How to Improve Automated Imaging Analysis with Raman Spectroscopy

For characterizing particle shape, automated image analysis is fast replacing manual microscopy and combining it with Raman spectroscopy adds chemical identification.

For characterizing both particle size and shape, automated image analysis systems which supply detailed morphological information are rapidly replacing manual microscopy as the most effective technique.

In order to provide useful and actionable insight, these sophisticated new instruments utilize the latest technology. These instruments had been regarded as rather niche until recently because of their previously limited functionality.

Yet, huge advances in terms of both their performance and capabilities, in addition to the new insights into particle morphology provided in these instruments, have opened up exciting new pathways for research and development

They have also helped to optimize production and manufacturing methods to make them a much more attractive proposition. Improvements in camera technology have been one of the key advances, enabling more sensitive measurements to be recorded.

This has been complemented by more powerful image segmentation methods, leading to far more accurate and detailed particle size and shape measurements.

The integration of Raman spectroscopy with automated imaging systems is another recent development in this field which has resulted in a method called Morphologically-Directed Raman Spectroscopy (MDRS®).

In addition to supplying morphological data on each of the particles being measured, it also supplies chemical identification and differentiation of particles within a mixed sample.  

The information that is supplied by automated imaging methods is invaluable in a range of industry sectors, including:

  • Additive manufacturing
  • Pharmaceuticals
  • Metal powders
  • Forensics
  • Battery electrode manufacture

This leads to a deeper understanding of material characteristics and manufacturing processes and helps to resolve issues during the development of new products and formulations.

This information has been sourced, reviewed and adapted from materials provided by Malvern Panalytical.

For more information on this source, please visit Malvern Panalytical.

Citations

Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Malvern Panalytical. (2023, May 30). How to Improve Automated Imaging Analysis with Raman Spectroscopy. AZoM. Retrieved on October 30, 2024 from https://www.azom.com/article.aspx?ArticleID=19286.

  • MLA

    Malvern Panalytical. "How to Improve Automated Imaging Analysis with Raman Spectroscopy". AZoM. 30 October 2024. <https://www.azom.com/article.aspx?ArticleID=19286>.

  • Chicago

    Malvern Panalytical. "How to Improve Automated Imaging Analysis with Raman Spectroscopy". AZoM. https://www.azom.com/article.aspx?ArticleID=19286. (accessed October 30, 2024).

  • Harvard

    Malvern Panalytical. 2023. How to Improve Automated Imaging Analysis with Raman Spectroscopy. AZoM, viewed 30 October 2024, https://www.azom.com/article.aspx?ArticleID=19286.

Ask A Question

Do you have a question you'd like to ask regarding this article?

Leave your feedback
Your comment type
Submit

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.