In Silico Material Discovery

Use in silico models to optimize new materials discovery & replace costly or non-sustainable ingredients.

In silico modeling means a lab can virtually screen properties and predict the performances of raw materials and ingredients.  Additionally, it can encapsulate and automate best practices by utilizing reusable protocols.  This maximizes understanding of how raw materials or ingredients will behave once it has been handed off from Discovery.  

With the In Silico Material Discovery solution, you can build models of different materials: Polymers, Catalysts, Crystals, Nano-structured materials to name a few.  Predict the properties of these properties virtually using validated techniques like quantum mechanics, classical simulations and mesoscale modeling.  This facilitates the rapid development of predictive models/machine learning to understand your material behavior.  

With In Silico Material Discovery, you can:

  • Innovate faster using 'virtual screening' of candidate material variations
  • Predict and understand the relationships of a material's atomic and molecular structure with its properties and behavior
  • Solve key materials and chemical research problems with an integrated, multi-scale modeling environment
  • Shorten time to market while reducing cost and risk