RA B
Accelerating Battery Research through Data, Modelling and Automation
Future battery research requires not only new materials and concepts, but also new ways of conducting research. Research Area B develops the methodological foundations for a faster, more integrated and increasingly data-driven research process. It combines advances in research data management, data science and multiscale modelling with experimental high-throughput methods, laboratory automation and digital workflows. Together, these activities establish a Battery Acceleration Network that supports the efficient discovery, characterization and optimization of next-generation battery materials and full cells across the entire POLiS programme.
Rather than focusing on a single battery chemistry, Research Area B develops methods that benefit all research activities within POLiS. It is therefore both an enabling platform and a research programme in its own right. Novel methodologies are conceived, developed and validated in close collaboration with the chemistry-focused Research Units, where they are continuously tested and refined through practical application. In this way, methodological innovation and battery research advance hand in hand.
Research Area B is organized into three complementary Units.
B.1 – Data
Research Unit B.1 develops new methods for managing, integrating and exploiting research data across heterogeneous experimental and computational laboratories. Its work includes semantic data structures, ontologies, electronic laboratory notebooks, scientific workflows and advanced data science approaches that transform distributed datasets into a coherent research ecosystem. These developments establish the foundation for FAIR, reproducible and interoperable battery research while enabling new forms of data-driven scientific discovery.
B.2 – Simulation Chain
Research Unit B.2 develops simulation chains that connect multiscale simulation methods to address battery processes across different length and time scales. Combining atomistic calculations, continuum models, digital twins and data-driven workflows, it creates new approaches for understanding complex battery systems and predicting their behaviour. By tightly linking theory with experiment, this linked multiscale approach provides deeper scientific insight while guiding the design and optimisation of next-generation battery materials and full cells.
B.3 – Acceleration
Research Unit B.3 develops experimental methods that accelerate the synthesis, processing and characterization of post-lithium battery materials and cells. Automated laboratory workflows, high-throughput synthesis, autonomous characterization techniques and advanced manufacturing concepts enable the systematic exploration of large materials and process spaces. Closely integrated with digital workflows and modelling approaches, these methods generate high-quality experimental data and establish rapid feedback loops between experiment, simulation and data analysis.
Together, the three Research Units form the methodological backbone of POLiS. By advancing data science, computational modelling and accelerated experimentation as complementary research fields, they establish a Battery Acceleration Network that enables faster, more systematic and more reproducible battery research. This integrated approach accelerates scientific discovery across all chemistry platforms and provides the methodological foundation for the sustainable battery technologies of the future.