Using artificial intelligence and machine learning to enhance materials modeling
Simcenter Culgi handles data scarcity with physical-chemistry expertise, transforms domain knowledge into valuable insights using AI methods, and screens chemical space to narrow down potential candidates.
Simcenter Culgi uses one-of-kind advantages to address and resolve typical challenges seen in smart materials modeling
AI/ML models may be missing essential data in the later engineering and production stages, causing time-to-market delays. Simcenter Culgi adds critical automation to the design and development stages, increasing trust in data-driven approaches that address complex physical-chemistry constraints and objectives.
The AI/ML in Simcenter Culgi can:
Reduce computations to focus on a crucial chemical space
Replace physical testing with AI, based on chemistry-informed virtual simulations
Develop new digitally upgraded materials using a range of preliminary lab data
Settle OEM manufacturing and logistics regulations for faster time-to-market
Download and read the white paper for more information.