Advanced CHN Microanalysis Software
Product News Mar 02, 2015
The 2015 software revision for the Model 440 combines the ease-of-use and intuitive operation of its Windows™ architecture with the many advantages of real-time data acquisition. This software enables complete control of combustion parameters allowing Model 440 users to achieve unsurpassed CHN data accuracy and precision as well as providing the flexibility to handle the most difficult sample types.
As a company dedicated to CHN microanalysis - Model 440 software truly reflects microanalyst needs in areas including ease of use, performance optimisation, data quality tracking and automated diagnostic routines for monitoring critical parameters / diagnosing problems should they occur.
In addition the Model 440 software contains some useful advanced features. Linear Regression Plus is a unique software algorithm that provides unmatched accuracy in the determination of the nitrogen content of combustible samples. Created from the experience of leading experts in CHN microanalysis - Linear Regression Plus both improves data quality and reduces the time taken to accurately determine the nitrogen composition of samples. Linear Regression Plus enables accurate measurement of low Nitrogen levels with a high degree of accuracy.
Committed to customer support Exeter Analytical provides free software updates for the life of your CHN instrument.
The Model 440 is a static combustion CHN Elemental Analyzer, with a unique horizontal furnace design, which enables easy removal of sample residue between each analysis. Consequently one combustion tube will analyse in excess of 1000 samples without the need for removal and cleaning. By comparison other elemental analyzers, employing vertical furnace designs, will require cleaning after as little as 20 samples. The gas flow characteristics of the Model 440 analyzer are superior to other elemental analyzers due to the effective elimination of troublesome residue build-up. This thereby provides longer-term calibration stability as well as enhanced accuracy and precision for measured sample data.