Good evening and welcome to the Chaos West stage. The next talk is about storing energy in the 21st century. Frank is a journalist mostly writing on manned space flight, but also working on energy storage. And he's going to tell us what his ideas are, what his knowledge about solutions for the future of storing energy will be. Please welcome him. Hi. As was already said, I'm a journalist and I'm a podcaster. I write text. I speak into microphones. Doing presentations is not part of my job. My presentations are bad. I'm sorry about that. So this talk is going to be about energy storage in 21st century. If you expect this to be about the future, you're only half right. Because if you had a look at the calendar, it's 2020. We are in the 21st century. And one of the things we need to talk about is our state right now and how we got here. And you might be a bit surprised by my first slide. Yeah, 1859, lead acid batteries, actually very first kind of battery that was ever invented, that was actually rechargeable. And it's still the most popular battery around. As you can see, it's over 370 gigawatt hours of lead acid batteries are produced every year to date. And that's more than twice. Or maybe this year, it's just about twice of what we have in production in lithium ion batteries. So this is really a very important technology. And yeah, electric cars were not very modern invention. In fact, around the start of last century, they were quite popular. And lots of people will say, yeah, OK, this was the moment when everything went bad. But if you look at the actual performance of these cars, well, this was for early adopters. They had four horsepower, three kilowatts of power. They were driving at about the speed of what you would walk, maybe a little bit faster. And if you were trying to go up a hill, this thing still weighs a ton. I mean, it's almost as heavy as a modern car. They were not very good overall. When you have a real car, you need a bit more than that. These days, about 70 million passenger cars are produced every year. 25 million commercial vehicles, like vans, trucks, tractors, and so on, are produced every year. And about 90 kilowatt hours of lithium ion batteries are put into electric cars. So if we took all production of passenger cars and divided the batteries among them, it's 1.5 kilowatt hours per car. That's not quite enough. So the number of electric vehicles you see on the street is not because people are not willing to make more, but they just don't have enough batteries for that. We need at least 3,500 gigawatt hours. And that's about 20 times the current production of lithium ion batteries just to supply passenger cars. All the other things, like trucks, vans, vehicles, maybe grid storage, all the other things that you need the lithium ion batteries for is not included in that figure. But in fact, lithium ion batteries are still fairly modern technology. And there were others, like nickel cadmium, also at the turn of the century, and yet others, like nickel ion. And what happened with nickel ion is that they replaced the cadmium with iron. In fact, it was still a bit more expensive to produce. But these batteries kind of worked. And that was a great advantage. On the other hand, nobody quite knew why they worked. In fact, when you see the formulas here, these formulas were figured out in around 1960 or so. Before that, it was very hard to figure these out because you couldn't actually look into the battery and do all the chemical analysis. And they needed near infrared spectrometry to figure that out. If you look at our formula and you squint a bit and maybe subtract the OH here from the H2O, what you actually see is that here's the hydrogen and it moves over to the nickel. And this was something that was observed. And somebody had the idea that you could just build a battery without any cadmium or any iron. You just have the hydrogen in there. And these batteries were actually quite successful, even though you might never have heard of them, because they were mostly used in space. Hubble Space Telescope still has them. The International Space Station had them or has them. They're currently being replaced by lithium batteries. But they were quite important, at least in that area, especially because they could sustain a large number of cycles, like 20,000, 50,000. And you have to remember, they were used in satellites or like the space station in very low orbits. So every 90 minutes, they go once around the Earth. And they have a sunrise and a sunset every 90 minutes. So about 6,000 per year. And so you get 6,000 cycles every year. And your battery has to be able to sustain that. However, these batteries were absolutely not suitable for anything here on Earth. For one thing, you don't really want to have a pressure vessel filled with anything around you, because it's really high pressure. And something might go wrong, especially when you build like millions of them. And also, inside there is gas. There's actually hydrogen being developed inside the battery. And as soon as it leaks, the hydrogen is out there. It's flammable, it's possibly explosive. You don't really want that. So people had the better idea. Actually, they had this idea before they said, why we can just use the hydrogen gas. They stored the hydrogen in the form of hydrides. And you all have these batteries. They're the typical AA rechargeable batteries with 1.2 volts. And they're chemically exactly the same. They're chemically exactly the same thing. Because they make hydrogen, and the hydrogen gets stored inside this black stuff here. And the black stuff is a metal, a mixture of metals that easily form hydrides. And so you have a chemical bond, but a very easy chemical bond, between the hydrogen and the material inside there. So the material can take up the hydrogen and give it off, even at room temperature, at fairly good rates. At least good enough for the batteries. The problem is, it's pretty darn heavy. When you look at the stuff that's in there, it's mostly nickel and cobalt and a bit of lanthanite. And that was the first mixture there. Now these days, there are others that are a little bit better and completely different materials, like titanium. But almost always some nickel. And yeah, there are others. Ford patented this one, actually for cars. Yes, Ford did want to build electric cars. And the battery they had was almost as good as the titanium ion batteries around 1990. They were quite good. They were three times as good as lead-acid batteries. Only problem is it's a high-temperature battery. Sodium and the sulfur are both liquid. And if you ever had sodium somewhere in, if you've ever seen the experiment in chemistry where sodium was in water and it exploded, well, if the sodium is liquid, it gets worse. It gets much worse. And in this battery, the sodium and the sulfur are divided by a solid electrolyte. And the solid electrolyte is actually a ceramic. It's aluminum oxide. It's fairly brittle and porous. It has to be porous because something has to get through. So the sodium and sulfur can react with each other. And no, you cannot really use this stuff in a car, which is kind of obvious. You don't want to have liquid sodium in your car. And these batteries are actually still used these days in grid storage, especially in Japan. There's a company I had never heard of when I read about those in 2010. And I know it's 2010 because that company was TEPCO. If anybody remembers this and why this is why it's so important that I read about this in 2010 and remember this sometime later in 2011. But the problem is a lot of these batteries, and we'll talk about lithium-ion batteries in a moment, materials. It's one of my favorite charts in Wikipedia. It's the abundance of chemical elements in the Earth's continental crust. It's a bit of a lie if you there is we have oceans and the oceans contain a lot less hydrogen than would be in this table. This is not a complete table. I took some sections out just to show some important bits here. Like, you know, lead is down here. It's fairly rare. Lithium is also quite rare. The reason lithium is rare is because of what happens in the sun. Lithium is very susceptible to nuclear fusion. So in nuclear fusion, lithium almost immediately gets burned and we don't have a lot of lithium anywhere in the universe. Also not on Earth, as you can see. Cobalt is almost the same.  Like, you know, sodium, for example, we had sodium sulfur batteries. Sulfur would be somewhere in between here. But we have a lot of sulfur because in case you didn't know, we do produce a lot of oil. And there's a lot of sulfur in the oil. And our fuels these days have... Yeah, we have to take the sulfur out of the oil in order to produce our fuels, because otherwise we'd have lots of sulfur oxide emissions. And all that sulfur that gets taken out of the fuel ends up somewhere. And so we have a lot of sulfur around. So we can use that any time. Other stuff that's... Maybe you may be surprised. There's titanium on this list, too. And it's... We have a lot of it. It's like the ninth most element. Nickel is quite rare on the one hand, but it's much more common, especially in production than something like cobalt. The other thing you might want to know about elements... By the way, it's really hard to find a good periodic table that shows the right numbers. And the only one... And it's free to use. And the only good one I found was a Japanese one. I'm sorry, but it shows the right numbers. That's important. One of the important things, if you want to have a battery that is light and has a lot of power, is the weight. These little numbers that nobody cares about down here, that's one of the most important numbers, because that's how much the atom weighs. Chemical reactions only work when worked with the outer electrons in the outer shell. And the energies of these electrons in the outer shell are kind of similar. It's always like a few electron volts. It doesn't differ too much. I mean, it's like, okay, it can be one, it can be five, but it's not like one has five and the other has 500. On the other hand here, everything goes from one hydrogen to something like lead, which has 207. So the differences are quite huge. So when you have a lead battery, you already know it cannot have a heck of a lot of capacity simply because the lead atoms in there are very heavy. Same goes for something like cadmium. Nickel, on the other hand, is a lot better already.  Nickel, cobalt, manganese iron, that stuff, is around 60 and on the one hand, it's quite heavy. On the other hand, it's much lighter than the stuff we had before. So when people were looking for high-performing batteries, they were looking in this corner up there. Obviously, hydrogen is the lightest atom of them all. And if you just want to burn hydrogen, you get a lot of energy out of it. On the other hand, it's hydrogen, it's a gas. It's really hard to contain into anything. And so for a battery, it's not the first choice. So what's the next best option? You may have noticed I took the noble gases and anything below fluoride out of this one just so it looks a bit nicer. But helium, no, you cannot make a battery out of helium. So they were looking at lithium. Lithium is fairly light. You see it has a weight of seven. That's seven grams per mole. And if you want to make a battery that has the highest possible performance, it's obviously lithium. Sodium has very similar chemical characteristics. That's why we have a periodic table. Everything that's on top in one column has kind of similar chemical behavior. So sodium will play a role a bit later. But as you can see, sodium is about three times as heavy as lithium. And so the first choice when you look at a new battery that you might want to invent will be lithium and not sodium. And that's what was done. Of course, this year we had Nobel Prize finally for John B. Goodenough at the age of 97 years.  He still researches in batteries, lithium batteries and also sodium batteries. And this was a revolution. It was really the big breakthrough. If you ever look at, I mean, there's so many articles that I try not to write. Let's say, yeah, this next super battery is just around the corner. On one hand, developing this thing took from the 1970s until the 90s just to make it work properly and commercialize it. The first ones were offered in around 1991. But it improved and improved quite a lot since then. As you can see, it's almost two and a half times the capacity in the last 30 years. Unfortunately, there's a lot of people who write articles saying, yeah, OK, we can get five times or 10 times the capacity within the next five or 10 years. By the way, these kinds of articles and announcements have been made ever since batteries were around. I mean, you can actually find articles in the 1900s that said the same thing. Like, yeah, OK, 10 times as much in the next 10 years. Well, let's put it that way. 100 years later, we had about 10 times as much. So that's about how long it takes. But it's actually not bad. And we are really quite good, especially in the last 20, 30 years, improvements have been quite good. The main problem with this thing, OK, maybe I should say how it works. There was actually another talk that explained how this thing works, so I will be quite brief. You have a material with lithium in here. Let's say cathode. And when you charge it, put a negative charge in here and the positive ions go over here. And are stored. In this case, and that was the first kind of battery ever was around, was in carbon. Actually, they used coke, I think. These days, we use graphite. And graphite is more or less maxed this one out. If you remember this table, storing it in graphite has a problem. You see up there carbon. Carbon has a weight of 12. And when you store lithium in these layers, you need about six carbon atoms to store one lithium atom. And the carbon atoms together, six carbon atoms have a weight of 72. The lithium atom has a weight of 7. So the carbon is about 10 times as heavy as the lithium. So obviously, this is not ideal. But it took a long time just to max this out. These days, I think they're at around 90% or so of the theoretical capacity. So if you want to do something with graphite, you cannot improve this much more. On the other hand, here, this one says metal cobalt. And this is because lithium cobalt oxide was a material of choice from the beginning in lithium batteries. It was pure cobalt oxide. This, too, has changed. Ah, damn it. OK, this will change, and we'll see it later. Lithium. Where's lithium coming from? This year, I was always sure that most of the lithium is coming from Chile. And it's not too bad. I wasn't wrong, but actually, this changed in the last two years. These days, most of the lithium is coming from Australia. And what changed is that lithium used to be mined simply by pumping water into the ground into salt layers, where you had a lot of lithium salts, pumping the water up, evaporating it, concentrating it, and extracting the lithium from that. There are some spots where this is possible, and this is actually quite easy and also quite cheap. But that's limited. And we've pretty much run up to the limit. In Australia, what they're doing is mining ores. Ores like this one here. Spooder means this is a lithium-aluminium silicate. And in theory, they could contain about the ores themselves. It could contain about 6.8% of lithium by weight. I know that's lithium oxide, so it's about half that. So about 3% to 4% of lithium. But typically, you will get maybe 1% of lithium by weight. And that's just for the ore. You have to get to the ore itself. And when you mine something, you not only get the ore itself, but also other stuff. So actually, you need to mine maybe about 1,000 tons of stuff in order to get one ton of lithium. And that sort of thing is done on a large scale in Australia. And that's where, as you can see, that's where it's coming from. And most of that is, by the way, from Chinese firms, because most of the batteries are made in China. Cobalt. Cobalt is a huge problem. A problem for one thing, because we don't have too much of it. As you have seen, it's about as much as lithium. And you need a lot more cobalt in your battery than you need of lithium, simply because, I mean, it's the same number of atoms. If you had lithium cobalt oxide, you need one lithium atom and you need one cobalt atom. But the problem is cobalt atom is about 10 times as heavy as a lithium atom. So you need a lot more cobalt than you need lithium. And so we first ran into the problem of running out of cobalt. Cobalt is mostly mined in a Congo. You will have seen a lot of pictures like this one and much worse ones also. And about a quarter of the cobalt is mined in the Congo. No, sorry. 2 thirds of all the cobalt is mined in the Congo. And one quarter, it depends on the current economic conditions. Something between 10% and a quarter of all the cobalt in Congo is mined by small scale mines like this. But most of it, also mostly by Chinese companies, or at least to a large part by Chinese companies, mined in something like this. If you go and look for pictures of cobalt mines that are free to use, you only find these. So I have a placeholder that is actually a copper mine. I'm sorry. But I really didn't find a free picture of a large scale cobalt mine anywhere. But the main problem is really the Democratic Republic of Congo is a warthorn, poor country. And it's really worth reading up on the history of this country. And that's the problem. The problem is not cobalt. Cobalt is just an element somewhere in the table. Don't blame the cobalt, blame the social situation in this country. And aside from that, we still have limited reserves. So there are many good reasons not to have cobalt or to at least reduce the amount of cobalt you can have. And this is what has been done. Also because cobalt's getting expensive, the more demand there is for cobalt, the higher the prices get. And when demand strips the supply, prices just skyrocket. So people had to find alternatives. And they did. These days modern lithium ion batteries use something like nickel manganese cobalt mixtures instead of just pure cobalt. And you have numbers like 532 or 811. The 811 means eight parts nickel, one part manganese, and one part cobalt. So today batteries use between 1 tenth and 1 third of the amount of cobalt that they used to use. There are also other possibilities. You can use something like lithium iron phosphate. Has no cobalt in it at all. But the problem is you only get about half the capacity out of the battery. And especially when you have something like a car that you want to have as much range as possible, that's not really an option, at least for this. It has other positive properties. Like it's much more robust. It cannot decompose thermally. Like a lot of the cobalt materials can. But it's possible. Lithium sulfide. Lithium sulfide is something that everybody would really want to have. And trust me, it's not for one of trying. Because sulfur is only half, an atom of sulfur is only half as heavy as an atom of cobalt. And you can have two lithium atoms together with one sulfur atom. The problem is the lithium has to, somehow you have to get rid of the, you have to divide the lithium and the sulfur. And when you divide the lithium and the sulfur, at some point you do it in stages. At first you have two lithium atoms and one sulfur atom. And at some point you have, I don't know, one lithium and one sulfur. And then you have two lithium and three sulfur and so on. And you do it in stages. And one of these stages, unfortunately, is liquid inside of the electrolyte. And that means that your cathode is now suddenly soluble. And it begins to slowly but surely destroy itself every time you charge or discharge the battery. And this is a problem that hasn't actually been solved yet. There are companies that sell these lithium sulfide batteries.  And the way they did it is by just putting a heck of a lot of material, a heck of a lot of lithium sulfide into the battery so that it, well, it still destroys itself, but it takes longer until it's completely gone. The other possibility is air. Lithium air batteries. Also one of the dreams that everybody wants to have and lots of people are trying is actually this is, this actually works almost like a fuel cell except with lithium on one side instead of hydrogen and air on the other side. The problem is that you now form, you form a lithium oxide on one side of the, on the cathode side of the electrolyte. And it's very hard to really maintain the integrity of this whole thing. And especially, I mean, it works in very thin layers, but if you want to have a thick layer and you would need a thick layer in order to actually exploit this because, I mean, remember what you have here is just lithium on one side, only lithium atoms and nothing else on the other side. That would be great. That would be perfect. It would be like two kilowatt hours per kilogram of battery. That would be really nice, but it really doesn't work. You need, you only get it in very thin layers and then you have a relatively speaking thick layer of electrolyte between that. And so long as the electrolytes that you need are so thick that they make up more weight of the battery than the actual lithium you're shoveling back and forth, the actual capacity is still worse than what we have today. And you also have to make sure you can cycle this without losing any of the lithium on the air side. And it's a bit of a mess. It's a bit of a problem and nobody had solved this yet, has solved this yet. Yeah, okay. I used to have the other slide before that, that's why. Yeah, lithium is just as rare as cobalt. And we have to replace this at some point maybe as well because lithium supply is limited and we have to get like 20 times as much batteries into production as we have currently. Okay, anode materials. Right now we have talked about one side of the battery, now it's the other side. Do you remember the graphite with the six carbon atoms? Well, you can improve this. If you don't use graphite, you can use graphene or graphite or some nanotubes or multi-walled nanotubes. Unicorns might help, maybe unicorns can make those cheaper, but no, right now you can find a lot of papers and a lot of science being done with graphene and nanotubes and so on, and it works. It actually does work. The problem is this is better expensive as gold, maybe not quite but almost and it's not useful for batteries right now. Maybe someday somebody gets to make those on the cheap and then it's an option. Silicon and phosphorus could help as well, it could improve upon the graphene, on the graphite have much higher capacities because especially with silicon, silicon forms an alloy with lithium and you get much better ratios. And so you can get much higher capacity. The problem is when you form such an alloy, what you get is much bigger, the electrode just gets much bigger, it gets four times as big as it was before and this puts a lot of stress on the material and it starts to crack and basically every time you use the battery, again it destroys itself. That's not helpful. Maybe, I mean there are tricks, some people make lithium like the wafers we use in chips and make them very small and you have very small structures that can store the lithium inside of them without cracking because they are very small but they never talk about price for some reason. I don't know why, I think it might be too expensive. Okay, the other thing you can do and there is active research and it's quite promising actually. It's pure lithium. Just nothing. The reason why nothing hasn't been done before is the lithium, when you grow lithium by electrochemical means, you just put one atom onto whatever lithium is already there and you do it by an electric field and all the atoms go wherever there is the strongest electric field. Problem is the strongest electric field is wherever there is like a little peak, a little bit of like, yeah, like a needle, the point of the needle or something like that and that's where they go. So what you get is dendrites. That is like small needle like projections that grow ever more and ever faster and that has prevented use of just pure lithium. Even though that would essentially half the weight of the battery. That's why people want to use it. You would just cut the battery and the weight of the battery in half and get about twice the capacity. What you need is solid electrolytes because you see right now the electrolyte, that's the stuff that's between the cathode and the anode is a liquid and that's why these dendrites can form. When the electrolyte is solid, like in the sodium sulfur battery, you know like the hot stuff that we had before from Ford. There's already something solid in between there and so nothing can grow through it, at least if it's solid enough. And people are working on this. They have made some advances. One of the problems is it's still a bit too heavy. The electrolyte's a bit too thick and too heavy and it's a fairly slow process. I mean, after all, it's no longer liquid. You have to get the ions through a solid material. So, the other problem, yeah, as I said, I switched two slides around, so now we talk about sodium. Sodium can replace lithium. As I already said, sodium is about three times as heavy as lithium, so it's not perfect. But on the other hand, since lithium currently only makes up about maybe 3 to 5% of the weight of the total battery, switching to something that's three times as heavy isn't quite so bad. One of the problems is that there's a lot less development that has been done on using sodium instead of lithium, simply because people started using lithium because it was the best performing material and there was plenty of lithium around. Why not? I mean, especially in the 1990s, lithium was mostly used as a grease or as, I don't know, like for colors, I think. They didn't use a lot of it, so there was plenty. There was a lot of supply of it and so why waste your work on sodium when you have something that works and something that is always going to get you better performance? So sodium will always be the second best in performance and so people didn't really start development on it. They have started development on it in the last couple of years, maybe this decade. You get a lot of more papers if you search online in scholargoogle.com. If you didn't know that page, it helps a lot to find scientific material. You find a lot more work on this and there are even some companies that are selling them more like as trials than as actual products but at least that's something and they have capacities of 140 watt hours per kilogram and that's similar to what we had in the year 2000 in lithium ion batteries. So development lacks behind about 20 years, roughly. And they still don't have this same kind of durability and cycle life that we expect today. They can sustain maybe two or 300 cycles. These days we expect a lot more than that. All that is the result because there has been much less development in the materials overall. Sodium is very similar to lithium but there are always some subtle changes and it just needs to be understood. It's simply you need a lot of scientists on benches and in front of their computers, crunching data, doing experiments just to find out what we don't understand and what we do wrong. Yeah, the other problem is, I mean batteries are great for stuff like this microphone or my smartphone or maybe a car but at some point you want to store more energy and batteries won't cut it. At least not lithium batteries, sodium maybe. Sodium, there's huge amounts of sodium. We're not going to run out of sodium, trust me. But you still have, when you have a battery, you still have to purify the materials, you have to assemble them. There's a lot of processing going on and that's a problem when you want to have something that's really big, something that can store a huge amount of energy like we need for storing something like the grid level energy. I mean if you read about it in the news or in articles you usually find something like this. This is from June. This is perfect for solar energy. As you can see, lots of solar energy but right now this is where we had this month. Almost no solar energy and we had some wind except when there's not and we kind of need to store the wind energy in order to have energy when we need it. With solar energy it's much easier. But the trouble is we're here at 91 degrees north and at 91 degrees north here in Leipzig, for example, it kind of looks like this. In winter it's cold and it's cold because we don't get a lot of solar energy right here. It's very different when you're somewhere in California or even in Spain. I mean Spain is already a few degrees further south and they get a lot more sun in winter as you can tell from the temperatures actually. And so you can rely much more on the cycle of the solar energy like every 24 hours and so on. But here we need much more storage. We need to be able to store energy from times like these and use it in times like these when you don't get any. And now we're talking about, I mean, we need 80, I think, yeah, I have it on this slide. I mean the amounts we need is huge. 40 gigawatt hours, by the way, 150 gigawatt hours is the worldwide production of lithium-ion batteries. Okay, 40 gigawatt hours in Germany is enough for 30 minutes of power supply. Let's say we really need a heck of a lot. One of the large scale, what we consider large scale storage possibilities is pumped storage and problem here is physics. Physics like this, E is M, G, H. M is the amount of water, the mass of the water. H is the height to which you pumped it and G is the gravity. We've maxed out gravity. Actually, in this solar system, you will not find a solid surface that has more gravity than ours. So we cannot optimize that further. I'm sorry. Height, if you get something that's better than this, I mean this is not 360 meters, but I assumed here 360 meters for one simple reason. It's easy to do the math on. Then you need one ton of water to store one kilowatt hour. And one kilowatt hour for one ton of material, that's a heck of a lot. And that's why these are almost always huge and don't store a lot of energy. And the total storage is something on the order of 40 gigawatt hours in Germany. There have been other proposals like compressed air storage. What you do is here in Germany, we have, there used to be a sea here around Germany and a lot of the salt water from the oceans evaporated and left behind a lot of salt. And we get these salt domes. And so what you can do is you can make holes inside the salt, simply by pumping water down into the salt and dissolving the salt. And yeah, then you have a huge hole in the ground, except you cannot see it from the surface. Here it's a bit better than the pump storage. When you do the math on it, you can get about three kilowatt hours per ton of salt that you've removed from the ground. This assumes 70 bar. You can have, if you go deeper into the ground, you can have higher pressure. You can have more than this, but it's kind of limited. And also you have a hole in the ground. And this hole will collapse sooner or later. I mean, these holes are stable for us. They're stable for centuries, maybe thousands of years, but eventually they will collapse. Something will go down. And sometimes when people don't pay enough attention when we're making these holes, it actually happens. And you can find accidents where this actually happened. Okay, how does this work? Well, it's very simple. You pump the air in and you take it out. You go let it blow through a turbine. It's almost like wind energy, except for really good turbine. And you get energy from it. Problem is when you compress the air, it gets really hot. And then you store it and it gets cold. And then you let it out and you decompress it. And when you decompress air, it gets even colder. And that's how you lose a lot of energy. And so what is done, one of these is in Germany actually. There's one in Germany and one in the US. And what they do here is they burn natural gas in order to make up for the heat that was lost. It actually makes the power plant itself more efficient, but yeah, it's not exactly renewable. What people actually want to do is store the heat. So as I said, when you compress the air, it gets hot. And then you want to store the heat. And when you decompress it, you put the heat into the decompressed air and heat it up again. And it gets much more efficient. So instead of 45%, you get up to about 70%. Oh, damn it. Okay, I was way too slow. The way you can store the seed is something like this. Thermal storage, there's a lot of thermal storage using liquid salt. Liquid salt is not terribly efficient at that task, especially because not very high temperatures, but you can actually use stones like volcanic rock. I think Siemens is building something like this. And what they use is basalt rocks, like this big, I mean, a couple of centimeters. I mean, like the pebbles you can see here, it is a very, very, very slow, very slow, very small storage, thermal storage. You want to build these things big. And when you build them really big, they're really efficient because it's a matter of geometry. When you have something like a cube and it's one meter on each side, and you make it two times as big, two times, it's two times as wide, two times as long, two times as high. It has eight times the volume, but only four times the surface area. And the problem is you lose heat through the surface area. So when you have eight times the volume and four times the surface area, it means that your heat losses are only half as big. And that's not actually enough because when you take something like this and you build it two times as big, you will also make these parts two times as big, and that's the insulation. And when you make the insulation two times as big, you also reduce the losses by a factor of two. So when you build something like this really, really, really, seriously big, you have very small losses. You have losses for small ones, you get losses of about 1% per day, and when you build them like 1,000 times as big, you can, in theory, get one tenth of that. In theory, you could store heat for weeks or even months in these, and you need, I thought I had this memorized, but you need, I think about 10,000 tons in order to store one gigawatt hour of electrical energy because you can actually use this to store electrical energy. Yeah, okay, I'm sorry. Everybody enthusiastic about hydrogen, I will not be talking about hydrogen because I'm running out of time. And yeah, big thing here is it has really cheap raw materials, simple stones, and capacity is fairly high. You get about 30 to 60 kilowatt hours per kilogram if you try to take the heat because you can heat these up to about 700, 800 degrees Celsius and run them through a common turbine, like the turbines you have in a coal power plant, and you get an efficiency of 45% out of this. That's not very good, especially not compared to a battery where you would get efficiencies on the order of 80% or 90%, it kind of depends on how fast you charge. If you have a Tesla supercharger, you have much less efficient batteries than if you take it slow and charge it slowly. But for something as simple as this, 45% is pretty good, especially because you can scale it up into the gigawatt hour range and even tens of gigawatt hour range, which is kind of like what we need. Yeah, and all you need is stones, fairly huge amounts of stones. The reason why I think this is a pretty good idea, even though it's not perfect, as I said, 45% you waste half the energy is because hydrogen is even worse. Yeah, okay, I tried to do this in two minutes, I'm sorry, it's going to be very fast. Okay, hydrogen, in theory, it sounds great. You split water into hydrogen and oxygen, you use the hydrogen to get energy and you have really great density of energy. You know, 39 kilowatt hours per kilogram is really great. You have theoretical efficiencies of 83%, and yeah, that sounds great, but in practice, well, the problem is, the efficiencies are usually related to the lower heating value, which is not the higher heating values, so there's a fudge factor of about 18% in the efficiency, or actually 10% in the efficiencies when you get to the real efficiencies. So when you have, when they say, okay, 60% efficiency for the electrolysis, no, when they say 70% efficiency for the electrolysis, the reality is more like 60%, and for the fuel cells, it's more like 50% than 60%, and the reality is, when you take all the losses into account, including the storage, you get about one third, and very often much less than 30% of the energy out of it, then you put into it. I'm sorry. That's a big problem. Okay. I'm sorry, I've run out of time. Okay. Thank you for his great effort. Yeah. I couldn't see, I really couldn't see the clock until just now. Okay, thank you. I think it was switched off at first, that's why I kept looking at my watch. Sorry.


TFNN headline news update Welcome folks. We had the Dow industrials finished down 55 Nasdaq off 20 S&P's down six and a half We get open we take a look at the S&P's folks what you're gonna see is this now the bottom line is that you actually didn't hold price We had a rejection of lower price a little bit earlier bottom. That's it's a close call, but bottom line is it Yeah, it's still a close call. We closed out at that 310 30 and that 310 30 Yeah, it's the ying and the yang this thing can go to the high tomorrow. I mean, that's how this thing is shaking out right now As we commit to the close what let's go take a look at this ESZ 9 what you're gonna see out here is that the ESZ 9 You're gonna see when I started the three o'clock show bottom line was a direct Rejection of lower price bottom line is that we were we were up to the 3108 level You came down now. You're gonna be lower tomorrow. You came down hard. So we came down to 3102 You have volume at that level meaning at the action that the lows 30 30 98 you had volume down at that level big volume too by the way That's that's gonna get tested more than likely overnight And the x100 same type of setup inside the end the x100 and you gotta remember we're coming into a Friday You're coming into the Thanksgiving holiday week next week and this is where things will slow down and the x100 same type of setup we hit 8258 or at 8269 expect that baby also is gonna come down into those lower levels the note and bond market bottom line Got to a higher high today Monster volume on the way up and couldn't hold price when you see that many times you back off a bit and then guess what you are right back top side Fast and furious far higher price and inside the 10-year today We got up to 130 oh to you had 2.4 million contracts monster contract volume folks and 30 year followed up right with it as did as did the TLT 30 year had Look at that volume 518,000 contracts. That's monster contract volume in huge We're gonna be right back top side. So picture your last swing point out here. I had 460,000 contracts that was the last swing point October 31 We pushed into that with 518 today bottom line notes as well as bonds want higher price Lower yield have a great night folks. Have a safe night come back here tomorrow morning 9 o'clock I'm a Mr. Larry Presidento great program. Have a great Tfnn has put together


So I'm in really big trouble if we don't manage to finish in the right time. So it is a pleasure to share this last bit of the second ESRB conference. Following the tradition started last year, we delivered in the last session, the ESRB research prize that was created in the memory of Ieke Banderhu, which is a founder of, in a sense, the advisory scientific committee that is currently administering the prize. Now, we got many very interesting submissions to the prize, it was hard to identify among the very best the current winners. I would like to take the opportunity if you have students or colleagues that fit the age requirement and the topic to encourage them to submit their work to this prize that is an annual event. It's intended to stimulate young scholars to do research in the area related to the ESRB mission. With this preamble, I think it is my pleasure to announce that this year's prize goes to Marco De Rico from University of Zurich and Tariq Rokni from MIT and University of Ghent for their paper, Compression Over the Counter Markets. It's a very interesting piece on something about which I knew very little when I read the paper, which is a multilateral netting in the case of their particular application in the paper to Over the Counter Derivative Markets. I have to be brief, so let me not elaborate too much. We are gonna give the chance to one of the winners and author of this paper to present the work to you, but we were impressed by the quality of the material and the combination of very serious theory. There are propositions actually very challenging mathematically trying to deal with what will be efficient algorithms, efficient rules for producing this multilateral netting in a way compatible with preserving trading relationships and with not touching, if my understanding is correct, the net position of those who operate in these markets as you know are characterized by enormous volumes of trade and enormous, therefore, resulting gross position. So with these algorithms, as Marco Derico will tell us in a sec, you can get an impressive reduction from gross to net amounts. So without further ado, let me call to the podium to Marco Derico and join me in applauding him and his co-author for having won this prize. So Marco, the floor is yours. You have 15 to 20 minutes to present a summary of your paper. Thank you, thank you. So okay, of course, thanks to the AAC for giving us this opportunity. We are extremely, it's a great pleasure for me and I think also for Tariq who is in the US at the moment and of course, thanks a lot to all the people that commented on our paper during this year, many of those are in the room also, so thank you very much. Of course, a big, big thanks to the secretariat because great part of this work is in particular the empirical part of this work was carried out using indeed data. So we came from a session where there was a lot of discussion about data, well, the issue was how data can be used. And okay, I have roughly 15 minutes, so I will try to walk you through what I'm gonna tell you. I mean, I cannot go into the details of the paper but as Javier mentioned, it looks very technical but the underlying intuition is very simple. So I will try to convince you that there is something simple and then the technicalities can be built upon that. So I'll give you the main intuition. Then I also give you the historical background because as you may infer from the title of the paper we are trying to reduce something in over-the-counter markets, in particular over-the-counter derivatives markets. Like in the previous session, we heard a difference between net and gross. So this will be a key point that I'm gonna make. So I will go through the theory, explain the key concepts and the last point will be about the empirics. In particular, I will show how we use the emu data in order to give estimations, various estimations about how compression techniques can be adopted in the market. So as you may recall, during the crisis but even afterwards, one of the main themes with that OTC derivatives markets were complex, opaque and they were characterized by large notional amounts in the orders if you recall of trillions. We're talking about trillions of dollars and the main question that we were wondering is what characterized these large notional amounts? And what compression does in a nutshell is a post-trade technique. So counterpart is trade these derivatives and then X post, we run an operation that reduces the gross positions while living basically unchange your net market risk. So as an example here, I have a network of obligation. Now the diagram is very simple to understand. Imagine you have three, four financial institutions and that whole money to each other. This can be a contingent claim like a credit default swap. Yesterday we heard from Richard, imagine this is a situation where a credit event is called and that money is due between counterparties. So they have to pass around that money in order to fulfill their obligations. Now, if you look, the gross amounts, I don't want to, given time constraints, I don't want to go into the marathematics of this but just to understand, you have a total gross notional of 45 in the system and each participants has a given net position. So in the moment of payment, for instance, B expects to give out 10 but it also expects to receive five, correct? The same thing goes for A, it expects to receive 20 but it also has to give out five, okay? So in the moment, A, for instance, doesn't receive the money from C, then you enter counterparty risk, typical example of counterparty risk. So at that point, A may not have enough liquidity to pay B, right? And this can create a chain of distress, chain of default, et cetera. So how do we act on this network of liability? A does not have the full view of the market. So A believes that they have to receive 20 and they have to give out five. Now, if we share information in some way, look at it, we can eliminate the minimal liability from the system. So we subtract five from each of these linkages that you see in the network and this is what happens. We have reduced the system from a previous amount of 45 to a total of 30. So we have a gross notion of reduction, gross notion of obligation reduction of 15. And if I manage to convince you about that, I think the rest will come very easy because the rest is how we find optimal ways to solve this problem in a very complex environment. A key, I believe, a key economic interpretation of this activity is that it's a sort of system-wide deleveraging process. So assets and liabilities are reduced, but this deleverage does not entail any asset sale nor injection of capital. So it's purely deleveraging that is achieved by correctly using information. And what we do in our paper is exactly to optimize these type of techniques. So I want to take a step back about the size of what you see with these markets. Credit default swaps at the onset of the crisis were in the order of 60 trillion. And immediately after they started shrinking. Now the question is, did the market disappear or did something occur that made these swaps disappear? So what you heard before is that many authorities are looking into data, but not having granular data. It's very difficult to see what really occurred on those markets. And the surveys and reports attribute this decline exactly to compression. In particular, both PIS and ISTA achieve these large reduction in notional amounts and notional obligations to compression. And if you see how we arrived there, we do need to understand the market structure because otherwise you can't understand the level to which this level of reduction of notional can be achieved. And in order to do that, you need to draw a CLI's model of the market. This can be done using data. So data are consistently reporting this type of structure when you look really a counterparty, counterparty relationship. This is a very good model of CLI's model, how the market looks like. You have, for instance, sellers of CDS and buyers of CDS at the very end points of this network. And then you have a large amount of dealers that are interconnected between one another. And this may sound surprising, but this is what we find consistently in the data. The dealers in the market actually account for 80% of the total notional. So the end user roughly 10 and 10, and then the dealers for 80%. And a large part of these obligations indeed lies within this intra-dealer set and within these closed chains of intermediation. The response to this very complex network structure was exactly to collect more data. So to come back to the, and this was the reaction that the G20 leaders committed to in post-quadruce summit. The problem is that the compression was not new to the market. So this production in notional amounts is not something we came up with. It was in the market. But it was mostly seen in the early 2000 years as just good housekeeping. It would help it to reconcile some trades to have some payments, but there was not much more than that. Importantly, in the global financial crisis, the immediate aftermath, actually few weeks after Lehman defaulted, there is a very nice article by the economists that is called The Great Untangling and relates exactly to credit derivatives. In particular, credit default swaps. And this article mentions that only now the industry is discovering the joys of compression. So that notional amounts, that huge decline immediately after the crisis is probably due to compression. And we find in our, with our paper, exactly that the enormous amount, so a three-fold reduction from 10 trillion, so 60 trillion to 30 trillion, is indeed completely reconcilable with compression techniques. Importantly, there's also not the pressure that put down this market. So it helped this market shrink. And it was exactly part of the regulatory response to the crisis. So it has capital requirements, leverage ratios that take into account also for gross exposures. And of course, the issue of margins and collateral. The more gross position you have, the more you may expect to have to post collateral. So if, especially for unclear trades, you ask for more collateral, then it would be way easier for participants to try to find ways to reduce that gross amount. And indeed, in a post-crisis assessment, Duffy mentioned recently, a very nice paper, that compression is indeed the greatest source of improvements in OTC derivative exposure. So this is what we are looking into. Compression is used today at the bilateral level. It's very easy to do. It reduces to bilateral netting. You don't need any sharing of information. But if you recall in the previous slide at the very beginning, you need to have the full picture. Otherwise, you can't intervene in the network. Or at least to have quite some good level of information on the network. And so what participants do that they go and talk to external providers. And they ask this, submit trades, and they ask, can you optimize and reduce my gross exposure? What is compressed, interest-free swaps, both with CCPs and without with our cleared and unclear, CDS, again, single name and index, more recently, more complex products are getting into compression. And I want to mention compression is an evolving service. So now it's getting more and more into complex products. And it will require more and more financial engineering. The numbers are staggering. Trioptima, one of the major compression provider, claims to have eliminated one quadrillion cumulative throughout from 2003 to 2017. One of the major cleaning houses, the derivative service of my major cleaning houses, reports say 380 billion, so only 2016, is that talks about roughly 70% of reduction. Compression is also included in the regulation. Mifir and Emir are supporting this view. But there is one problem that despite this global support, what we found is that compression by changing the network completely reshapes the type of risk that one may see in the market. So there may be a sort, and this is why we're very interested in this topic because there can be a shift from a local, say, individual incentive to perhaps increase systemic risk concerns. And in particular, I mentioned the risk concentration because if compression can be done only between the large dealers, these reduction in counterparty exposure will increase relatively this exposure to the end customers that are typically known banks. And this may create problems that we all know. Another important point is the legal and institutional framework, especially if we understand compression and we say that is a good thing for our financial market for systemic risk, we also need to have a good regulatory framework to make it work. Also, there is a lack of credibility because the techniques that are used by compression providers are rather opaque. We don't know what these techniques are. They're very difficult to understand at the moment. So we had to somewhat try to understand ourselves what the compression provided, what we're doing. And also, of course, this is due to very limited literature. I mentioned here very interesting papers. What we do in the paper is that we felt that there was a lack of research combining the theory and empirics. And this is why we motivated us to work on this. So given for time reasons, I want to skip through this because what I want to focus on is the notion of excess notional. If, as we saw before, there is some notional in the market that is not needed to satisfy the net expected exposure that you have in the market. And this is quantified, this is the only formula I'm gonna show. This is quantifiable like this. It's very simple. It's the difference between the total gross notional and the minimum amount of notional in the market. Of course, not all these notional that is in excess can be removed from the system. And what we do is that we try to find ways to remove this excess in various compatible ways with strategies of participants. Now, it's important to understand that excess is present in the market only if and only if there is intermediation. So the dealers in the market are those that originate this excess in the market. And what we do is that we look at different classes of compression. I'll go in particular, we focus on a conservative type of compression that preserves the type of counterparty relationship. So as there was a relationship, I say, I was expecting to receive 100 from Javier, the new trade, the new relationship cannot exceed that 100, can only reduce, can be also to zero, can eliminate the relationship between you and I, but at the same time, it cannot increase. And then we have a non-conservative that basically allows participants to reshuffle completely their counterparty relationship. These may occur in certain cases and it is a good benchmark at least. So, of course, what happens in terms of efficiency, so in terms of notion that you can eliminate, you need, you have way more efficient in a non-conservative case for a reason of constraints. Whereas if you want to keep counterparty relationships, then you're never gonna eliminate all the excess in the market. This is very important because in particular, in terms of efficiency, the natural structure that these two different types of compression generate, I wrote them down at the end of the slides, is that they produce natural structure that preserve intermediation, but eliminates close chains, whereas the other type of counterparty, the non-conservative completely eliminates compression because this is simply matching between sellers and buyers. Now, I want to give you an example. This is when we go from a current outstanding network to a conservative and non-conservative case, so we have eliminated the intermediation in the right-hand side. And okay, I want to go briefly on hybrid compression. We simply want to allow inter-dealer relationship to be switched, for instance. So a dealer that was previously buy something from Javier and then I can become the seller. It's very simple. We have produced efficiency rankings, but more importantly, I believe, is the empirical application. I'll take one minute if I'm allowed to do it. We use data exactly from Emir, so we use credit default swaps, cleaning procedure, outlining the SAP Occasional Paper 11. We take monthly data from October 14th to April 16th and in order to make sure that the network that we'll build is perfectly fungible. That is, it makes sense to subtract and add elements to that network. That is, they have the same payoff in terms of, they have the same product. We're not summing apples and oranges. We find, we devise a way to fix maturity and same reference entity. Then we implement the algorithms that we found and we run an analysis, especially on the finding levels of excess and compression efficiencies. So this is the result. The total excess oscillates between the various reference entities from 50% as a minimum to the maximum, so 90% of excess in the market. And this is more or less stable across the various snapshots. So you see, we potentially can eliminate, on average, between 75% and 76% of gross motion in the market. Now the question is, how much can we eliminate with the various algorithm of these 70% and the answer is, well, quite a lot. If you look at conservative compression, the blue, this is a block spot, and you look at the red line at the median level, we can eliminate up to 90% of this excess. So if you think about that, this means that you can eliminate 60% of total motion in the market with this type of compression. Now, I'll conclude. Networking markets generate excess. This is due to intermediation. This excess can be removed by compression. This is widely used in derivatives market, and we also do an important ability in periodical application, showing how this data can be used. Importantly, because this can also lead to probably some discussion, is that we are trying to understand how this tool can be used in a macroprudential way. That is, imagine that you want to compress the liability of the Lehman, that's the next Lehman type of, what data do you need, what counterparties do you need to contact, what counterparties do you need to convince to run a compression exercise? And of course, since compression reduces gross notionals, it will have an impact on margins. So it can be used counter-psychologically. By running constantly compression exercise, you won't face large levels of margins in case volatility increases. Of course, an important point is the epistemology of market size. That is, if markets went from trillions, so 60 trillion of credit default swaps to 10 trillion, and for individual reference entities, say you have a sovereign credit default swap in the order of one trillion, does it really mean that there's a need of one trillion of insurance on the sovereign? Well, we find that the large part of this notion can be eliminated. Last but not least, we are working on netting efficiency with respect to CCP and impact on capital, collateral price, and of course, something for future is the legal framework. So thank you very much, I hope. Thank you very much, Marco. So I think we have time for a few questions, and I will start with two. In some sense, your list of ongoing research was already providing sort of the answer to some of them that probably this is a very interesting policy-connected area for research that doesn't get exhausted by your paper as most good papers happen to have as a feature, that most of the questions are for future work. So one first question. So you saw in your paper that with compression techniques, you can achieve massive reductions of gross positions. Now, if I am a macro prudential policymaker concerned about which risk for the system is behind those positions, is the declining gross proportional to the decline in the underlying aggregate risk, or is it just an image?


What's up everybody, Jason here for jaspyscasebreaks.com. We're doing a round of number block farm Peckable, picker team number 21. This features Pittsburgh, Buffalo, Dallas, LAC, which is the Chargers, Detroit, Denver, Seattle, Baltimore, Chicago, Los Angeles Rams, and the Carolina Panthers. And again guys, you get a piece of all these teams and if there's any hits for these teams they'll be distributed via a serial number break. You get randomized a number from 0-3-9. There's your examples there on how it works. If they do hit, we go by the first number on the left side of the serial number dash. And there you go guys. So here's the dice roll, here's the customer names. These customers here, John, got those straight up, got all five of them right, or six of them. And then Nick, Jeff, Aaron, and Alan got those from a pack filler. And then of course 0-3-9 there. So let's click roll. It is a six and a two, eight times. Good luck. One, two, three, four, five, six, seven, and eight. Eight times, six, two, eight, eight. John down to John. So this will be for this one here. Eight, one, two, three, four, five, six, seven, and eight. Seven down to eight. Now, let's get this a little bit bigger here. So John, you have a spot seven, Alan with spot six, Aaron with spot three, John with two and five, Jeff with one, John with zero, as well as four, Nick with nine, and then John with eight. So again, we'll alphabetize it there, and there you go, guys. So that's the first randomizer I needed to do. Now I'm going to do a second one in a separate video, guys, for the 18 RMB. And then we'll be able to break impeccable, guys. So good luck, everybody. Thank you, guys.


Hello and welcome to the Tracy Johnson show. I'm Joe Wamba joined, of course, both Tracy Johnson, head coach of the women's ice hockey team. And coach, you guys travel up to Becker and play that semifinal rematch game and beat him twice. We did. We knew going up there, it was going to be our first taste of the long bus ride and having to deal with bus legs and get those shaken out pretty quickly because we knew that March 5th was the date that Becker had in their mind and that they wanted revenge for. So we had to take it to them as well. And you guys, both goalies earned a shutout over the weekend. Yeah. Pretty impressive. Yep, they were solid between the pipes. They didn't see as many shots as we were putting on net, but anytime they needed to make the save, they were doing that. So that's all you can ask of a goaltender. And let's talk about Chelsea Blackburn, of course. It kind of has Becker's number here. She's got nine goals in the five meetings that we've had with them. And four of them are game winners. I don't know what it is about Becker, but she seems to really dial it up a notch. I mean, she dials it up a notch every game she plays and plays with intensity. But for some reason, I don't know why she has Becker down as one that she just likes to really put the puck in the net. But yeah, four game winners in five games is pretty impressive. She's got to know somebody on that roster.  I'm fine with it. And looking forward to this weekend, another conference competition with two of them against Johnson & Wales at their home. Yeah, so we take off again and have to deal with working through the bus legs and shaking those out as quickly as we possibly can. And Johnson & Wales is a good team. They're coached by a very good coach. And they brought two very competitive games to Endicott this past weekend. So we have our work cut out for us and have to make sure that we're focused on getting the fast start this entire week. We have to be focused on that. Well, coach, we wish you the best of luck with those bus legs again and a good week of practice here. And we'll be watching those games for you. Thanks so much. She's Tracy Johnson. I'm Joe Waman. This has been the Tracy Johnson Coach's Show.