Anwendung

The most important criterion for medical diagnostics is an accurate and reliable method for determining the cause of the disease in order to be able to make an optimal therapy decision. Here, Raman spectroscopy in combination with machine-learning systems offers you the following advantages:

For the production of life-saving, life-sustaining and life-enhancing drugs, high precision and efficiency is essential to manufacture them in high quality and at low cost. Raman spectroscopy in combination with machine-learning systems offers you the following advantages in this regard:

AI-based process analytics are increasingly providing new insights into processes that must ensure high quality assurance requirements while reducing costs. These require special analysis techniques that must both completely and accurately map the process and offer timely evaluation of the data. Raman spectroscopy as a versatile analysis technique, offers enormous potential for this.

The advantages of Raman spectroscopy in chemical process analysis:

• High specificity
• Analyses of organic and inorganic materials
• Applicable to solids, liquids and gases
• Non-invasive and non-destructive
• Short measurement times
• Low effort for sample preparation
• Process monitoring at the highest level
• Possibility to measure from aqueous media

We would be happy to support you in developing solution strategies for your individual problems and discuss ideas with you on how Raman spectroscopy, linked with AI technology, can also be usefully applied for you. We are looking forward to your inquiry: This email address is being protected from spambots. You need JavaScript enabled to view it.. 

Micro Raman spectroscopy in combination with chemometric methods allows to quickly and easily identify bacteria and other microorganisms independent of their strain, different growth conditions and cultivation. Analysis with Raman spectroscopy offers you numerous application possibilities and advantages, e.g.:

Soils and water bodies are complex ecosystems that are sometimes severely out of their ecological balance due to intensive management. Raman spectroscopy in combination with machine-learning algorithms can contribute to the restoration of sensitive ecosystems, e.g. through the use of the "Raman" method:

Quality awareness for foodstuffs is becoming increasingly important in our society. In order to meet this and to analyse and produce your products at the highest level of quality, Raman spectroscopy in combination with chemometric methods offers you the following advantages: