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3 ways that machine learning can supercharge battery development

  • Events
  • in: Batteries

Recorded webinar - guest speakers, Deregallera

In this webinar, we heard from Intellegens and battery experts Deregallera as we discussed how machine learning could supercharge battery development. Powering the electric vehicle revolution. Enabling renewable energy sources. Cutting charge times for personal devices. These are urgent drivers to develop new battery technologies, and to do so faster. But battery R&D is complex and slow, with many competing factors to balance, and a heavy reliance on time-consuming, costly experiments to fill gaps in data and test prototypes. Machine learning can guide and focus this work. We looked at three key areas of battery development: (1) New battery materials and chemistries; (2) Design of battery packs; (3) Battery management systems.

Original broadcast date: Wednesday 23 February, 2022

Speakers:

  • David Keating, Commercial Director, Intellegens
  • Joe Smith, Materials Research Scientist, Intellegens
  • Dr Kat Hunter – Senior Battery Scientist – Materials Synthesis, Deregellera
  • Dr Daniela Ledwoch – Senior Battery Scientist – Cell Manufacture, Deregellera

About Deregallera

South Wales based SME Deregallera are developing battery materials that store more energy, and electric motors that use less. The battery activity is focused on sodium-ion, an upcoming alternative to lithium-ion with an emphasis on achieving genuine sustainability and minimising the environmental impact of the whole supply chain.

More on this topic

  • Alchemite™ for batteries
  • White paper: Machine learning for battery applications
  • An overview of the Alchemite™ Technology
  • Case studies

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