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Workflows and Principles for Collaboration and Communication in Battery Research
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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.
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Cited by 1 Pith paper
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A Primer on Bayesian Parameter Estimation and Model Selection for Battery Simulators
SOBER and BASQ, two previously published Bayesian algorithms, are adapted for battery simulators and demonstrated on six case studies, including impedance-based model selection.
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