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
Materials property information such as composition and thermophysical/mechanical properties abound i...
Improvements in computational resources over the last decade are enabling a new era of computational...
In this big data era, the use of large dataset in conjunction with machine learning (ML) has been in...
Computational capability has enabled materials design to evolve from trial-and-error towards more in...
| openaire: EC/H2020/676580/EU//NoMaDData-driven science is heralded as a new paradigm in materials ...
Data are a crucial raw material of this century. The amount of data that have been created in materi...
Materials discovery is an incessant process and has been the landmark of human progress. This articl...
Herein we review aspects of leading-edge research and innovation in Materials Sciencethatexploits bi...
This chapter addresses the challenges and chances of big-data driven materials science, and it descr...
Materials informatics: a 'hot topic' area in materials science, aims to combine traditionally bio-le...
Materials informatics owes much to bioinformatics and the Materials Genome Initiative has been inspi...
This book addresses the current status, challenges and future directions of data-driven materials di...
Data is a crucial raw material of this century, and the amount of data that has been created in mate...
Propelled partly by the Materials Genome Initiative, and partly by the algorithmic developments and ...
Data mining has revolutionized sectors as diverse as pharmaceutical drug discovery, finance, medicin...
Materials property information such as composition and thermophysical/mechanical properties abound i...
Improvements in computational resources over the last decade are enabling a new era of computational...
In this big data era, the use of large dataset in conjunction with machine learning (ML) has been in...
Computational capability has enabled materials design to evolve from trial-and-error towards more in...
| openaire: EC/H2020/676580/EU//NoMaDData-driven science is heralded as a new paradigm in materials ...
Data are a crucial raw material of this century. The amount of data that have been created in materi...
Materials discovery is an incessant process and has been the landmark of human progress. This articl...
Herein we review aspects of leading-edge research and innovation in Materials Sciencethatexploits bi...
This chapter addresses the challenges and chances of big-data driven materials science, and it descr...
Materials informatics: a 'hot topic' area in materials science, aims to combine traditionally bio-le...
Materials informatics owes much to bioinformatics and the Materials Genome Initiative has been inspi...
This book addresses the current status, challenges and future directions of data-driven materials di...
Data is a crucial raw material of this century, and the amount of data that has been created in mate...
Propelled partly by the Materials Genome Initiative, and partly by the algorithmic developments and ...
Data mining has revolutionized sectors as diverse as pharmaceutical drug discovery, finance, medicin...
Materials property information such as composition and thermophysical/mechanical properties abound i...
Improvements in computational resources over the last decade are enabling a new era of computational...
In this big data era, the use of large dataset in conjunction with machine learning (ML) has been in...