AI method radically speeds predictions of materials’ thermal properties
The approach could help engineers design more efficient energy-conversion systems and faster microelectronic devices, reducing waste heat.
Materials science and engineering
New computer vision method helps speed up screening of electronic materials
The technique characterizes a material’s electronic properties 85 times faster than conventional methods.
From steel engineering to ovarian tumor research
Ashutosh Kumar, a materials science and engineering PhD student and MathWorks Fellow, applies his eclectic skills to studying the relationship between bacteria and cancer.
Using AI to discover stiff and tough microstructures
Innovative AI system from MIT CSAIL melds simulations and physical testing to forge materials with newfound durability and flexibility for diverse engineering uses.
MIT engineers develop a way to determine how the surfaces of materials behave
Using machine learning, the computational method can provide details of how materials work as catalysts, semiconductors, or battery components.
This 3D printer can watch itself fabricate objects
Computer vision enables contact-free 3D printing, letting engineers print with high-performance materials they couldn’t use before.
Learning the language of molecules to predict their properties
This AI system only needs a small amount of data to predict molecular properties, which could speed up drug discovery and material development.
Deep-learning system explores materials’ interiors from the outside
A new method could provide detailed information about internal structures, voids, and cracks, based solely on data about exterior conditions.
AI system can generate novel proteins that meet structural design targets
These tunable proteins could be used to create new materials with specific mechanical properties, like toughness or flexibility.