Solid Energy Systems (SES) plans to go public on NYSE by merging with special purpose acquisition corporation Ivanhoe Capital Acquisition Corp. Founded in 2021, the company is a spinoff from Massachusetts Institute of Technology and operates two facilities in the U.S. and China.
The SPAC merger puts the combined company at a value of US$3.6 billion. Furthermore, the deal is expected to fund SES’s expansion plan by providing US$476 million in gross proceeds, including a $200 million private investment in public equity from prominent automakers such as Hyundai Motor Company, Kia Corporation and Geely Holding Group.
Above all, the electronics contract manufacturer Foxconn will also participate in the investment, with the exact amount undisclosed, in accordance with its EV strategy. Foxconn has already made a series of moves this year to strengthen its position in the EV battery sector. The company plans to release its first solid state battery prototype this year, and commercialize it in 2024. To realize the objective, Foxconn already partnered with Formosa Plastics Group which in turn has cooperated with Taiwan’s Industrial Technology Research Institute (ITRI) on producing a type of solid polymer electrolyte used in solid-state batteries.
Solid-state batteries have been the holy grail of the EV industry, but their commercialization faces several obstacles, including low energy densities, high temperature requirements and most importantly, difficult-to-scale manufacturing processes.
SES claims that its battery solution with a Li-metal anode is able to reach an energy density of above 400 Wh/Kg. Li-metal anodes have long been considered as the ultimate anode for their higher energy densities as well as faster recharging times.
Indeed, according to SES, its product represents a major boost in energy density compared to today’s li-ion batteries with average densities around 280 Wh/Kg. In addition, SES states that its batteries can be 80% charged within 15 minutes. In terms of safety, SES indicates that it utilizes an algorithm trained on terabytes of data to optimize battery performance.