they invested in the equipment to make lots of materials in parallel that are a little bit different, and to do massive designs and experiment, and then also in parallel, get them into lots of small battery cells. And so, I might say, in order to develop a material, I might collect hundreds of data points to get there. What Wildcat might say is for a few hundred thousand dollars, tell me what you want me to study, and instead of a few hundred, I’m going to collect many thousands of data points. It’s just random in some ways, but you’re just doing a massive designed experiment.
DC: I think the big data thing is making more of an impact than artificial intelligence. We have a good example where a collaborator was using one of our proteins as a negative control for his stem cell work. It turns out that protein induced an 800 percent increase in a grafting of stem cells. It shouldn’t. There’s absolutely no reason this protein should do that. It does something very different.
And in the past you would have had to set probably three or four postdocs on this, and they would have to try to figure it out. All we’re proposing to do is we’re going to dump the protein on stem cells and do a massive expression profile of these cells, and most likely it will tell us which pathways are being turned on and why it does this.
In the past it would have taken years, probably a decade to figure it out. And this will probably take us six months—assuming that the pathways make sense. We’re all hoping that it’s going to tie in to something that somebody knows something about.
Another good one is we’re trying to crystallize one of these proteins to determine its structure. That’s most of what I did during my later grad student and postdoc years. Now you pay 300 bucks and there’s a robotic system that will set up thousands of crystallization conditions and automatically image them and send you back the conditions that work. You think about one or two years of your life versus $300 for a screen that’s going to come back in two weeks. It’s like, Wow, this field has really moved on since I left.
X: What’s a technology you think might have a major impact in the next 10 years on the work you guys do day to day? Do you think we’re going to see scientists wearing augmented reality goggles and manipulating 3D holograms of molecules while you’re still in the field?
AF: I don’t know. The thing that I look forward to in my field—it’s much more macro-scale—but what’s happening with solar is very interesting in terms of the price of solar and what that’s going to do. It’s on an exponential curve downward. We’re already getting to where a lot of it is cheaper than the grid in certain situations. If that keeps going down enough to the point where you get people defecting from the grid for cost reasons, and we’re able to bring in energy storage to make it reliable and so that you don’t have to worry about night or clouds or bad weather, than that totally fundamentally changes the entire energy infrastructure. The whole system.
It seems like it’s not that far away, so that could be a really big shift in how the world operates, how energy is used, how expensive it is.
When you talk about energy storage at the grid scale, it’s so much more massive than anything that we’ve seen yet. The number of batteries in those types of installations absolutely dwarfs the size of all the electric vehicles or all of the laptop batteries or all of the cell phone batteries that are currently produced.
Lithium ion batteries are a $10 billion business right now. If that was the technology that was used to store grid-scale energy, we’re talking about trillions and trillions of dollars.
DC: Does that bring a lot of the old pollution questions if you have all this lithium hanging around?
AF: There are a lot of challenges with any of those. Lithium ion is not as well recycled now as it could be, so before you deploy it at that kind of scale, you’ve got to figure out how to reuse it. [Lead in lead-acid batteries is] more thoroughly recycled because it’s toxic so people don’t want to see it in the environment. It’s not like the plastic bag you see on the street. It’s a lot worse than that. The percentage of recycled lead is extremely high. It could be, if you bothered to figure it out, for lithium ion batteries or lithium sulfur batteries or ultracapacitors or whatever. It’s all doable, there just hasn’t been the investment in figuring it out.
From Failure to Discovery
X: You are also both company founders in addition to being scientists, Darrick several times over. Aaron, EnerG2 is your first company, but it’s been 13 years. Tell me what it was that compelled you and your co-founders to take the science you were working on and build a company around it. How did you know when you pulled the trigger that it was the right thing, the right time?
DC: I couldn’t work at a big company. I realized when Corixa got so big, it was just too much HR, too much forms, too many things that I didn’t want to deal with.
But to say it’s the right time—I was glad I was so naive, because in hindsight I don’t think I would have done it, knowing what I was going into. My son was born just about that time, so it wasn’t great in terms of money. I don’t regret doing it, but at times—like when the economic downturn happened and I was paying our salaries and rent on my credit card—those are times when you go, ‘I don’t know how good of an idea this was.’
AF: My wife wanted to strangle me for a few years in a row.
DC: Oh, good. It’s not just me!
AF: She still does, but for different reasons now.
X: In business and in the scientific discovery process, failure—fast failure, ideally—and trips back to the drawing board are a way of life. How have you remained motivated throughout your careers?
AF: I don’t see failures. I see pivots. It’s not like you just gave up and went home. You decided that this approach wasn’t going to work and we’ve got to try something different. Yeah, there’s a bunch of things that didn’t work. Trial and error is not a beautiful way to pursue something, but it is tried and true.
DC: When I look at scientific misconduct and people faking their results, I think they’re shooting themselves in the foot in the worst way possible. Because, to me, a lot of times, the failures are the most interesting things. When things aren’t working like you think they should. Like this new molecule with the stem cells. What the hell? But now it could turn into a huge discovery. If we could make stem cell technology more efficient, it’s a big deal.
It’s almost likely there isn’t such a thing as failure—except if you do something stupid, like I just forgot to add this enzyme and now all my reactions are off.
AF: Yeah, you’re right. All you’ve done is just figured out that you’re missing something, and then it opens up the opportunity to go find out what really matters in this situation. That’s how discovery is made, right?
DC: If you’re applying all the knowledge that is there and it doesn’t work, then something’s wrong about the knowledge.
