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MIT Short Course: Predictive Multiscale Materials Design: June 10-14, 2019

Markus J. Buehler's picture

Computational methods including AI are revolutionizing the materials design world. Today, an engineer or scientist can simply enter the desired properties into a program and the system will manufacture a microstructure that matches the specifications. Algorithms predict which chemical building blocks at the nanoscale can be combined to create advanced materials with superior functions — from ultra-strong, lightweight materials used in the automotive, construction and aerospace industries, to biomaterials used in implants and biomedical devices with the ability to self-heal and regenerate. The goal of this new approach is to construct, in a bottom-up manner, atomically-precise products through the use of molecular design and manufacturing, allowing the fabrication a vast array of designs.

Participants will spend a week at MIT and immerse themselves in interactive lectures, labs and networking with others. Participants will receive an MIT certificate upon successful completion. 

The course covers a variety of topics from theory, modeling and experimental perspectives, including the use of machine learning and artificial intelligence for materials design, additive manufacturing, as well as translational components to connect disparate domains in materials science and engineering.

Fellowships are available for academic participants to reduce the course fee. Interested applicants should email their CV/biosketch to mbuehler@MIT.EDU.  

Registration is now open at http://professional.mit.edu/programs/short-programs/multiscale-materials-design.  

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