Neural networks are emerging as transformative tools in the field of material sciences by providing new avenues for constitutive modelling. Integrating advanced algorithms with physics-based insights, ...

An illustration of the machine learning model framework, showing its application in predicting the electro-mechanical behavior of CNTs/PDMS composites. As featured in National Science Open, the ...

Data-driven science represents a transformative paradigm in materials science. Both data-driven materials science and informatics encompass systematic knowledge extraction from materials datasets.

Publishing in the International Journal of Extreme Manufacturing (IJEM), researchers from Harbin Institute of Technology, Huazhong University of Science and Technology, Guizhou University and ...