How to save time with HighScore's powerful big-data features

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In this webinar, we will cover best practice procedures and share our tips on how to save time when analyzing multiple XRD datasets with HighScore

The webinar will cover efficient data display, raw data and data clusters, how to create a predictive partial least squares regression (PLSR) model, how to efficiently automate tasks using Smart Batches – as well as discuss some handy shortcuts that could save a great deal of time in day-to-day work.   

Whether you have questions about samples or sample prep, setting up an experiment, or performing analysis, feel free to submit them so that we can deliver the information you require. There’s always more to learn, whether it’s setting up your measurements for quick batch processing, gaining confidence in the quality of your results, or presenting your data in the best format. 

For this webinar, we’ll assume you’ve watched the previous one on the same topic. Don't worry if you missed it or can't remember it – you can watch it back here.

More information: 

This webinar is part of our ongoing Ask an Expert! webinar series. These live webinars are meant for students, researchers, and professors alike who want to sharpen their analytical methods, deepen their knowledge, or find out how to improve their data.  

We’ll provide extensive materials analysis information and answer your most frequently asked questions. In other words, it’s the ultimate way to improve your materials science research and engineering knowledge.  

It’s free to attend any of the classes. For a full overview of the 2022 program, click here

To watch any of last year’s webinars, take a look at the full program of 2021 recorded here.

演讲嘉宾

  • Thomas Degen - Senior Scientist and Co-author of HighScore Software
  • Matteo Pernechele - Application Specialist XRD

更多信息

Who should attend? 

  • Any Researcher or Industry XRD user that must analyze many datasets

What will you learn? 

  • How to efficiently analyze many scans in HighScore
  • How clustering can help to get the big picture of an experiment
  • How to setup Smart Batches and what they can do