Why Automat Solutions
A recent California executive order requires all new passenger cars and trucks sold in-state be zero-emission by 2035. The electric vehicle (EV) era has officially begun, and battery technology is an essential component of our futures. Battery improvements and the success of EV products, however, will depend on our ability to quickly identify new and better raw materials.
Most companies today adopt an "Edisonian" approach to R&D; this “trial and error” methodology is time-consuming and costly. To overcome this obstacle, we need to accelerate the R&D process for raw material recipes. Automat's high-throughput screening robotics are powered by an AI engine that will lead the hunt for the best recipes by automating chemical lab experiments on a large scale and with greater efficiency. Whereas manual R&D is a 10- to 20-year process, Automat Solutions’ self-driving platform will reduce discovery time to between 12 and 24 months.
It takes 7-14 years of R&D and 3-6 years of validation to discover new materials manually. The self-driving platform will reduce the discovery time from 10-20 years to 1-2 years. Automat Solutions provides the technology that enables companies to find new materials and generate recipes for batteries in a much shorter time.
Automat’s software can predict the conductivity of a given new electrolyte and actively search for new electrolytes that have higher ionic conductivity. Automat Solutions’ high-throughput screening system can test and match these advanced electrolytes with raw materials (for example, lithium metal anode) to create recipes for high-density-energy batteries. These high-density-energy batteries can charge faster and last longer at a lower cost.
Automat Solutions provides innovative technology that enables companies to find new materials and generate recipes for batteries faster, because Automat’s software can predict the conductivity of an electrolyte and then search out new electrolytes with even higher ionic conductivity. Furthermore, Automat Solutions’ high-throughput screening system can test and match these advanced electrolytes with raw materials (e.g., lithium metal anode) to generate recipes for high-density-energy batteries. Automat’s software also uses machine learning and AI to “recommend” potential recipes, document the sample data into its database, and notify the technicians of the appropriate protocols to execute. This high-throughput screening runs up to 96 samples simultaneously. In other words, Automat will allow us to create batteries that charge faster and last longer at a lower cost.
The Founders of Automat Solutions
Automat Solutions is about much more than cutting-edge innovation. The TSVC Deeptech team was impressed by the expertise and experience of its founding members who have both the technical and soft skills to succeed.
Dr. Leon Wang studied battery and electrochromic materials at Tsinghua University and acquired more than fifteen years of experience developing EV batteries and new battery materials before launching Automat Solutions as its CEO in 2021. In the mid-2010s, he led Seeo’s lithium battery development team and later joined Heliotrope Technology to head their electrolyte development team.
Dr. Jason Wang (no relation) studied robotic development at Peking University and has acquired more than twenty years of experience and many accolades from Chinese academic research institutes for his contribution to high-throughput robotics. As COO of Automat Solutions, he has already successfully introduced and marketed Automat’s R&D equipment in China.
Dr. Leon and Dr. Jason share a vision to create cutting-edge technologies that combine with materials science and robotics. TSVC is confident that Dr. Leon Wang and Dr. Jason Wang will succeed in the project to develop materials for longer-lasting and lower-cost batteries.
TSVC Conviction
TSVC seeks out innovative, cross-disciplinary technology that uses artificial intelligence and machine learning (AI/ML) to transform much of the knowledge work currently completed by highly-trained professionals. As with so many of our seeds, 18-to-24 months is too small a timeframe to fully appreciate the potential benefits. For example, Automat’s sophisticated AI algorithms can enhance R&D efficiency in discovering new materials for both solid-state and regular lithium-ion. Solid-state batteries, however, will take time to reach the mass market, despite current hype. Automat Solutions is partnering with lithium-ion batteries manufacturers to provide raw materials at the current stage of the industry and as industry needs evolve as well.
https://www.usitc.gov/publications/332/journals/the_supply_chain_for_electric_vehicle_batteries.pdf
https://semiengineering.com/why-ev-battery-design-is-so-difficult/
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