Workflows and Principles for Collaboration and Communication in Battery Research

TL;DR

This paper proposes a structured data management system using ontologies and software engineering to enhance collaboration and data sharing in battery research, aiming to accelerate material discovery.

Contribution

It introduces a comprehensive framework combining ontologies, FAIR-compliant databases, and software engineering to improve data curation and reproducibility in battery science.

Findings

Demonstrated applicability of the approach on various electrodes using GITT

Enhanced data interoperability and reproducibility in battery research workflows

Facilitated automated, scalable material discovery processes

Abstract

Interdisciplinary collaboration in battery science is required for rapid evaluation of better compositions and materials. However, diverging domain vocabulary and non-compatible experimental results slow down cooperation. We critically assess the current state-of-the-art and develop a structured data management and interpretation system to make data curation sustainable. The techniques we utilize comprise ontologies to give a structure to knowledge, database systems tenable to the FAIR principles, and software engineering to break down data processing into verifiable steps. To demonstrate our approach, we study the applicability of the Galvanostatic Intermittent Titration Technique on various electrodes. Our work is a building block in making automated material science scale beyond individual laboratories to a worldwide connected search for better battery materials.