OPUS Release 8.7: Microscopy Spotlight

At Bruker, we are pretty proud of our all-in-one spectroscopy software OPUS. It combines all vital FT-IR tools, from identification and database search to time resolution and microscopy, into a single interface. But that is not what we want to talk about today.

In this article we want to talk about the latest OPUS release. Actually, many of our customers are not aware that each release also contains brand new core features. Today we want to have a look at the major microscopy functions, that have been added in OPUS 8.7.

Before we get into the list of new features, know that Bruker is working hard on autonomous analysis mechanisms. Our vision is to completely relieve the user of tedious work-steps, and to perform basic evlaution transparently and autonomously. This should help the user with one thing above all: to concentrate on the results.

New Feature: Adaptive K-Means Clustering

TL;DR: K-means clustering analyzes large data sets at the push of a button, based on the spectral variances of the collected data.

Figure 1: The components of this pain killer tablet were detected autonomously by adaptive K-means clustering and fitting IR image was generated.

This new function is the logical next development step for our well known cluster analysis function. Its new algorithm evaluates your imaging or mapping results autonomously by the determination of spectral variances. This way, a time-consuming search for existing chemical classes is avoided.

Now you can watch the algorithm predict the sample’s chemical classes without manual input or supervision. By doing so, it allows chemical mapping and distribution analysis of unknown samples or small structures in mere minutes.

New Feature: Cluster ID for IR Images

TL;DR: Automatically detects and identify clusters of the same spectral origin within chemical images fully automatically, e.g. particles.

Cluster ID has simplified the analysis of this particle-loaded filter. All particles are identified, classified in groups and statistics and size data are provided as well.

The Cluster ID feature provides easy determination of the chemical identity of classified sample components. It is applied in the analysis of particles, layers in laminates, the constituents of pharmaceutical tablets and other inhomogeneous materials.

It reliably generates comprehensive statistical reports on the quantity, size and, of course, identity of all analyzed structures. This takes analysis of particles or technical cleanliness to a new, autonomous level.

Compatible to All IR and Raman Microscopes

Obviously there are many other new functions, features and patches. As always, you can find our complete release-notes on our homepage:
OPUS Latest Release Notes.