An automated workflow
for rapid large-scalecomputational screening
to meet the demandsof modern catalyst
development
As market demands evolve, R&D scientists across industries fromconsumer packaged goods to oil & gas, automotives and polymers, facesimilar challenges in developing and optimizing the next-generationof catalysts to reduce energy requirements, eliminate unwanted sideproducts and improve the selectivity and reactivity of reactions.

Materials

First-principles simulation has become a reliable
tool for the prediction of structures, chemicalmechanisms, and reaction energetics for thefundamental steps in homogeneous catalysis.
Details of reaction coordinates for competing
pathways reveal a fundamental understanding ofobserved catalytic activity, selectivity, and specificity.
Such predictive capability raises the opportunity toaccelerate computational discovery and design of
new single-site catalysts with enhanced properties.
However, along with the rapid technology
development and materials innovation,
challenges persist:• The complexity of chemical reactions and theneed for associated computational research has
increased as demands for innovation increase• The traditional rate of catalysts discovery islimited and unable to keep pace with demands
for improved catalysts• Existing computational frameworks are manuallyintensive with limited scale, and require a highlevel of expertise and training• Cataloging and maintaining databases of novel
catalysts is challenging and time-consuming
To democratize the fundamental understanding,design, and discovery of novel catalysts,
Schrödinger developed an automated reaction
workflow called AutoRW. AutoRW combines theelements of enumeration, mapping, organization,and output needed for high-throughput screeningof catalysts, reagents, and substrates, requiring
a pre-built reaction coordinate, novel chemicalfragment, and any R-Groups for enumeration.
By automating processes and computing thereaction coordinates, rates, energies, transition
states, structures, properties, for each reaction,
AutoRW streamlines the process of large-scalecomputational catalyst screening.

Create reaction workflow input andstructure library

R-Groups and novel fragments enumerate

Swap enumerated novels onto
known reactions

Run each reaction workflow

Compute reaction rates, energy profiles,
structure properties, etc. and run analysisOutput structures and properties+Known Transition
StateNew Candidate
Reactant

Known Transition
State mapped onto
New Reactant

AutoRW workflow

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Solution: AutoRW for
automated large-scale
catalysts screening

Case Studies: How AutoRW
Accelerates Innovation in
Catalysis and Reactivity• Simplified, customizable workflows thatenhance reproducibility and predictability

Understanding the Effects of Catalysts
Selectivity on Polypropylene Tacticity• Easy to use for both expert and non-expert
computational users

Production of olefin-based polymer products
has surpassed 100 million tonnes. Of these,
polypropylene is the second most produced
polymer. Its physical properties are directly
influenced by the regularity of adjacentstereocenters. This regularity, or tacticity, isdetermined by the kinetic selectivity and thecontrol of incorporation of α-olefin monomer
allows for fine-tuning of its physical properties. In
this project, scientists studied 13 isotactic catalysts
using AutoRW to fundamentally understandthe adjacent stereoselectivity of polypropylene.
The results were in good agreement with theexperimental selectivities (R2 = 0.8). This quick
and accurate approach allows for optimizedpolypropylene design and synthesis with target
structures and properties.

• Increased productivity for highly-complex
problems and challenges• Enhanced coverage where conformers could be
missed by manual methods• Improved organization of files and properties
to save time and reduce errors• Dedicated scientific & technical supportand vast learning resources

Front:

Top-Side:

Experimental Selectivity: 0.991
Computational Selectivity: 0.997

3Screening Epoxy Amine Reactions for Efficient
High-performance Polymer Design

Epoxy amine crosslinking reaction. The initial reaction occurs between
a primary amine and a single epoxide. The resulting product contains asecondary amine that can further react with additional epoxide.
Thermoset polymers have gained interest in recent
years due to their favorable thermomechanicalproperties for applications in aerospace,automotive, defense and high performanceathletics equipment. While thermosets are very
versatile, the cost to incorporate these polymers
into new materials is high. Accelerating thedevelopment process pipeline would not only
reduce costs, it would also decrease accumulationof thermoset waste which is difficult to recycle.
Towards this end, the scientists studied a libraryof 12 amines and 21 epoxides to build a relative
reaction barrier heat map. Each epoxy/aminecombination was subjected to the Reaction
Workflow to locate all stationary points in thereaction as well as compute energetic barriers for
all reaction steps, enabling efficient design andsynthesis of high-performance polymers.

• 252 Epoxy/Amine combinations• ~240 conformations per combination• 2 DFT calculations per conformation• Primary & secondary reaction pathways• 2 AutoRW jobs
• 504 Reaction Workflow subjobs• ~480,000 DFT calculations

4Investigating Comonomer Selectivity for Optimized
Block Copolymerization
Block copolymers have unique properties that include
high strength, flexibility, and melting temperature.
Their physical properties are directly influenced by thepolymer block length and distribution, which are thendetermined by the kinetic comonomer selectivity andchain shuttling agent activity. The comonomer selectivity
is influenced by both the catalyst and existing polymer
product. In this project, scientists ran AutoRW to screen
and test 35 catalyst derivatives with different polymer
substrates to understand the effect of catalysts oncomonomer selectivity for different copolymerization
reactions. This approach enables quick screening of
catalysts and substrates to design block copolymers withtarget structures and properties.

Computed monomer selectivities with existing linear and branched polymer attached to the catalyst. Positive selectivities denote preference for ethene
insertion and negative selectivities denote propene insertion.

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Empower advanced catalysts discovery
across entire R&D project teams
As the modern R&D processes evolve in a morecollaborative and globalized manner, tremendous
effort has been put into data storage and sharing,communication and project management acrossteams and geographies. Enterprise scale informatics
platforms for R&D have been developed to break thesilos and barriers, and have been adopted by many
companies across several molecular
design industries.

Schrödinger’s LiveDesign is a powerful, webbased informatics and molecular design platformthat enables teams to rapidly advance materials
discovery projects by collaborating, designing,experimenting, analyzing, tracking, and reportingin a centralized platform. By incorporating AutoRW
into LiveDesign, scientists can get the most benefits
from both.

The benefits are clear: project teams can work
across departments and sites, across geographies
and time zones, and even across companies, withlive sharing of all the project data of experiments,
designs, processes, simulations, etc.; Teams canshare, analyze and communicate data seamlessly
and make rapid decisions, accelerating thecollaboration and progress of the projects.
Enterprise informatics platforms also simplify andoptimize data management for organizations,eliminating the chaos of storing large data on
computer drives and transferring data between
teams and during team or personnel changes.

6AutoRW in LiveDesign for enterprise-wide time andcost savings• Streamlined automated enterprise solution for catalysis
and reactivity• Scalable to satisfy the need of large global organizations• Integrated with advanced machine learning systems• End-to-end collaborative discovery between chemists,
modelers and engineers on a single web-based platform• Live sharing of ideas and results for rapid
decision-making• Intuitive cheminformatics: visualization, data andmodel analysis for experimental and computational
data simultaneously
Using LiveDesign, the team can collaborate and virtually screenover 2000 catalysts per year, while a single modeling user
can only screen about 150 catalysts annually. Employing theautomated enterprise-scale workflows lead to much higher cost
efficiency and rates of success.

MethodSingle
Experimentlist

SingleModeling UserEnterprise
Deployment

Synthesis
and Testing

$$$$$

$Max
Throughput
Per Year50-100150

2000+Cost
Efficiency

1~5~12• Cost includes employee salary, lab costs, analytical testing, licensing, and cloud costs of$1k for ~34k CPU hours Reaction Workflow job.
• ”Max Throughput” is based on available licensing, computational resources, and budget.
• “Cost Efficiency” is the cost savings for each catalyst screened vs experimental.

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Conclusions
Scientists across industries are entering a newparadigm for catalysis research. Research historically
based on pure experimental trial-and-error ismoving to computationally-driven workflows. Rapid
technology development and evolving project
collaborations demand for simplified and automatedworkflows at enterprise scale. Schrödinger’s AutoRW
and LiveDesign enable rational catalyst design in an
automated, accelerated and collaborative manner
on a single web-based platform, which are easy touse and deploy across teams and organizations.
The tools empower scientists to solve high-level
challenges of even more complex reactions andcatalysis systems with reduced time and cost while
enhancing predictability and productivity.

Discover the Schrödinger products thatenable your success in catalysis research:
MS Live DesignWeb-based enterprise informatics for materials design
MS Jaguar
Rapid ab initio electronic structure package
MS Reactivity
Tools and workflows for automated catalysis andreactivity discovery
AutoTS
Automated workflow to obtain transition states andreaction energetics
AutoQSAR
Automated creation and application of predictive QSAR/QSPR
models following best practices

Contact us: sales@schrodinger.com
Learn more: www.schrodinger.com/materials-science

Copyright © 2022 Schrödinger, Inc.

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