Designing the next generation of materials starts at the molecular level.
Our molecular modeling platform enables the prediction of better properties for better materials.
Solutions for diverse materials science R&D applications
- Polymeric Materials
- Consumer Packaged Goods
- Catalysis & Reactivity
- Thin Film Processing
- Energy Capture & Storage
- Pharmaceutical Formulations & Delivery
- Metals, Alloys & Ceramics
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
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
Consumer Packaged Goods
Harness molecular simulation to accelerate innovation for consumer goods
- Predict key performance indicators for consumer products
- Build and simulate complex molecular systems that directly relate to product formulas
- Leverage easy-to-use, automated solutions backed by expert scientific support
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
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
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
Pharmaceutical Formulations & Delivery
Optimize your pharmaceutical at the molecular level with smart, strategic drug formulation
- Characterize and optimize drug formulations and delivery
- Understand drug stability and reactivity
- De-risk your solid form selection process by identifying the most stable polymorph at room temperature
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.
BY INDUSTRY
Oil & Gas
Consumer Packaged Goods
Aerospace
Academics
Automotive
Specialty Chemicals
Biotechs & Pharmaceuticals
Semiconductor
BY TEAM FUNCTION
Computational Chemistry
Experimental Chemistry
Materials Engineering
Research IT
The leading computational platform for molecular design and discovery
Grounded in physics-based molecular modeling
Amplified by state-of-the-art machine learning
Democratized across teams through collaborative enterprise informatics
Featured Product
MS Microkinetics
MS Microkinetics is an effective tool for calculating the overall kinetics of a network of surface reactions, which can be used to optimize reaction conditions and to identify reactivity bottlenecks.
Upcoming Events
- Materials Science
- Webinar
Leveraging atomistic simulation, machine learning, and cloud-based collaborative ideation for display materials discovery
This webinar will explore the union of physics-based simulations, machine learning (ML), and cloud-native collaboration and informatics tools in revolutionizing R&D innovation for display materials.
-
Date & Time:
Aug 7th, 2024 | 10:00 AM PT / 1:00 PM ET / 6:00 PM BST / 7:00 PM CEST
-
Location:
Virtual
Date & Time: 
Location: The world’s most innovative companies use Schrödinger
