The Role of Digital
Chemistry Across thePolymer Supply Chain
Molecular modeling and simulation tools have proven effective inmaterials development and are increasing in use throughout thepolymer industry, from raw materials suppliers to end productmanufacturers. Computational workflows also open new avenues
for developing polymers with improved recyclability. Physics-based
simulations offer reliable predictions of structures, morphologies,properties, and chemical reactivity for polymers. Recent advances inmachine learning, deep learning, and enterprise informatics platforms
have accelerated the speed, accuracy, and automation of novelmaterials and solutions discovery. A paradigm shift to computer-driven
molecular design is occurring throughout the industry.

RAW MATERIAL SUPPLIER

Offer Optimized
Raw Materials

ProvideDetailed
Requirements

POLYMER COMPOUNDER

Offer
Optimized
Formulations

Provide Specific
Formulation
Requirements

END PRODUCT MANUFACTURER

Vision of a digital chemistry
catalyzed polymer supply chain:
Raw Materials Suppliers: Employ atomistic
simulations to improve understanding and predict
properties of downstream products; offer optimized
raw materials to compounders.
Polymer Compounders: Use atomistic simulations
to understand formulation chemistry and predict
properties; provide detailed requirements to raw
materials suppliers and offer optimized products toend product manufacturers.
End Product Manufacturers: Leverage atomistic
simulations to predict the performance of final
products and quickly identify causes of failure; give
specific formulation requirements to compounders.

Solution Overview
Schrödinger’s Materials Science platform offers
tailored solutions for research and businessthroughout the polymer supply chain, withdifferentiated model builders, efficient simulationengines accelerated by GPU computing power,
automated thermophysical and mechanicalresponse workflows, and accurate analysis tools.

• Broad molecular simulation and property
prediction tools for: Thermal Properties,
Mechanical and Dielectric Properties, Reactivity
and Kinetics, Aggregation in Polymer Production,
Solvent Sensitivity, Gas, Ion, Additive Diffusivity,
Phase Morphology and SAXS Scattering, Semicrystalline Morphology• Applicable to all polymer types: thermoplastic
homo and copolymers, crosslinked, elastomers,
and dendrimers• Intuitive user interface with automated workflows
for experts or non-experts• Dedicated scientific/technical support and vastlearning resources

Digital Chemistry Value Across Polymer
Supply Chain (Example: Transportation Industry)

13

Raw Materials Suppliers

End Product Manufacturers

Suppliers of petrochemical and chemical
feedstocks, additives, and various monomers
and resins

Processors of resins/formulations who make theminto finished products on the market

Design new chemistries from alternative
sources and discover new applications throughsimulating downstream products properties• Predict polymer crosslinker performance incomposite matrix resins such as epoxy-amineand cyanate esters• Simulate the interaction between thermoplastic
styrene-butadiene and crosslinkers
Speed decision making for catalyst selection inraw materials production• Simulate and understand the catalysis
mechanisms, selectivity, and reactivity of epoxy
amine, urethane, and other reactions
Develop alternative greener raw materials thatare more environmentally sustainable• Simulate the impact of degradation on modulus
for a chemistry of focus

Enable reliable decision-making throughpredictive modeling of end product properties• Predict tire materials performance with different
additives and cross-linkers
Obtain best chemistry from upstream suppliers
by targeted chemical design to properties
critical to product and processing constraints• High-throughput screening of epoxy-amine
reactions to identify the unique combinations
for target properties
Accelerate the manufacturing process pipeline• Predict polymer gelling during
manufacturing process
Quickly screen and identify potential causes
and impacts of manufacturing and material
source deviations• Predict sensitivity of matrix to cleaning solvents
Design greener products that are moreenvironmentally sustainable

2

Polymer Compounders• Simulate and predict properties of highperformance resins with bio-based materials
and automate discovery of new biomaterials

Suppliers who prepare polymer formulations bymixing or/and blending polymers and additives into
process-ready products

4Predict the performance of alternative raw
materials in formulations and end products

Polymer Recycling• Predict glass transition, thermal stability, andthermal expansion with new polymers

Research and design for recyclability throughout
the polymer supply chain• Quantify the diffusion of additive in polymers• Understand water transport and morphologicalstability of polymer formulations
Efficiently optimize formulation properties• Predict and track water uptake inpolymer composites• Predict curing kinetics and processing properties
Develop greener formulations that are moreenvironmentally sustainable• Simulate and screen for optimal formulation
with new bio-based chemistry

Design polymers for recyclability• Predict selectivity of chemical recycling reaction
Expand use of recycled materials• Simulate impact of recycled polymers
in packaging
Determine impact on product with use ofrecycled material• Screen for property changes with recycling
driven microstructure changes

About Schrödinger
Schrödinger is transforming the way materials
are discovered. Schrödinger has pioneered aphysics-based software platform that enables
discovery of high-quality, novel molecules formaterials applications more rapidly and atlower cost compared to traditional methods.
Learn how digital chemistry is driving innovation
across materials science industries

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

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