ACD/ChromGenius :: Method Selection Based on Chemical Structure :: ACD/Labs
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ACD/ChromGenius

The functionality of ACD/ChromGenius has been migrated to ACD/AutoChrom and ACD/MS Structure ID as of ACD/Labs software release 2018.1. ChromGenius has been officially retired as a standalone product and will not receive any further updates. Technical support will continue for 3 years from the time of retirement, as per our Software Life Cycle Policy.

For more information on migrating or upgrading, please contact our Sales team: sales@acdlabs.com.

Predict Retention Times and Chromatograms Based on Physicochemical Property Parameters

ACD/ChromGenius predicts retention times and chromatograms based on the structures of the compounds to be separated, and allows you to select the best generic separation method for your sample, prior to injection. ACD/ChromGenius reduces the number of screening experiments needed, by helping you determine which generic methods will work and which will fail, before you perform a single separation or sample preparation.

Features

Benefits

ACD/ChromGenius uses a knowledgebase of experimental structures and retention times as a basis to predict retention times and chromatograms for new compounds using ACD/Labs' physicochemical prediction algorithms.

Draw or import the chemical structure of compounds to be separated, and ACD/ChromGenius simulates the separation for different separation methods available in the knowledgebase. In just a few seconds, the methods are ranked according to suitability, and displayed with a simulated chromatogram and a table of predicted retention times.

Boost Prediction Accuracy with Absolv Parameters

Depending on the application, or when the compounds under investigation fall outside of the chemical space covered by your experimental database, you may want greater accuracy than can be achieved with ACD/ChromGenius alone. The ACD/ChromGenius Absolv Add-on increases the accuracy of predicted retention times using Abraham solvation parameters calculated from chemical structure. The parameters are then incorporated into the prediction algorithm, resulting in greater accuracy.

Additional Resources

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