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Economical Machine-Learning to Accelerate Materials Discovery

The increasing popularity of 3D printing for manufacturing all kinds of products, from personalized medical devices to economical homes, has generated additional demand for new 3D printing materials engineered for very specific applications.

Accelerating the Discovery of New Materials for 3D Printing

New machine-learning system costs less, generates less waste, and can be more innovative than manual discovery methods

Accelerating the discovery of new materials for 3D printing

The growing popularity of 3D printing for manufacturing all sorts of items, from customized medical devices to affordable homes, has created more demand

Accelerating the discovery of new materials for 3D printing

Accelerating discovery of new materials for 3D printing

The growing popularity of 3D printing for manufacturing all sorts of items, from customized medical devices to affordable homes, has created more

MIT-Developed System Optimizes the Shape of Robots

MIT-Developed System Optimizes the Shape of Robots Written by AZoRoboticsDec 1 2020 So, you need a robot that climbs stairs. What shape should that robot be? Should it have two legs, like a person? Or six, like an ant? Choosing the right shape will be vital for your robot's ability to traverse a particular terrain. And it's impossible to build and test every potential form. But now an MIT-developed system makes it possible to simulate them and determine which design works best. You start by telling the system, called RoboGrammar, which robot parts are lying around your shop -- wheels, joints, etc. You also tell it what terrain your robot will need to navigate. And RoboGrammar does the rest, generating an optimized structure and control program for your robot.