Ever‐increasing demands for superior alloys with improved high‐temperature service
properties require accurate design of their composition. However, conventional approaches …

This work utilized computer vision and machine learning techniques to predict both
qualitative characteristics and quantitative values, from SEM images of Ti–6Al–4V fracture …

The micro-and macroscopic fatigue crack growth (FCG) rates of a wide class of structural
materials were analyzed and it was concluded that both rates coincide either during high …

Grain boundaries play an important role in governing the mechanical and physical
properties of polycrystalline materials. Therefore, quantitative analysis of grain structure is …

The foundation of materials science and engineering is the establishment of process–
microstructure–property links, which in turn form the basis for materials and process …

Recent advancements in machine learning (ML) techniques have opened up new
opportunities for using image analysis to solve materials science and engineering problems …

Fractographic analysis poses a significant challenge for field researchers without
specialized training in fractography. To address this issue, this study introduces a …

In this experiment, Ni–P nanoparticles were deposited (ED) on SiC micro-and nanoparticles
with different parameters. Our goal was to successfully prepare metal deposits and develop …

Ductile fracture occurs with large plastic deformation prior to fracture and is primarily
characterized by voids of varying sizes. In this work, a new approach based on machine …

Recently, there has been an increased interest in additive manufacturing (AM) for its
potential to reduce costs and lighten the weight of manufactured parts. However, materials …