Publication date: 28th August 2024
Automation in experimental battery research is limited, and cell assembly and cycling often require labor-intensive steps. Additionally, the outcomes of lab-level battery research are not always reproducible and are often dependent on the skill of the researchers. Extending lab automation improves reproducibility, accelerates experiments, and frees experimentalists from repetitive tasks, providing more time for creativity.
In a joint collaborative effort, the Swiss company Chemspeed Technologies and Empa developed and validated an automated coin cell assembly robot integrated into an argon glove box. The robot can assemble 32 coin cells per batch, with anode/cathode capacity balancing fully automated to a precision of 0.01 mg. It is capable of formulating complex mixtures of liquid electrolytes, which are then dispensed with a precision of 1 µL. Cells are then cycled on a 256-channel potentiostat interfaced with an open-source Python package developed within the Battery2030+ BIG-MAP Aurora project1. Each cell can be traced and monitored as a digital twin within the open-source workflow management platform AiiDA, developed at EPFL/PSI2. The data generated will be ontologized and made FAIR (findable, accessible, interoperable, reusable) using the BattINFO ontology, adhering to principles that facilitate data sharing and reuse.
We present the first results from robotic cell assembly and cycling, demonstrating the power of the Aurora platform in accelerating battery materials research.
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