For the last decade, battery chemistry company Sila has been working to replace the graphite anode in lithium-ion batteries with silicon, a material that’s easier to come by, more environmentally friendly and allows for a battery cell that’s denser and cheaper.
In September, the company shipped its first commercial product with Whoop wearables. Now, Sila aims to scale 100x so it can provide its battery chemistry to power electric vehicles by 2025.
Before Sila was founded, co-founder and CEO Gene Berdichevsky was the seventh employee at Tesla, where he spearheaded the production of the battery pack that was used in the Tesla Roadster, the world’s first highway-legal electric vehicle that ran on lithium-ion batteries.
Considering his background and experience with scale, we caught up with Berdichevsky to explore how founders who work on emerging tech should think about scaling, how they should approach funding and why they should go after the hardest problem first.
Scaling as a part of the innovation process
Billions of dollars have gone into producing different battery chemistries to make better, cheaper and more efficient batteries, but Berdichevsky says there’s a reason they haven’t hit the market yet. A startup could produce a stellar new technology, but if it can’t scale, no one will buy it.
“One of the things we did very early on is, we told our scientists and engineers they could only use global commodity inputs so that we know we can make enough for millions of cars,” Berdichevsky told TechCrunch. “You can’t use anything bespoke; you can’t say we’ll figure it out later.”
Supply chains are strained, particularly as COVID-19 drags on, so it is key to build technology that can scale quickly and cheaply. To do this, Sila also uses bulk manufacturing techniques and ensures its technology can seamlessly drop into any battery factory and existing cells.
To date, Sila has raised $925 million off the back of this strategy.
Funding is a means to an end
Source Link Why emerging technology founders should tackle the hardest problems first
