Product News: TA Instruments introduces the Discovery X3 Differential Scanning Calorimeter for multi-sample analysis

The Discovery X3 DSC is said to generate three times the amount of experimental data as a standard DSC

04 Mar 2020


TA Instruments has introduced a new addition to the Discovery™ Differential Scanning Calorimeter (DSC) suite: Discovery X3 DSC. This revolutionary multi-sample X3 DSC incorporates patented Fusion Cell™ and Tzero™ technologies and aims to deliver industry-leading performance for up to three samples simultaneously.

The demand for the development of high-performance materials is increasing rapidly throughout many industries. New materials require considerable testing and these tests significantly extend the development and validation timelines. Traditional DSCs are limited to analyzing a single sample during an experiment which may, depending upon the method, require several minutes to many hours.

Temperature modulating DSC (MDSC) experiments, which are used to determine material properties or explore material stability and compatibility, typically take hours to achieve a result.

Uniquely engineered to eliminate multiple testing steps, the new Discovery X3 DSC generates three times the amount of experimental data as a standard DSC, effectively consolidating three instruments into one. The baseline quality and sensitivity of the Fusion Cell technology allows researchers to compare various formulations or competitive materials side-by-side under the exact same test conditions. It is the most versatile, highest-throughput DSC available to scientists. Internal verification of the instrument calibration performed simultaneously with measuring valuable pharmaceutical samples is also a possibility now with the X3 DSC multi-sample cell.

TA Instruments innovation stretches beyond the hardware with the introduction of the TRIOS™ software feature, Batch Processing, which is perfectly aligned to assist with three times more data generated with the X3 DSC. Batch Processing in TRIOS easily handles analysis, reporting and control charting of large data sets.

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