Experiment Design Frameworks for Accelerated Discovery of Targeted Materials Across Scales

2019 Talapatra, Boluki, Honarmandi, Solomou, Zhao, Ghoreishi, Molkeri, Allaire, Srivastava, Qian, Dougherty, Lagoudas and Arryave. Over the last decade, there has been a paradigm shift away from labor-intensive and time-consuming materials discovery methods, and materials exploration through informatics approaches is gaining traction at present. Current approaches are typically centered around the idea of achieving this exploration through high-throughput (HT) experimentation/computation. Such approaches, however, do not account for the practicalities of resource constraints which eventually result in bottlenecks at various stage of the workflow. Regardless of how many bottlenecks are eliminated, the fact that ultimately a human must make decisions about what to do with the acquired information implies that HT frameworks face hard limits that will be extremely difficult to overcome. Recently, this problem has been addressed by framing the materials discovery process as an optimal experiment design problem. In this article, we discuss the need for optimal experiment design, the challenges in it's implementation and finally discuss some successful examples of materials discovery via experiment design.

Talapatra, A., Boluki, S., Honarmandi, P., Solomou, A., Zhao, G., Ghoreishi, S. F., ... Arroyave, R.

Talapatra, Anjana||Boluki, Shahin||Honarmandi, Pejman||Solomou, Alexandros||Zhao, Guang||Ghoreishi, Seyede Fatemeh||Molkeri, Abhilash||Allaire, Douglas||Srivastava, Ankit||Qian, Xiaoning||Dougherty, Edward R||Lagoudasi, Dimitris C||Arroyave, Raymundo

Experiment Design Frameworks for Accelerated Discovery of Targeted Materials Across Scales Academic Article