Advantages of Sample Observation Calorimetry for Polymers
Presented by Meaghan Fielding
Rigaku’s Sample Observation technology, able to help visually identify heat events during DSC and STA analysis
Calorimetry is a trusted method in thermal analysis that is used to determine thermal events, specific heat, and mass loss. With applications in pharmaceutical, polymers, and many other areas, DSC and STA are common lab instruments. Recent innovations in calorimetry by Rigaku have resulted in the development of sample observation calorimetry – the first of its kind.
Sample observation technology allows for the accurate determination of heat events with visual confirmation. Changes in shape and color can easily be observed. This is invaluable when trying to differentiate endothermic heat events, such as a melt vs a decomposition, or exothermic heat events, such as a crystal-crystal phase change vs a decomposition.
This recent innovation in calorimetry has significant benefits for the polymers/plastic industry. Novel materials typically present a challenge to analyze, as there is no way to visually confirm events such as melt, crystallization, etc. These problems are solved with sample observation calorimetry, as any changes to the sample can be viewed in real time.
With the turn away from single-use plastics, we are seeing a rise in novel materials which are developed as an alternative. One example of this is PHBH, a biopolymer. Biopolymers have been replacing single-use plastics for applications such as straws. When PHBH is tested on the Rigaku STA8122, there is a small change in baseline at around 150C, which would typically be attributed to noise. However, when using sample observation, it is easy to confirm this is in fact the melting point.
In the past, it has been impossible to visually confirm changes in a sample when measuring with DSC and STA. Now, changes such as colour, shape, size, and phase change can easily be confirmed. This eliminates the ambiguity from data analysis and ensures correct characterization, resulting in less time wasted searching literature and more confidence in the data.