The history of machine learning (ML) can be traced back to the 1950 s, and its application in
alloy design has recently begun to flourish and expand rapidly. The driving force behind this …

The paradigm of advanced materials has grown exponentially over the last decade, with
their new dimensions including digital design, dynamics, and functions. Materials modeling …

Aluminum alloys are attractive for a number of applications due to their high specific
strength, and developing new compositions is a major goal in the structural materials …

At GE Research, we are combining “physics” with artificial intelligence and machine learning
to advance manufacturing design, processing, and inspection, turning innovative …

Accurate prediction of the creep life is important during the alloy design and optimization of
nickel-based single crystal superalloys, especially for those with expensive alloying …

Corrosion is a serious problem, which reduces the efficiency and lifespan of various
technologies, such as thermal power plants, aviation, nuclear reactors, etc. It starts from the …

Density functional theory (DFT) calculations and machine learning (ML) methods are used to
establish a relationship between the crystal structures of rare‐earth (RE) disilicates …

The discovery, design, and development of new alloys have long been critical elements of
advanced engineering systems. Challenged by their chemical and structural complexity, this …

In this paper, a state-of-the-art Artificial Intelligence (AI) technique is used for a precipitation
hardening of Ni-based alloy to predict more flexible non-isothermal aging (NIA) and to …

Geometrical model is an important part of the CALPHAD method and has been widely used
for the prediction of physicochemical properties of multicomponent systems. However, most …