Research Data Infrastructure for High-Throughput Experimental Materials Science

Experimental Research Data Quality In Materials Science

In materials sciences, a large amount of research data is generated through a broad spectrum of different experiments. As of today, experimental research data including meta-data in materials science is often stored decentralized by the researcher(s) conducting the experiments without generally accepted standards on what and how to store data. The conducted research and experiments often involv...

The AFLOW standard for high-throughput materials science calculations

The Automatic-Flow (AFLOW) standard for the high-throughput construction of materials science electronic structure databases is described. Electronic structure calculations of solid state materials depend on a large number of parameters which must be understood by researchers, and must be reported by originators to ensure reproducibility and enable collaborative database expansion. We therefore...

Experimental Design for Combinatorial and High Throughput Materials Development

High-quality science requires high-quality open data infrastructure

Resources for data management, discovery and (re)use are numerous and diverse, and more specifically we need data resources that enable the FAIR principles1 of Findability, Accessibility, Interoperability and Reusability of data.

Leveraging e-Science infrastructure for electrochemical research.

As in many scientific disciplines, modern chemistry involves a mix of experimentation and computer-supported theory. Historically, these skills have been provided by different groups, and range from traditional 'wet' laboratory science to advanced numerical simulation. Increasingly, progress is made by global collaborations, in which new theory may be developed in one part of the world and appl...