Unsupervised learning and pattern recognition in alloy design
Machine learning has the potential to revolutionise alloy design by uncovering useful
patterns in complex datasets and supplementing human expertise and experience. This …
patterns in complex datasets and supplementing human expertise and experience. This …
[HTML][HTML] Efficient alloy design strategy for fast searching for high-entropy alloys with desired mechanical properties
The exponentially large compositional space of high entropy alloys (HEAs) offers more
possibilities for designing alloys with desired properties. However, it also poses challenges …
possibilities for designing alloys with desired properties. However, it also poses challenges …
Viscosity Calculation for Al–Si–Mg–Fe System through CALPHAD Method
Viscosity is a crucial parameter affecting the fluidity of metal melts, which directly influences
the founding properties of Al alloys. However, obtaining viscosity measurement data is …
the founding properties of Al alloys. However, obtaining viscosity measurement data is …
Supervised machine learning for multi-principal element alloy structural design
The application of supervised Machine Learning (ML) in material science, especially
towards the design of structural Multi-Principal Element Alloys (MPEAs) has rapidly …
towards the design of structural Multi-Principal Element Alloys (MPEAs) has rapidly …