Your ability to design the next generation of materials starts at the molecular level.
A digital chemistry platform for modern industrial R&D teams.
Your expert insights + accurate digital predictions + experimental data = technology working for you
Grounded in physics-based modeling
Confidently predict key properties of molecules and de-risk experiments
Amplified by machine learning
Reduce time to insights and explore broad chemical space
Optimized through collaborative enterprise informatics
Democratize access to predictive models across project teams
Broad applications across industrial materials design and development
Organic Electronics
- Accurate atomistic-scale modeling for prediction of key optoelectronic properties
- High-throughput screening for rapid design and discovery of advanced materials
- Leverage easy to use, automated workflows backed by expert scientific support
Polymeric Materials
- Accurate atomistic modeling of chemical reactivity, polymer morphology and more
- Design new polymers, screen formulations & optimize manufacturing
- Leverage easy to use, automated workflows for discovery and optimization
Consumer Packaged Goods
- Accurate molecular modeling for complex formulations of real-life products
- Validated solutions for food & beverage, cosmetics, cleaning products & packaging
- Leverage easy to use, automated workflows backed by expert scientific support
Catalysis & Reactive Systems
- Automated workflows for high-throughput discovery of novel catalysts and reactants
- Accurate modeling to elucidate the details of reactivity, selectivity, and specificity
- Leverage a collaborative enterprise platform for novel materials discovery
Complex Formulations
- Validated workflows for predicting solid state organic crystals and amorphous solid dispersion properties
- Explore bulk and interfacial properties for board applications such as coatings, paints, and drug delivery
- Screen and evaluate a large number of candidate materials and formulations
Alloys, Metals & Ceramics
- Optimize structure and composition of advanced inorganic materials such as metal alloys and ceramics
- Provide insights to the characteristics of inorganic surfaces and interfaces with respect to key mechanical, electronic, magnetic and dielectric properties
- Leverage easy to use, highly-efficient multiscale simulation tools, and machine learnt models backed by expert scientific support
Semiconductors
- Accurate atomistic modeling of surface reactivity to optimize deposition or etch processes
- Validated prediction of precursor volatility by machine learning
- Efficient simulation tools for the design of novel chemicals for materials processing
Energy Capture and Storage
- Accurate atomistic modeling of materials for batteries, fuel cells, & hydrogen storage
- Simulate and analyze critical properties of component materials and interfaces
- Enumerate and explore vast chemical space using streamlined workflows
Digital chemistry in action
“On average, applying Schrödinger’s technology has expedited timelines against a purely experimental approach. As a result, we are adopting digital simulation as part of our innovation strategy. We have enjoyed our collaboration and we are eager to continue to apply the approach across more brands for both innovation and problem-solving.”
—Martin Settle,
Senior Research Manager,
Polymer Science Sustainability & Packaging, Reckitt