2023.11.07 Michael Rauch, Schrödinger Inc.
Schrödinger's AutoQSAR tool for Machine Learning can be found at: https://nanohub.org/tools/autoqsar
For details for free access on nanoHUB see: https://nanohub.org/groups/schrodinger/

We are in the midst of an inflection point in the utilization and impact of molecular modeling in materials science, particularly for industrial applications. This inflection is driven by significant advancements in compute power, methods development, and the integration of physics-based methods with machine learning.

In this workshop, we will demonstrate the hands-on use of Schrödinger's MS Maestro graphical user interface within nanoHUB to perform machine learning model creation and implementation.

In particular, we will walk participants through a hands-on demonstration of Schrödinger’s AutoQSAR tool for predicting experimental ionic conductivity of ionic liquids. Note that while the example demonstrated here will be tailored towards energy materials, the same workflow can be applied for a variety of materials science applications, ranging from organic electronics to complex formulations.

In order to participate in the hands-on portion of the workshop, please be sure to request membership to the Schrödinger Materials Science nanoHUB group (https://nanohub.org/groups/schrodinger) prior to the seminar. Otherwise, feel free to simply watch the demonstration.

Table of Contents:
00:00 Hands-On Workshop in nanoHUB: Machine Learning Models for Ionic Conductivity with Schrödinger's AutoQSAR
01:47 The Schrödinger Platform: An integrated solution for digital materials discovery and analysis
02:29 Atomistic Simulation Across Diverse Systems and Applications
03:19 Methods Power Capabilities
04:06 From Engines to Workflows
04:32 Visit Our Blog for Case Studies
04:46 Today's Example
05:43 Today's Example
07:13 AutoQSAR
07:55 nanoHUB Access
08:37 Live Demo
42:39 Next Steps
44:37 Questions? Thank you!