STANDARDS and PROTOCOLS

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BATTERY 2030+ Knowledge base for standards and protocols in battery research & development

Every researcher uses standards in their everyday work. They apply standard protocols developed and fine-tuned in their laboratories and preserve knowledge in the form of good laboratory practice (GLP) guides, safety regulations, standard routines, research protocols, electronic laboratory notebooks, etc. Such standards reduce errors, improve repeatability, and increase the overall quality of data generated during research – both in experiment and simulation.

However, within BATTERY 2030+, we want to take the next step: In order to enable researchers to collaborate efficiently, we work on harmonized procedures and protocols for mutual acceptance of data (MAD), data reuse, and full data sharing. We have selected several focus areas, in which we concentrate our activities. These areas include:

  • Electrochemical Testing
  • Synthesis and Characterization Protocols
  • Confirmation of Theoretical Data with Experimental Results (and vice versa)
  • Simulation infrastructure and interfaces

With the input from the BATTERY 2030+ consortium we created the BATTERY 2030+ Knowledge base for standards and protocols in battery research & development.

This web resource gives an open access overview on over 100 Key Performance Indicators (KPIs) and over 60 Process Parameters (PPs) that are involved in the battery research and development process chain. Over 112 different measuring techniques for the KPIs and PPs are provided and will be linked to consortium-wide standards and protocols in the future. The knowledge base will be further improved in an iterative and ongoing process.

Benefits of setting consortium-wide standards:

  • Collaboration on new levels, allowing for novel, autonomous research approaches, accelerated materials discovery, and data-based research in a field that has thus far mostly adhered to classical trial and error research
  • Highest quality of research within BATTERY 2030+
  • Enabling FAIR data principles

Contact:

Dr. Philipp Veit (KIT) – philipp.veit@kit.edu

Dr. Christian Punckt (KIT) – christian.punckt@kit.edu