3. AI for Mechanical Design, the Key to Thwarting Quantum Hackers, Making Better Batteries

The Next Byte Podcast · 2 Feb 2021 · 16m

AI in practice: one real use of AI described

What this episode covers

Daniel Scott Mitchell and Farbod Moghaddam discuss three recent engineering breakthroughs, starting with Dr. Barati Farimani’s team at Carnegie Mellon University, who developed an AI algorithm to select materials for mechanical design by combining experimental data with molecular physics simulations. They then cover research from Eindhoven University of Technology on quantum key distribution, a method to create unhackable communication channels by detecting intrusion attempts in real-time. Finally, they examine Dr. Lauren Marbella’s work at Columbia University, which adds potassium to lithium-ion batteries to prevent microstructure growth, thereby improving safety and extending battery life for devices like phones and electric vehicles.

AI in practice

Where this conversation describes AI being used to build or deliver a product. Part of the AI in practice tracker.

DesignCarnegie Mellon University algorithm

An AI algorithm uses experimental and simulated molecular data to predict material properties, allowing designers to select the correct material for a specific application without extensive manual testing.

“This team from Carnegie Mellon have developed an algorithm to help engineers pick the right material based on what they're going to use it for. Um, and they fed it data from experiments and then also from simulations to allow to their material library to be like a lot wider than current algorithms are used.”

Speaker 1 · Hear it at 0:01

Mentioned

Companies
Carnegie Mellon University, Eindhoven University of Technology, Columbia University, AutoDesk
Products
Samsung Note

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