A research team led by Dr. Se-Jong Kim and Dr. Juwon Na of the Materials Data Management Center in the Materials Digital Platform Division together with a research team led by Professor Seungchul Lee ...

In recent years, additive manufacturing technology has attracted considerable attention from various stakeholders. Among the different techniques, Arc wire-based direct energy deposition (DED) has ...

A research team led by Kyung Mun Min and Seonghwan Choi of Materials Processing Research Division (Korea Institute of ...

Researchers have developed a new microscopy technique that maps material microstructure in three dimensions; results demonstrate that the conventional method for predicting materials' properties under ...

MIT researchers say they have found a more efficient way to train machine learning models that predict how complex metal alloys will behave.

A method that can automatically identify and quantify materials’ microstructure from microscopic images has been developed by the research teams led by Professor Seungchul Lee of POSTECH and Dr.

Which factors determine how quickly a battery can be charged? Microstructural models have helped researchers discover and investigate new electrode materials. When sodium-nickel-manganese oxide is ...

Visit NAP.edu/10766 to get more information about this book, to buy it in print, or to download it as a free PDF.

A 70-year-old model used to predict the microstructure of materials doesn’t work for today’s materials, say Carnegie Mellon University researchers in Science. A microscopy technique developed by ...