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Welcome to the D3TaLES Documentation

This documentation contains information about the structure, accessibility, and methodology for the data contained in the D3TaLES database. Here, you will find details about how the data is structured schematically, how and when to access the data through a REST API, and what theory and which parameters were used in generating computational data.

D3TaLES aims to accelerate the capacity to discover and develop liquid-based energy storage (LES) materials by combining novel domain knowledge with machine-enabled modeling and autonomous synthesis and characterization. We have constructed an interdisciplinary network of collaborators who have expertise in:

  • materials design,
  • materials characterization,
  • materials deployment,
  • autonomous experimentation,
  • data analytics, and
  • machine learning.

In total, our synergistic research, infrastructure, and workforce development activities will situate Kentucky and Iowa as leaders in addressing the critical and growing need for energy storage capacity.

D3TaLES Workflow

D3TaLES Workflow

Citing the D3TaLES Database

Please cite the following work when using ExpFLow.

Towards a comprehensive data infrastructure for redox-active organic molecules targeting non-aqueous redox flow batteries, Digital Discovery, 2023,2, 1152-1162, DOI: 10.1039/D3DD00081H

Contact Us

If you have any questions, comments, or issues, you may submit a contact form here or email us at

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