Published October 19, 2020
| Version v1
Journal article
Open
Fast predictions of liquid-phase acid-catalyzed reaction rates using molecular dynamics simulations and convolutional neural networks
- 1. Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, WI, US
Description
This repository contains molecular dynamics simulation trajectories, Python scripts, and procedures for the publication:
A. K. Chew, S. Jiang, W. Zhang, V. M. Zavala, and R. C. Van Lehn. "Fast predictions of liquid-phase acid-catalyzed reaction rates using molecular dynamics and convolutional neural networks." Chem. Sci. Science, 2020, 11, 12464-12476. [Link]
Please refer to "2020_SolventNet_Chem_Sci_ReadMe.pdf" for step-by-step instructions to accessing the data and generating main text images.
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2020_SolventNet_Chem_Sci_ReadMe.pdf
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