4.2.2025 18:00 CET
This webinar will introduce both single and twin-screw extrusion techniques for lab-scale animal food production.
3. Agilent Technologies: Learn Why Atomic Absorption, MicroWave, and ICP Plasma Spectroscopy are the Perfect Tools for Both a Teaching and Research Environment
- Tu, 4.2.2025 19:00 (CET)
We will discuss each of the above techniques and outline the advantages and challenges of each.
4. Anton Paar: Scratch Measurement Optimization
- Tu, 4.2.2025 20:00 CET
Explore how to fine-tune scratch test parameters for your specific needs.
5. Agilent Technologies: Atomic Spectroscopy
- Th, 6.2.2025 04:00 CET
In order to increase the effectiveness and productivity of elemental analysis in food and environmental samples, in this first session we will exchange tips and the newest Agilent technology available.
6. Anton Paar: Data Integrity - the Anton Paar way
- Th, 6.2.2025 10:00 CET
Data integrity has now been extended from the device to the AP Connect Pharma edition. This software allows you to store, verify, and validate your data easily in your own SQL database.
7. Separation Science/Agilent Technologies: Improving Efficiency with Challenging ICP-OES Applications Utilizing a Robust Sample Introduction System
- Th, 6.2.2025 11:00 CET
In this webinar, we'll provide an overview of some new sample introduction components that remove pain points around running challenging sample matrices by ICP-OES efficiently.
