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autoDIAS: A Python Tool for an Automated Distortion/Interaction Activation Strain Analysis

preprint
revised on 20.05.2019, 21:49 and posted on 21.05.2019, 15:15 by Dennis Svatunek, Kendall N. Houk
The Distortion/Interaction Activation Strain (DIAS) analysis is a powerful tool for the investigation of energy barriers. However, setup and data analysis of such a calculation can be cumbersome and requires lengthy intervention of the user. We present autoDIAS, a python tool for the automated setup, performance, and data extraction of the DIAS analysis, including automated detection of fragments and relevant geometric parameters.

Funding

FWF Austrian Science Fund - J 4216

Hochschuljubiläumsstiftung of the city of Vienna - H-331849/2018

History

Email Address of Submitting Author

d.svatunek@chem.ucla.edu

Institution

University of California, Los Angeles

Country

United States

ORCID For Submitting Author

0000-0003-1101-2376

Declaration of Conflict of Interest

The authors declare no Conflict of Interest.

Version Notes

Reformatted. More extensive citation of research using DIAS. Minor bug fixes in the code.

Exports