  Scientific discovery evolves from the experimental, through the theoretical
and computational, to the current data-intensive paradigm. Materials science is
no exception, especially for computational materials science. In recent years,
great achievements have been made in the field of materials science and
engineering (MSE). Here, we review the previous paradigms of materials science
and some classical MSE models. Then, our data-intensive MSE (DIMSE) model is
proposed to reshape future materials innovations. This work will help to
address the global challenge for materials discovery in the era of artificial
intelligence (AI), and essentially contribute to accelerating future materials
continuum.
