Work

Perspective: Materials informatics and big data: Realization of the “fourth paradigm” of science in materials science

Year: 2016

Type: article

Abstract: Our ability to collect “big data” has greatly surpassed our capability to analyze it, underscoring the emergence of the fourth paradigm of science, which is data-driven discovery. The need for data informatics is also emphasized by the Materials Genome Initiative (MGI), further boosting the emerging field of materials informatics. In this article, we look at how data-driven techniques are playing a big role in deciphering processing-structure-property-performance relationships in materials, with illustrative examples of both forward models (property prediction) and inverse models (materials discovery). Such analytics can significantly reduce time-to-insight and accelerate cost-effective materials discovery, which is the goal of MGI.

Source: APL Materials

DOI: 10.1063/1.4946894

Authors: Ankit Agrawal, Alok Choudhary

Institution: Northwestern University

Language: English

Topic: Machine Learning in Materials Science

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,200

Funders: National Institute of Standards and Technology, Defense Advanced Research Projects Agency, Air Force Office of Scientific Research