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Guiding Product Development

Strategic investments across the R&D portfolio

IMPROVED R&D OUTCOMES

Because AI can rapidly assess the likelihood of achieving the desired properties across millions of options, it can be used to:

REDIRECT RESOURCES TO SUCCESSFUL PROJECTS

Assess if a given research direction is likely to be a dead end, so that a project can be cancelled quickly if success is not likely.

Comparison of battery materials using AI

Design Space Visualization for Guiding Investments

Learn how visualizations of achievable properties in different scenarios can be used to guide research.

Determine Research Direction

Evaluate likelihood of positive outcomes across a range of project directions. For example, it can be used to assess which substrate gives the highest likelihood of achieving project goals so that all further experiments are focused on that substrate.

glass

Data-Driven Research Strategy

Learn how data-driven assessments of research directions drive R&D strategy at a global glass manufacturer.

Highlight Potential Risks and Opportunities

Run Scenarios Through the AI Model:

  • What are the maximum achievable material properties with ingredients from various vendors?
  • Will switching to sustainable ingredients impact material properties?
  • Can the product be made at lower temperatures and still meet customer requirements?
  • Which ingredients are essential to achieve market-leading properties in my products?

What if scenario

Understanding the impact of inclusion of rare earth metals on battery cathode performance

James Peerless, Emre Sevgen, Stephen Edkins, Jason Koeller (Citrine Informatics) et al. “Design space visualization for guiding investments in biodegradable and sustainably sourced materials” MRS Comms (2020).