Mechanical engineering has traditionally relied on physics, mathematics, and empirical knowledge to design and optimize systems. Machine learning (ML) introduces powerful tools that can complement ...
A new computational method allows modern atomic models to learn from experimental thermodynamic data, according to a ...
Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...
Microelectromechanical systems (MEMS) electrothermal actuators are widely used in applications ranging from micro-optics and microfluidics to nanomaterial testing, thanks to their compact size and ...
Electron density prediction for a four-million-atom aluminum system using machine learning, deemed to be infeasible using traditional DFT method. × Researchers from Michigan Tech and the University of ...
In the past decade, advances in algorithms, computer architecture and processing power have led to giant strides in the development of computers that are capable to learn by themselves how to solve a ...
The world is changing rapidly with the development of information technologies. Mechanical engineering is no exception. Digital technologies are being introduced into all areas of production, ...
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