The Exchanges

Q the world where you just wanted to replace the hydrogen source, and say you were going to be operating an electrolyzer at something less than a hundred percent capacity, and so you did need to buffer that hydrogen, from a techno-economic standpoint, how big a deal is that? Like, how expensive would that be? Is it enough of a problem that it necessitates introducing entirely new technologies to replace Haber-Bosch?

A Yeah, that's a good question, Jill. High level, I think it would be pretty impactful to the levelized cost of ammonia if we need to account for hydrogen storage on site in order to feed the ammonia synthesis loop continuously. So if we take data from a couple sources, the levelized cost of hydrogen storage ranges from somewhere between 30 cents a kilo hydrogen to about a buck 20 a kilo hydrogen for compressed gas. So we put this in an ammonia basis, this is about five to 20 cents a kilo ammonia In hydrogen storage cost alone that accrues to the LCOA. And this is a pretty big chunk of your cost stack. And if we keep that same, ah, high-level target, the long-term average selling price of ammonia in the US between five to 600 dollars a ton, you can see that this, ah, quickly can make a big impact. And I'm sure we're gonna talk about this later, but one of the key drivers of decentralized Ammonia production is to eliminate or reduce the transportation cost of between where you produce ammonia and where you use ammonia, but if we need to buffer hydrogen, the value in reducing this transportation cost is perhaps eclipsed somewhat by hydrogen storage cost and really points to either trying to develop ammonia synthesis reactors that can ramp with renewables Uh, or looking at other technologies like batteries, but, uh, those will also have their own, uh, cost drivers.

AI assessment note: “this is about five to 20 cents a kilo ammonia In hydrogen storage cost alone”

Q a better solution for green ammonia production, for one reason or another. I guess the first question is, why? Like, what's the premise on which you could imagine doing better than this century-old technology that seems to work very well, and is it Just generally that we could do better, or is it that we could do better specifically if we want to pair with electrolysis to produce the hydrogen?

A Yeah, that's a good question. I think on the, ah, on the new technical pathways that we're seeing, the, the one that we were talking a lot about is, like, if you think about air or nitrogen and your hydrogen as the input into these new reactors, we've seen a lot of different reactor types, so electrochemical, photochemical, thermochemical, and while they're all early, Probably the most advanced we've seen is the thermochemical approach of this decentralized thermochemical processes to produce ammonia. Some are actually just scaling down typical Haber-Bosch, i.e., just still having high temperature, high pressure. And then others on the new novel reactor design, what they're, what they're working on is having lower temperature, lower pressure Haber-Bosch or ammonia synthesis loop reactors. And so there's a couple reasons why. And, and one is really the, the pairing with, ah, renewables. So we, we mentioned earlier that you need to be able to, if you want to have a green ammonia, you need to have, ah, green electrons, and so in order to pair with renewables, if you're a lower temperature pressure reactor, when the sun is shining or the wind is blowing, you can, you could potentially ramp down your reactor, and so you could follow the renewable cycle. And then the other more TEA reason why people are working on this type of technology, this lower temperature pressure reactors, rea…

AI assessment note: “one is really the, the pairing with, ah, renewables”

Q hundreds of, of TEA models and analyses on the things that are commonly done wrong. And we should do it as much as possible with the frame of actual Examples, right, in climate tech, um, and figure out sort of through that vein, like, okay, what is the right way to do it? So, Mel, I'm gonna start with you. Uh, name a, name a pet peeve in TEA models.

A I'm, I'm so excited, uh, for this. So, number one pet peeve, uh, for me would be unreasonable assumptions. So I think we, we probably have a few examples in all of our brains. My number one here to the spirit of an example is this tension between capacity factor and electricity price. And so let's kind of unpack it a bit. So capacity factor, I think most people might know what that is, but in the highest level, it's, you know, your actual output divided by your theoretical output. So if you could have continuous operation, So like in power generation, it's your actual megawatt hours divided by your nameplate capacity times by the number of hours in a year. And so we know in, in some power generation like nuclear, that's going to be really high. And then in some, uh, power generations like solar or wind, we're thinking more of like a capacity factor, 30% of a really good solar resource, 50% really good wind resource. And so if we unpack energy cost, Often what we see in these TEAs, or what I would say, are a levelized cost of energy. And so, you know, ignoring capacity factor, why I think that's independently not the right energy cost to put in your TEA, is that essentially what the end customer's paying is a, is a generation plus a transmission or distribution, or basically you need to generate that, that energy, and then you need to get it to where you want it to be. And so, u…

AI assessment note: “number one pet peeve, uh, for me would be unreasonable assumptions.”

Q Yeah, and it's not just electricity that we see as, as one of these, like, unreasonable inputs, I think. We also see this, oftentimes, even if, um, the inputs are on the, on the molecule side, right?

A No, totally. I, I think I'm very passionate about this one, being an organic chemist, and, and the idea that organics, uh, i.e. those, um, molecules that are made from hydrogen and carbon, so hydrocarbons, are cheap. And it's, it's a relic of, of being an organic chemist, which usually these people are coming from that discipline, and they, we write it in all our papers, and that's like the promise of using organics. But, Organic molecules, i.e., those made from carbon and hydrogen, are not always cheap, and the reason is, is that there's purification, so again, like, even that system boundary really matters, because your, your yield matters a lot, and your purification matters a lot, and so a good example is redox flow batteries. You know, the, the, one of the active species is an organic molecule, and You know, everyone pencils in something that's really, really cheap on a dollar per kilogram basis. And I think that the way that I like to think about it is I, you know, I bound it like ethylene, one of the most ubiquitous organic molecules that there is, is a dollar per kilogram. But you're, and I don't think you're probably going to come close to that. So in the, in that example, it's how cheap does that organic need to be to be competitive? And you have to get really close to ethylene to try and beat LFP or vanadium redox flow batteries in order to be competitive. So it's al…

AI assessment note: “Organic molecules, i.e., those made from carbon and hydrogen, are not always cheap”

Q hundreds of, of TEA models and analyses on the things that are commonly done wrong. And we should do it as much as possible with the frame of actual examples, right, in climate tech. Um, and figure out sort of through that vein, like, okay, what is the right way to do it? So, Mel, I'm gonna start with you. Uh, name a, name a pet peeve in TEA models.

A I'm, I'm so excited, uh, for this. So, number one pet peeve, uh, for me would be unreasonable assumptions. So I think we, we probably have a few examples in all of our brains. My number one here to the spirit of an example is this tension between capacity factor and electricity price. And so let's kind of unpack it a bit. So capacity factor, I think most people might know what that is, but in the highest level, it's, you know, your actual output divided by your theoretical output. So if you could have continuous operation and So like in power generation, it's your actual megawatt hours divided by your nameplate capacity times by the number of hours in a year. And so we know in, in some power generation like nuclear, that's going to be really high. And then in some, uh, power generations like solar or wind, we're thinking more of like a capacity factor, 30% of a really good solar resource, 50% really good wind resource. And so if we unpack energy cost, often what we see in these TEAs are what I would say are a levelized cost of energy. And so, you know, ignoring capacity factor, why I think that's independently not the right energy cost to put in your TEA, is that essentially what the end customer's paying is a, is a generation plus a transmission or distribution, or basically you need to generate that, that energy, and then you need to get it to where you want it to be. And so,…

AI assessment note: “number one pet peeve, uh, for me would be unreasonable assumptions.”

Q Yeah, and it's not just electricity that we see as, as one of these, like, unreasonable inputs, I think. We also see this oftentimes even if, um, the inputs are on the, on the molecule side, right?

A No, totally. I, I think I'm very passionate about this one, being an organic chemist, and the idea that organics, uh, i.e. those, um, molecules that are made from hydrogen and carbon, so hydrocarbons, are cheap. And it's, it's a relic of, of being an organic chemist, which usually these people are coming from that discipline, and they, we write it in all our papers, and that's like the promise of using organics. But, um, Organic molecules, i.e. those made from carbon and hydrogen, are not always cheap, and the reason is, is that there's purification, so again, like, even that system boundary really matters, because your, your yield matters a lot, and your purification matters a lot, and so a good example is redox flow batteries. You know, the, the, one of the active species is an organic molecule, and, you know, everyone pencils in something that's really, really cheap on a dollar per kilogram basis, And, I think that the way that I like to think about it is I, you know, I bound it, like ethylene, one of the most ubiquitous organic molecules that there is, is a dollar per kilogram, but you're, and I don't think you're probably going to come close to that, so in the, in that example, it's how cheap does that organic need to be to be competitive, and you have to get really close to ethylene to try and beat LFP or vanadium redox flow batteries in order to be competitive, so it's a…

AI assessment note: “Organic molecules, i.e. those made from carbon and hydrogen, are not always cheap”

Q or another have to look like in order to change the world here, right? Like, what would, what would be revolutionary enough that you can imagine getting to, getting green ammonia, clean ammonia at Commodity gray ammonia prices. Is it as simple as really, really cheap clean hydrogen? Like, it may be just that simple, but is there anything else that you can imagine would be a game changer here?

A You know, I've, I've thought a lot about this question, and really trying to think about one miracle that would, would make this happen, and I think where I am at is that, yes, uh, I think the hydrogen is, is certainly a huge part of the levelized cost, I think, from a CapEx, and from an, and also from an energy perspective, so I think you need both, uh, cheap, uh, cheap energy, and you need cheap CapEx. I think also what we were just saying about the nitrogen generation unit, if we're going to have these decentralized Smaller, uh, productions. The nitrogen generation is a sensitivity at small scale, and so, you know, if you said what's like one big miracle, one thing I was thinking about was if you could have a air as your input as opposed to actually eliminating the nitrogen generation completely, uh, that coupled with I, the, uh, cheap electrons and also the cheap capex for the hydrogen electrolyzer, Could be game changer for ammonia.

AI assessment note: “if you could have a air as your input as opposed to actually eliminating the nitrogen generation”

Q to get both of your perspectives on in terms of, yes, there's a lot you can, a lot of value to be gained from doing this work, but there's also only so much of it that you really can do at a That line between what actually adds value and what is just, like, modeling theater, basically. I don't know, Mel, do you have, do you have a view there?

A Yeah, I, I, I think that especially some of the, the TAs we've looked at are the founders, um, they're paying for a TA. So some people are using consultants, which I would assume is going to be very expensive. So, you know, back to the top level, like, how It's supposed to be a tool to help drive your technological progress, and so if you're paying good money for this, I'm actually curious y'all's thoughts on that too, but I, I think there's like over-specification. My worry with that, and I think we, we saw, we've seen this recently, is that you can essentially miss the forest from the trees. So if you're so busy counting the number, you know, the power in your pumps and the number of little widgets and, and valves and et cetera, You, you might miss something that's really crucial that actually is a driver of your economics, uh, because you were focusing on, on so much that you didn't hit, like, the really, the couple of things at the stage that you're at that's going to hit, allow you to get to the next milestone. And so, I mean, I, I'm sensitive to it. I think, you know, ultimately, when we receive a TEA, I think Greg and I probably always look at it, of course, and I think we independently are, you Making our own, so we can teach ourselves what is the driver, the drivers in that, in technology, and what should be important at this, at the stage that company's at.

AI assessment note: “over-specification. My worry with that... you can essentially miss the forest from the trees”

Q and, you know, you can, you can make that bet, but you should be clear on that, if that is the case. At the end of the day, you're gonna have to deliver a thing to a customer, and it's gonna have to be better for some reason, cheaper or otherwise, than the thing that they otherwise would have been buying. Any good examples spring to mind on this one?

A Yeah, I was going to say, I think also implicit in this is that the distribution costs are, are low, and that's, and from some of, like, whether it's hydrogen, or it's ammonia, or it's energy, that's, that's certainly not true, and I know, you know, Greg's also been looking at some of this with hydrogen, but with, you know, ammonia, you know, we, we did a deep dive on what those distribution costs could be, and, you know, you, depending on where you are in, in the U.S., or, and I'll stay U.S. centered, but this is even more so outside the U.S., Those distribution and transport costs can be even two X your level, your production cost. And so it really matters which, you know, target you're, you're comparing yourself to because it's not just 10% off at times. It can be, you know, it can be way off. And then that really impacts your, your TEA.

AI assessment note: “Those distribution and transport costs can be even two X your level, your production cost.”

Q of, yes, there's a lot you can, a lot of value to be gained from doing this work, but there's also only so much of it that you really can do. At a certain stage. And so how do you find that, that line between what actually adds value and what is just like modeling theater, basically? I don't know, Mel, do you have, do you have a view there?

A Yeah, I, I, I think that especially some of the, the TAs we've looked at are the founders, um, they're paying for a TA. So some people are using consultants, which I would assume is going to be very expensive. So, you know, back to the top level, like, it's supposed to be a tool to help drive your technological progress, and so if you're paying good money for this, I'm actually curious y'all's thoughts on that too, but I, I think there's like over-specification. My worry with that And I think we, we saw, we've seen this recently, is that you can essentially miss the forest from the trees. So if you're so busy counting the number, you know, the power in your pumps and the number of little widgets and, and valves and et cetera, you, you might miss something that's really crucial that actually is a driver of your economics, uh, because you were focusing on, on so much that you didn't hit, like, the really, the couple of things at the stage that you're at that's going to hit, allow you to get to the next milestone. And so, I mean, I'm sensitive to it. I think, you know, ultimately, when we receive a TEA, I think Greg and I probably always look at it, of course, and I think we independently are making our own, so we can teach ourselves what is the driver, the drivers in that, in technology, and what should be important at this, at the stage that company's at.

AI assessment note: “if you're so busy counting the number... you might miss something that's really crucial”