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Designing the next generation of materials starts at the molecular level.

Our molecular modeling platform enables the prediction of better properties for better materials.

Materials science

Solutions for diverse materials science R&D applications

Polymeric Materials

Polymeric Materials

Understand and predict product performance through simulations of polymers at molecular and atomic scale.

  • Accurately predict chemical reactivity, polymer morphology, and key physicochemical properties
  • Design new polymers, screen formulations, and optimize manufacturing
  • Leverage easy to use, automated workflows for discovery and optimization
Organic Electronics

Organic Electronics

Discover optimal organic electronic materials with good conductivity, mechanical and thermal stability, and suitable for fabrication.

  • Accurately predict key optoelectronic properties
  • Run high-throughput screening for rapid design and discovery of advanced materials
  • Leverage easy-to-use, automated workflows backed by expert scientific support
Catalysis and Reactivity Lithium EC Cluster

Catalysis & Reactivity

Accelerate the discovery of the next generation of catalytic and non-catalytic processes.

  • Run automated workflows for high-throughput discovery of novel catalysts and reactants
  • Elucidate the details of reactivity, selectivity, and specificity
  • Leverage a collaborative enterprise platform for novel materials discovery
Thin Film Processing

Thin Film Processing

Optimize atomic level processing for the semiconductor industry and improve device performance.

  • Accurately predict surface reactivity to optimize deposition or etch processes
  • Validated prediction of precursor volatility by machine learning
  • Leverage efficient simulation tools for the design of novel chemicals for materials processing
Energy Capture Storage

Energy Capture & Storage

Accelerate the development of cleaner, lighter, safer, and more energy-efficient materials for batteries, fuel cells and photovoltaics.

  • Predict key properties for batteries, fuel cells, photovoltaics, and hydrogen storage R&D
  • Simulate and analyze critical properties of component materials and interfaces
  • Enumerate and explore vast chemical space using streamlined workflows
Complex Formulations

Complex Formulations

Optimize the properties of end formulation products across the pharmaceutical, consumer product, plastic, composite, and petrochemical industries.

  • Predict key properties with automated workflows
  • Accelerate ingredients selection with high-throughput screening and machine learning
  • Identify risks and predict performance in processing
Metals, Alloys & Ceramics

Metals, Alloys & Ceramics

Enable the design of high-performance inorganic materials with highly efficient multiscale simulations and cheminformatics machine learning models.

  • Accurately predict key properties (structures, morphologies, and compositions) for inorganic materials
  • Enhance your materials analysis capabilities

Use Cases

Explore how teams can apply Schrödinger technology to accomplish their work across industries.

Use Cases by Industry
BY INDUSTRY
Oil & Gas
Consumer Packaged Goods
Aerospace
Academics
Automotive
Specialty Chemicals
Biotechs & Pharmaceuticals
Semiconductor
Use Cases by Team Functions
BY TEAM FUNCTION
Computational Chemistry
Experimental Chemistry
Materials Engineering
Research IT
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The leading computational platform for molecular design and discovery

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Computational platform for molecular design and discovery
Grounded in physics-based molecular modeling
Grounded in physics-based molecular modeling
Amplified by state-of-the-art machine learning
Amplified by state-of-the-art machine learning
Democratized across teams through collaborative enterprise informatics
Democratized across teams through collaborative enterprise informatics

Upcoming Events

  • Materials Science
  • Conference

Tire Technology Expo

Schrödinger is excited to be participating in the Tire Technology Expo taking place on March 19th – 21th in Hannover, Germany. Join us for a presentation by Eli Sedghamiz, Senior Scientist II at Schrödinger, titled “Tire polymer formulation from molecules to performance properties.” 

  • calendar icon dark Date & Time: Mar 19th-21st, 2024
  • location icon dark Location: Hannover, Germany
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FEATURED CourseMolecular modeling for materials science applications: course bundle

Molecular modeling for materials science applications: course bundle

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