Deep learning (DL) is one of the fastest-growing topics in materials data science, with
rapidly emerging applications spanning atomistic, image-based, spectral, and textual data …

Alloy modelling has a history of machine-learning-like approaches, preceding the tide of
data-science-inspired work. The dawn of computational databases has made the integration …

The age of cognitive computing and artificial intelligence (AI) is just dawning. Inspired by its
successes and promises, several AI ecosystems are blossoming, many of them within the …

Given the emergence of data science and machine learning throughout all aspects of
society, but particularly in the scientific domain, there is increased importance placed on …

The fields of machining learning and artificial intelligence are rapidly expanding, impacting
nearly every technological aspect of society. Many thousands of published manuscripts …

For many decades, experimental solid mechanics has played a crucial role in characterizing
and understanding the mechanical properties of natural and novel artificial materials …

Industry 4.0 promotes the transformation of manufacturing industry to intelligence, which
demands advances in materials, devices, and systems of the construction industry …

Although high-entropy materials are attracting considerable interest due to a combination of
useful properties and promising applications, predicting their formation remains a hindrance …

Due to its unique properties, high-pressure aluminum die-casting parts are used quite often,
especially in the automotive industry. However, die-casting is a process which requires non …

Microstructural characterization and analysis is the foundation of microstructural science,
connecting materials structure to composition, process history, and properties …