MS Informatics
Efficient machine learning model builder for materials science applications
Overview
MS Informatics provides machine learning (ML) and featurization tools for organic and organometallic molecular materials, polymers, and inorganic solid materials to assist informatics-based materials research. By combining physics-based featurization with customized pre-built ML models, users can take advantage of speed of data-driven approaches in addition to the generalizability and accuracy of physics-driven methods.
Key Capabilities
Analyze structures and diversity of a large chemical space with cheminformatics tool
Generate advanced 2D, 3D, and repeat-unit-based descriptors for organic, inorganic, and polymeric materials
Featurize materials by quantum mechanics (QM) and semiempirical QM molecular descriptors
Build models for quantitative structure-property relationships (QSPR)
Includes prebuilt machine learning models to predict a diverse range of properties
Boiling point and vapor pressure of organic and organometallic compounds
Glass transition temperature of polymers
Frequency-dependent polymer dielectric constant and dielectric loss
Density
Viscosity
Case Studies
Discover how Schrödinger technology is being used to solve real-world research challenges.
How machine learning enables accurate prediction of precursor volatility
Accelerating the design and optimization of OLED materials using active learning
De novo design of hole-conducting molecules for organic electronics
Broad applications across materials science research areas
Get more from your ideas by harnessing the power of large-scale chemical exploration and accurate in silico molecular prediction.
Catalysis & Reactivity
Energy Capture & Storage
Organic Electronics
Polymeric Materials
Complex Formulations
Consumer Packaged Goods
Related Products
Learn more about the related computational technologies available to progress your research projects.
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Quantum ESPRESSO GUI
Integrated graphical user interface for nanoscale quantum mechanical simulations
Publications
Browse the list of peer-reviewed publications using Schrödinger technology in related application areas.
Training & Resources
Online certification courses
Level up your skill set with hands-on, online molecular modeling courses. These self-paced courses cover a range of scientific topics and include access to Schrödinger software and support.
Tutorials
Learn how to deploy the technology and best practices of Schrödinger software for your project success. Find training resources, tutorials, quick start guides, videos, and more.
Other Resources