INDUSTRY APPLICATION

Driving Innovationin Polymer R&D
with MolecularSimulation &Machine Learning
R&D scientists across broad industries from aerospace toelectronics face challenges in developing the next-generationof polymers and composites with high-performance,
multifunctional capabilities that also meet society’s demands
for miniaturization and environmental sustainability.

Solution Overview
Chemical reactivity, physical morphology, and polymer physics drive
the behavior of polymers and soft materials. Schrödinger’s Materials
Science platform provides a unique combination of capabilities for thedesign and optimization of polymers, including:• Differentiated model builders• Extremely efficient, GPU-powered molecular dynamics (MD) engine• Automated thermophysical and mechanical response workflows• Chemically adaptable cross-linking workflows• Analysis tools for the simulation, optimization, and discovery
of novel polymers including linear, crosslinked, elastomers,dendrimers, and copolymers
Schrödinger’s tailored solutions for molecular modeling of polymers,
mixtures, and composites can reduce cost and risk, shorten timelinesand drive innovation in a broad range of industries.

Industries and Applications
Automotive and Aerospace• Optimize polymer formulation properties:
Model water transport, uptake andmorphological stability in polymer composites
using multistate simulations• Accelerate chemical design to properties
critical to product and processing constraints:
Identify the unique combinations of epoxy-amine
reactions for target properties using highthroughput screening• Accelerate the manufacturing process
pipeline: Predict polymer gelling during
manufacturing process• Design greener products that are moreenvironmentally sustainable: Simulate
and predict properties of high-performanceresins with bio-based materials, and automatediscovery of new biomaterials

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CPG Packaging andFormulation• Develop environmentally sustainable
packaging: Study interfacial interactions
between packaging materials and consumer
goods, and simulate water uptake for barrier
design and performance• Optimize polymer formulation: Quantify
the diffusion of additives in polymer
packaging materials• Minimize production waste: Understandthe potential causes and impact of polymer
production deviations• Innovate with natural materials: Explore
active, recyclable, and bio-based materials
through molecular simulation• Reduce processing cost: Evaluate new
formulations for potential manufacturing
challenges

Specialty Polymers• Speed up decision-making on catalyst
selection for raw materials production:
Simulate and understand the catalysis
mechanisms, selectivity, and reactivity of epoxy
amine, urethane, and other reactions• Optimize the design of high-performancepolymers: Predict glass transition,
thermal stability, and thermal expansion
with new polymers• Drive innovation in polymer reactions:
Predict curing kinetics and processing properties3

Electronic Packaging• Identify thermal/mechanical performanceissues early in design: Simulate coefficient ofthermal expansion for packaging polymers• Optimize chemical stability: Simulate interactionsof packaging polymers with processing solvents
and water to predict stability in use• Design new monomers for improved
performance: Predict design drivers like Dk, Df
and refractive index with physics-based simulations
and machine-learned models

Batteries• Understand mechanisms at molecular level:
Predict electrolyte degradation reaction mechanisms
and control energetics to understand the formationof functional solid electrolyte interphase layers atanodes (SEI) and cathodes (CEI)• Identify best-performing battery materials:
Perform high-throughput screening of anode,cathode, electrolyte and additive materials toidentify best chemistries for development of nextgeneration batteries• Optimize electrolyte design: Simulate interatomic
interactions and transport of ions in liquid andpolymer electrolytes

4Pharmaceutical Formulation• Optimize drug carrier design: Evaluate thesolubility/miscibility of drugs with different
polymeric carriers or barriers• Optimize drug formulations: Visualize
and characterize pH-dependent polymericsurfactant and drug interactions in solution andprecipitation inhibition behavior• Drive effective drug delivery: Simulate
drug release profiles from amorphous solid
dispersions into solution

Team Collaboration and Digital
Data Management• Empower collaboration: Employ web-based
enterprise informatics tools for sharing
experimental and predictive models seamlessly• Amplify research: Rapidly deploy of machinelearning models to drive 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

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Products
Check on the products that enable your success in the polymer industry.

Desmond

AutoQSAR

Highly efficient Molecular
Dynamics (MD) tool

Automated machinelearning tool

MS CG

MS LiveDesign

MD tool with coarse-grained(CG)/mesoscopic sites

Web-based enterprise
informatics formaterials design

OPLS4

MS Dielectric

Advanced modern force field

Combined QM & MD
workflows for dielectric
properties

MS Transport

MS Penetrant Loading

MD workflows for shear
viscosity, and the isotropic
and anisotropic diffusion
coefficients

MD tool for predictionof water or small
penetrant uptake

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Selected Publications
Melt-state degradation mechanism of poly(ether ketone ketone): the role of branching on
crystallization and rheological behavior.
Wiggins J. et al. Polym. Degrad. Stab. 2022, 200,109968

Photophysical Properties of Cyclometalated
Platinum(II) Diphosphine Compounds in the Solid
State and in PMMA Films.
Anderson C. M. et al. ACS Omega 2021, 6, 42,28316–28325

Atomistic Molecular Dynamics in PEO/PMMABlends Having Significantly Different GlassTransition Temperatures.
Habasaki J, Int. J. Appl. Glass Sci,
doi.org/10.1111/ijag.16553

High-Throughput Molecular Dynamics Simulations
and Validation of Thermophysical Properties ofPolymers for Various Applications. Afzal. A et al.
ACS Appl. Polym. Mater. 2021, 3, 2, 620–630
Fundamental Limits to the Electrochemical
Impedance Stability of Dielectric Elastomers in
Bioelectronics.
Floch P. L. et al. Nano Lett. 2020, 20, 1, 224–233

Experimental Investigations of AlMg3 Components
with Polyurethane and Graphene Oxide
Nanosheets Composite Coatings, after Accelerated
UV-Aging.
Murariu A. C. et al. Molecules 2022, 27, 1, 84
Polycyanurates via Molecular Dynamics: InSitu Crosslinking from Di(Cyanate Ester) Resinsand Model Validation through Comparison toExperiment.
Moore L. M. J. et al. Macromolecules 2021, 54, 13,6275–6284

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

Copyright © 2022 Schrödinger, Inc.

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