Atom probe tomography (APT) provides three-dimensional compositional mapping with sub-
nanometre resolution. The sensitivity of APT is in the range of parts per million for all …

Prediction of material performance in fusion reactor environments relies on computational
modelling, and will continue to do so until the first generation of fusion power plants come on …

The lack of strength and damage tolerance can limit the applications of conventional soft
magnetic materials (SMMs), particularly in mechanically loaded functional devices …

The Automatic Identification System (AIS) of ships provides massive data for maritime
transportation management and related researches. Trajectory clustering has been widely …

Atom probe tomography (APT) is routinely used for analyzing property-enhancing particles
in the nanometer-size range and below, and plays a prominent role in the analysis of solute …

Life extension of light water reactors requires robust models to predict the embrittlement of
reactor pressure vessel (RPV) steels under long-term neutron irradiation. Embrittlement is …

Abstract High-entropy alloys (HEAs), also called multi-principal-elements alloys, possess
extraordinary mechanical properties, including high strength and hardness, thermal stability …

Data clustering divides the datasets into different groups. Incremental Density-Based Spatial
Clustering of Applications with Noise (DBSCAN) is a famous density-based clustering …

The clustering behaviors in two Al-Mg-Si alloys with and without Cu after different pre-aging
and natural aging conditions were systematically quantified using microhardness …

Cluster analysis is a valuable data analysis and data mining technique. Nature-inspired
population-based metaheuristics are promising search methods for solving optimization …