APPLICATION OVERVIEW

Accelerating Catalysis
and Reactivity R&D
with Atomic-scale
Simulation, Machine
Learning, andEnterprise Informatics
As market demands evolve, R&D scientists across industries —from consumer packaged goods to automotives — face similar
challenges in developing and optimizing the next-generation ofcatalysts. Scientists need new catalysts that help them reduceenergy requirements, eliminate unwanted side products, andimprove the selectivity and reactivity of reactions.

Solution Overview
We need new materials, and we need them fast. Fortunately, thecontinual march of scientific progress promises faster answers than inthe past. Computer-driven molecular design, with its ability to generatemassive quantities of simulated data, facilitates entry into new frontiersof chemical discovery for sustainable materials design. It brings thepromise of speed and accuracy, and it allows R&D scientists to scanthrough large molecular space to triage down and experimentally test
only the most promising chemistries.
Schrödinger’s Materials Science platform leverages the power ofphysics-based simulation, machine learning, and enterprise informatics
to enable the optimization and discovery of effective and selective
catalysts and reactive systems by offering:• Differentiated model builders• Interactive visualization and analysis tools• Highly-efficient density functional theory (DFT) engines• Customizable automated reaction workflows• A collaborative enterprise platform solution

Application Overview
Catalysts• Advance the knowledge of catalytic
mechanisms: Simulate catalytic pathways tofundamentally understand the forces providing
reactivity and selectivity• Improve the lifetime of catalysts: Predictstability and degradation of catalysts
and products• Design and optimize catalysts: Automaticallyrun high-throughput screening of catalysts byleveraging known mechanistic pathways withnovel catalysts• Benefit from inherently chemically agnostic
workflows: Accelerate and automate any
reaction mechanism in both homogeneous andheterogeneous screening workflows2

Reactive Systems• Understand reaction mechanismand pathways: Simulate reaction
thermodynamics, kinetics, reaction rates,and barriers• Accelerate product development:
Automatically predict selectivity and activityof reactions with a library of interesting
substrates and catalysts• Optimize product properties: Computetacticity of polymers with relative reaction
pathway energies• Predict product distribution: Automaticallylocate transition state• Drive innovation in reaction design: Studyeffect of steric, electronic, and ligand on
the reactivity

Team Collaboration and Digital
Data Management• Empower team collaboration: Employ webbased enterprise informatics tools for sharing
experimental and predictive models seamlessly• Amplify research with improved decisionmaking: Rapidly deploy automated reaction
workflows and machine learning models to drive
large-scale predictions and assist novel
design approaches• Improve project management: Accelerate
project communication and collective learning by
capturing, analyzing, and testing new ideas anddata in a centralized platform

3Products
Discover the Schrödinger products that enable your success in the catalysis industry.
MS LiveDesignWeb-based enterprise
informatics formaterials design

AutoTS
Automated workflow to
obtain transition states
and reaction energetics

MS Reactivity
Tools and workflows forautomated catalysis andreactivity discovery

MS Jaguar
Rapid ab initio
electronic structure
package

AutoQSAR
Automated machinelearning tool

MacroModel
Highly efficientmolecular
mechanics tool

Selected Publications
Iron-catalysed Synthesis and Chemical Recycling ofTelechelic 1,3-enchained Oligocyclobutanes.
Chirik P. J. et al. Nature Chemistry 2021, 13, 156-162

Cut-off Scale and Complex Formation in Density
Functional Theory Computations of Epoxy-Amine
Reactivity. Laurikainen P. V. et al. ACS Omega 2021,
6, 44, 29424–29431

Exploring the Mechanism of Cr(VI) Catalyzed
Hypochlorous Acid Decomposition. Busch M et al.
ChemCatChem 2022, e202101850

Decarbonylative Fluoroalkylation at Palladium(II):From Fundamental Organometallic Studies toCatalysis. Sanford M. S. et al. J. Am. Chem. Soc.
2021, 143, 44, 18617–18625

Intramolecular Hydroxyl Nucleophilic Attack
Pathway by a Polymeric Water Oxidation Catalyst
with Single Cobalt Sites. Sun L. et al. NatureCatalysis 2022, 5, 414–429

One-Pot Chemo-bioprocess of PET
Depolymerization and Recycling Enabled by a
Biocompatible Catalyst, Betaine. Kim K. H. et al.
ACS Catal. 2021, 11, 7, 3996–4008

Olefin Metathesis Catalyzed by a Hoveyda–
Grubbs-like Complex Chelated to Bis(2mercaptoimidazolyl) Methane: A Predictive DFT
Study. Martínez J. P. et al. J. Phys. Chem. A 2022,
126, 5, 720–732

Automated Transition State Search and Its
Application to Diverse Types of Organic Reactions.
Friesner R. A. et al. J. Chem. Theory Comput. 2017,13, 11, 5780–5797

Mechanistic Study of Metal–Ligand Cooperativity
in Mn(II)-Catalyzed Hydroborations: Hemilabile
SNS Ligand Enables Metal Hydride-Free Reaction
Pathway. Baker R. T. et al. ACS Catal. 2021, 11, 15,9043–9051

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Learn more: www.schrodinger.com/materials-science

Copyright © 2022 Schrödinger, Inc.

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