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AI and Computational Materials

Cornell University_011121C
[Cornell University]

Simulate Today, Innovate Tomorrow: 

The Future of Materials Science


- Overview

Computational materials science uses computers to understand and predict the properties and structures of materials. It's based on fundamental physics, thermodynamics, kinetics, mechanics, and numerical algorithms. 

Artificial intelligence (AI) uses sophisticated algorithms and data-driven models for problem solving and decision making. AI and computational materials science can be combined to:

  • Accelerate discovery and development: AI can improve the efficiency of hypothesis generation, testing, and data analysis.
  • Gain fundamental understanding: AI and machine learning (ML) models can extract patterns at spatiotemporal scales that were previously impossible.
  • Open new windows: Computational materials science and advanced experimental techniques can open new windows into the materials world.


Please refer to the following for more details:



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