Ant Scans, Lunar Chickpeas, Hidden Galaxies & Superconductivity
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The path to room-temperature superconductivity: A programmatic approach
Room-temperature superconductivity, a game-changer for technology, is still a tough puzzle, but advancements in prediction and engineering could help solve it. By improving our understanding of how to create new superconductors and control their properties, we might soon unlock this incredible phenomenon that can enhance energy efficiency and revolutionize many technologies.
Identifying astrophysical anomalies in 99.6 million source cutouts from the <i>Hubble</i> legacy archive using AnomalyMatch
Imagine the Hubble Space Telescope has been taking photos for over 30 years, and nobody has had time to look carefully at all of them. There are about 100 million little image stamps sitting in a digital archive, most never closely examined. These researchers built a smart computer system called AnomalyMatch that works a bit like training a dog to sniff out truffles — you show it a few examples of weird, interesting things, and it goes hunting through the entire archive to find more. In just 2 to 3 days, it flagged hundreds of extraordinary cosmic objects: galaxies crashing into each other, galaxies with gas being ripped away so they look like jellyfish, and gravitational lenses where one galaxy bends light from another galaxy behind it like a cosmic magnifying glass. The exciting part is that humans alone would have taken centuries to do this job.
High-throughput phenomics of global ant biodiversity
Imagine being able to take a detailed 3D MRI of a tiny ant — seeing every hair, joint, and internal organ — without cutting it open or even touching it. That's basically what this team did, but at incredible speed and scale. They used a giant particle accelerator (a synchrotron) that shoots powerful X-rays to scan 2,193 ants from nearly 800 different species, creating detailed 3D models of each one. They then put all these 3D models on a free website for anyone to explore. Think of it like Google Maps, but for ant bodies. Scientists can now use computers to automatically compare body shapes across thousands of ants, pairing those body blueprints with DNA data to understand how ants evolved and why different species look so different from each other.
Bioremediation of lunar regolith simulant through mycorrhizal fungi and plant symbioses enables chickpea to seed
Imagine you tried to grow vegetables in crushed-up volcanic glass mixed with toxic dust — that's basically what Moon dirt (called regolith) is like. It has sharp, jagged particles, almost no nutrients, and contains chemicals that stress plants out. Scientists wanted to see if they could make Moon dirt farmable. They mixed it with worm poop (vermicompost), which adds nutrients, and introduced a special fungus that lives on plant roots and helps them absorb water and nutrients. The plant they chose was the chickpea — a hardy, protein-rich legume. The result? When the fungus was present, chickpea plants actually grew flowers and made seeds even in soil that was 75% Moon dirt. Without the fungus, no seeds at all. The fungus also helped the Moon dirt clump into small balls, which makes it less dusty and dangerous. Think of it like the fungus being a personal trainer and nutritionist for the plant, helping it survive and thrive where it normally couldn't.
Transcript
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Intro — four science stories and the quiz
0:00They identified 1,300 objects that have an odd appearance, right? And more than 800 of these objects have never been identified in scientific literature before. The secret to farming on the moon is worm poop and fungus. Not quite exactly what NASA put in the brochure. However, could be the future of a permanent lunar presence. Now, that could transform our society more than I think any other technology that I can really think of. Hello internet, this is your captain speaking. Lester Nare is always joined by my co-host and our resident PhD, Krishna Shoutery. This is a rundown episode. We'll be covering
0:41four stories at a high level. If you're interested in our deep dives, check out the previous episodes from this week. We may even, in fact, have another round of are you smarter than a scientist? So, in this week's rundown, first of the four stories, 3D scanning of ants, thousands of ants with a particle accelerator, published in Nature Methods. Fascinating story. We're following that up with growing chickpeas on the moon with fungus and worm poop. The good stuff. Scientific Reports brings us that one. We will follow that up with some discoveries from the Hubble archive. And that Hubble archive
1:22discovery of cosmic hidden anomalies, but we used AI to discover them. That was an astronomy and astrophysics. And we will end with an LK-99 throwback about the state of room temperature superconductivity, where we may have a roadmap that was published in PNAS. We are going to learn about the science from the ground up today, because this is from first principles.
3D scanning ants with a particle accelerator
2:02>> So for our first story, we are going to be talking about ants, like the movie, the Pixar movie. Uh 3D scanning of thousands of ants with a particle accelerator team led by researchers at the Okinawa Institute of Science and Technology uh used a cyclotron particle accelerator to create detailed 3D micro CT scans. I've gotten a couple CT scans, but not a micro one. Uh of a 29 2100 ant farm colony with nearly 800 species. And this was published in Nature Methods because the method is what is interesting here. Yes. So for the longest time, if we want to find if we want to make like a 3D version of
2:44these really tiny insects, and we want to do it to super super high resolution, you use something called a micro CT scanner. This thing is going to send out x-rays, and then those x-rays are going to scan and allow the scientists to examine like the physical structure, the stuff inside without actually like destroying the specimen. Each of these scans takes about 10 hours for a single specimen. So it's not very high throughput, right? And we want to be able to do a lot in parallel. And so that's what these researchers did. They employed the Karlsruhe Institute of Technology, which has a giant synchrotron particle
3:24accelerator, x-ray imaging. It's also got robotics. It's also got artificial intelligence. And what they're able to do is generate interactive digital reconstructions of 800 ant species. Mhm. It's pretty incredible. If we If we look at the the headline, right? And if we look at this animation, look at the detail that we're getting this ant. >> This is This is crazy. >> Yeah. This This at micron resolution of an ant, right? And this is rendered using AI because a lot of times we get little slices when we do a CT scan, we get like little slices or like different sort of configurations of what the ant
4:06is in, depending on the specimen, but you can use AI now to reconstruct that 3D version of the ant. It's It's really quite amazing. With that setup they've
Antscan, AI reconstruction, and why it matters
4:15scanned 2,000 species Sorry, 2,000 specimens in a single week, 800 different ant species. The effort is called antscan. They've got a free public website called antscan.info, and it's kind of like a Google Maps for ant anatomy. The data is also synchronized with genome sequencing projects. >> cool. So, you've got 585 of those scans linking to the genomic data of about 186 different species. I think it's a really cool application of particle physics and like particle accelerators that we don't really think about. It reminds me of a very old story that we did on this podcast about the T-Rex bone. Yeah. Remember that?
4:57>> Yeah. Where it was like they found um blood clotting in a T-Rex bone and showed that, you know, the T-Rex was capable of rapidly healing its bones after some kind of, you know, I think it was a fight with another T-Rex, probably. But it's just it it's a really cool application of particle accelerators that doesn't have anything to do with fundamental physics. It's just leveraging it as a tool to do very high resolution 3D imaging of biological specimens. Which if you asked me before I, you know, we did the original T-Rex story, yeah, which my reaction was like this is unbelievable because we're sort of
5:38repurposing this very expensive Mhm. uh large-scale device Yeah. to become multi-purpose beyond its sort of initial mission or context. >> Yeah, and the scans are like so detailed that they they can be used for further training of machine learning systems to recognize ants in the field. For example, you know, I'm out in the field, I get some specimen, now I have a pre-trained network, a machine learning model that is trained using this really high-fidelity, really high-resolution data, and it can immediately tell me what kind of species it is, or at least what species it is most related to if it's a new species, right? Um it's also something that can be used for like
6:20if Disney or somebody wants to make What is it called? A visual effect. >> Yeah, yeah. Like with like a giant ant. You know, remember that that one movie where like it's like Honey, I Shrunk the Kids? You want to make like a, you know, a giant ant visual effect for that. Now you can be really, really biologically accurate. So if you want to be as precise as Interstellar was in their replication of the physics of a black hole and the amount of science that went into creating so, now particle accelerators can give us animated 3D ants that are giant at very high fidelity. >> Yeah. I kind of is a little bit the the
7:01example you just brought up sounds a little bit like a Pokedex. You can tell if it's a Caterpie Yeah. or a Beedrill or a Weedle Yeah. or any of these, Butterfree. I'm trying to flex my Pokémon knowledge as much as I >> know any of I just know a Pikachu. And um Charizard. >> Charizard, classic. >> Yeah. Classic. Always interesting to see the intersection of different disciplines. >> Yeah. And how again past work can inform new work. And so this was again a methods story. Yeah. Uh fascinating and published in Nature Methods. Uh we have this coming out of the Okinawa Institute of Science and Technology, and the I'll let you you had the good pronunciation on the second institute. >> Oh yeah, that's the Karlsruhe Institute
7:41of >> of technology and Okinawa Institute of Technology of Science and Technology OIST is what we used to call it. I actually did a summer workshop there um for like computational neuroscience. >> That's so sick. It's an amazing like place. That's amazing. >> uh it's on a hill in Okinawa in the middle of the Pacific Ocean. Beautiful, beautiful spot. A lot of bugs, I have to say. >> of bugs. >> of bugs, but you know, it's a tropical island. And you know what does not have
Growing chickpeas on the moon
8:09bugs? This podcast. And if you've been listening or watching, or if you're a new listener, or a new watcher, we're grateful for you joining us today to learn more about the universe around us. A like, a comment, a share, a follow on any of the platforms helps us reach more curious people and helps us continue to do this podcast and deliver the best science podcast on the planet, in our opinion. Every week, day in and day out. And we're going to now transition into our second story, which is about growing chickpeas on the moon. Now, we are from California, but this story comes out of Texas. Mhm. Not only just out of Texas, but from
8:50researchers at UT at Austin and Texas A&M, published in Scientific Reports, where they demonstrated that uh they can successfully grow and produce seeds in soil that is very similar to the soil that we know exists on the moon. And if we ever want to expand the human experience beyond our local Gaia on planet Earth, being able to do agriculture in space is valuable. And it seems like we may have an interesting finding in this recent paper. Yes. Um trying to establish a permanent presence on the moon will require probably, you
9:31know, doing some form of agriculture there. Light is pretty easy to come by, but soil is pretty hard to come by because moon regolith, which is the name for lunar soil, is very very different from Earth soil. Earth soil has an entire ecosystem inside, right? There's bacteria, there's fungi, there's all sorts of creatures living in there. And so, soil is not just like a bunch of like, you know, small particles of rock, which effectively is what the in you know, the a biological part of soil is. You need a lot of these helper agricultural necessities to actually create an
10:12environment to grow crops. In The Martian with Matt Damon, right, he grew potatoes, I think, but he supplemented it with his own poop. Right? This is trying to get that dream a reality. Without the poop or with the >> Without the poop. In this case, it's not human poop. They're actually going for um worm poop. Ah, I see. Okay. So, what they're saying is we can take lunar regolith, which is this super, you know, kind of dry, dead substance. We can supplement that with both fungi, which are going to help the plants,
10:52and also poop from worms, where the worms eat like sort of biological matter and trash and other kinds of stuff that comes out of the human presence there, right? Cuz we're going to have a lot of like biological waste. >> Mhm. The worms can subsist on that, create organic material, we supplement that organic material into dead lunar regolith, and then we grow chickpeas, and it actually worked. That's incredible. >> Yeah, and one one thing that they actually did test was without the fungus, the plants did not produce any seeds. So, it's really important that we have the fungus, and we have this
11:32biodegradable waste that comes from the worms. So, part of the idea here is is like we know we can't we can't grow in a completely dead substrate. Uh we do need some biological ingredients >> Yes. mixed in to make the recipe work. Yeah, and they simulated the lunar regolith because obviously you can't like get the little bit of lunar soil that NASA brought back from its space missions. And now other people have also brought back with their non-human space missions there. But I mean lunar soil is very hard to come by, okay? I don't think you're going to convince anyone, "Hey, I want to grow chickpeas in your
12:12lunar soil." Right? That's going to completely contaminate lunar soil. So, they simulated lunar soil, and then they made sure that that sort of composition closely reflected the stuff that actually came back. And then they, you know, did this experiment with creating better soil with worm compost and fungi.
Are lunar chickpeas actually safe to eat?
12:33The secret to farming on the moon is worm poop and fungus. Not quite exactly what NASA put in the brochure. However, could be the future of a permanent lunar presence in better understanding how we can sustain particularly uh on the ability to have a food supply when we might not be able to send Starship rockets or whatever the defense prime rocket of the day is that can carry humans uh to the lunar surface. >> Yeah, and one thing I do want to mention is that we don't quite know whether these grown chickpeas are safe to eat. Ah. We just know that they've been grown, and they look like chickpeas.
13:13Mhm. Okay. Right? In every sense of the word. So, there's still more testing that needs to be done to make sure that these plants don't absorb like harmful metals that are in the soil on the lunar surface, and they actually provide the nutrients that the astronauts would need. So, there's still more to the story, but it's a great first step. We will one day traverse the stars and one of the key aspects to us being able to do so is being able to survive. >> Mhm. And food is a key aspect of that. An early first step, are you going to be the first to try to test the lunar chickpeas? >> I won't be the first. I'll tell you that. >> You sound like Elon. He's not going to be the first to Mars either.
13:54Now, I'm very excited to transition to one of my favorite parts of the show.
Are You Smarter Than a Scientist?
14:09Ladies and gentlemen, welcome back to another episode of Are You Smarter Than a Scientist? And the quizzical look on Krishna's face is how he's going to attack this question on this week's rendition. Name the 10 deadliest animals to humans. As you know, Are You Smarter Than a Scientist? We have a question. We have 10 answers. We have three strikes. You at home, you might have some ideas in your head. Our resident PhD has some ideas in his head and we are going to see how many of the 10 deadliest animals to humans Interesting. that Krishna can name in this round. The floor is yours, good sir. Man, I don't think I'm going
14:51to do well on this, but let's give it a try. Um, you know, the first thing I can think of is mosquitoes because of malaria. It is a very good guess. Okay. And mosquitoes is number one. Okay, 750,000 per year. Wow, that's a lot. It's It's not a small amount and it's incredible that such a small thing can kill so many of us. >> Mhm. Yeah okay. Um, let's do Okay, in that vein, let's do like insects that carry disease. So, like what about like fleas? Fleas. >> Or ticks. Can you give me that? >> Fleas or ticks. Impacts dogs a lot, but it is not
15:33>> It's not for us. Okay. It is not on our list. >> on a strike. All right. This was a tough one. I know it's a good This is outside of your purview, so Definitely. Um I hear about bears a lot. I know I'm not going to say bears. Nobody interacts with bears. Um sharks are probably also overblown overblown. Um I will note that some of them are classic. Okay, they are Let's go with bears. Well, that's not what I expected you to say. Unfortunately, Oh no, it's not even Oh my god, I'm going to be so bad at this, guys. You're on strike two. I will note that Chris is a biophysicist, so this is
16:14Yeah, this is zoology and like society. Oh my gosh, I'm doing so bad. I'm already on two strikes. Some of them are classic. Maybe maybe I should not maybe I should not reference that because I don't want to throw you off. >> Okay. Okay, can you give me a hint cuz I'm only on one left? >> so so many of us may be familiar with a gentleman who rest in peace was really impactful for us when we used to watch things about animals. >> Stingrays. Oh. Or a manta ray. Not what I was expecting you to say. Oh, I thought you said Steve Irwin. I was talking about Steve Irwin. Was it not a stingray? But it was not a stingray. Oh, it's a crocodile. All right. Okay, just
16:54go All right, now let me just see how many I can get. Come on. I I got one, bro. So, a crocodile is number nine on the list. We will have one lifeline again. We're very new to this. >> All right. How about I'll give you one extra strike, which is against the rules, but we will have one mulligan in this exception. So, we have number one mosquitoes, number nine crocodiles. This is This is a tough one. Hippo? Do we have hippo on the board? Number 10, hippo. We have I have one. I have nine and 10. Um >> We have a lifeline. Damn. Um Dude, I'm like like I guess I'm so
17:36sequestered in like you know, normal society. I have no idea. Sharks. Let's go with sharks. Sharks. Is that on the list? I don't have a four strikes, but I do have the sound effect and that is That's not correct. That is not correct. Unfortunately, we have mosquitoes at one, crocodiles at nine, and hippos at 10. If you're at home, make your list now for what you think two through eight is. I purposely threw your cool curveball. I gave you two easy ones Yeah. the first two episodes. I had to had to curve. Number two, you could argue this was not going to be easy to get, but the answer is humans.
18:17>> Oh. All right. That's fair. to humans. That's fair. We know that very well here in the United States. Number three, was snakes. >> Oh, why didn't I guess? Yeah, duh. Okay. >> Very poisonous animals. If you're a black mamba, RIP Kobe, or others. Number four, it might not have been your corgi, Really? >> but some dogs are our fourth. My fear of dogs as a child is now reignited all over. >> on here? So, unfortunately, cats are busy taking over the world intellectually. >> they're not killing people. >> killing people. They're smarter than that. Number five, there was no way you were going to get this one.
18:57Freshwater snails, which was news to me. Freshwater snails. Wow. Okay. >> So, this is our number five. Number six in our order, assassin bugs. >> I've never heard of that. >> So, I just had to >> Assassin bugs. I got to look this up later. So, we may do now an episode on Assassin bugs. Number seven, the tsetse fly. Oh, I've heard of that. >> In the continent of Africa and it's interesting some of my dad's research has been around this this area and about the diseases. A big one. Another funny reference to a family story which we'll talk about in a future episode about how someone ended up in the hospital for 21 days is scorpions. So, our top 10 deadliest animals to
19:40humans, mosquitoes, humans unironically, snakes, dogs, freshwater snails at five. I think I said something else earlier by accident. Six, Assassin bugs, tsetse flies, scorpions, crocodiles, and hippos.
AI finds hidden anomalies in the Hubble archive
19:57This was This was a bad one, guys. >> This looked like Ferrari at F1 two weeks ago. Not not a good start to the season. >> looked like Aston Martin. What's the other one? Haas? Is Haas doing anything? >> Haas is doing okay. They They've got a Ferrari engine. They're doing okay. Yeah, they're doing okay. >> Okay, so it is simply it is simply the Ferrari. This is something again we're trying to see if you all enjoy. Let us know in the comments how many you got? Are you smarter than scientists? Probably on this one. And we'll bring you back we'll bring it back for next week's rundown. If you want it more, you got to let us know you want it more. But in the meantime, before our next episode game
20:37show, we are going to go to our third story which is about hidden cosmic anomalies in Hubble's archive discovered by AI. Researchers at the European Space Agency, ESA, published in Astronomy and Astrophysics a new AI system called Anomaly Match. Very on the nose. That scanned approximately 99.6 million images cutouts from the entire Legacy Hubble archive in two to three days, which is an unbelievably short period of time. And what did we find? Yeah. So, for background, machine learning and AI
21:19systems are very good at something called anomaly detection, right? Which is something that is out of the ordinary. Just because of the way that they learn data and they learn the data space, there's ways that they can group similar items together in their latent space and they can figure out outliers. It's kind of a I mean, if you think about like rudimentary clustering algorithms where, you know, you project your data into some kind of subspace and then in this case, let's say, "Oh, normal spiral galaxies are over here. Normal barred galaxies are over here." There's going to be little tiny sectors where you find extremely rare objects. And machine learning algorithms can do this
21:59very, very efficiently. Now, what these scientists did from the ESA was apply that method to the Hubble legacy archive, which is over the past 35 years, the Hubble Space Telescope has just been taking image after image, right? And one of the great things about the Hubble Space Telescope is all of their images are now public access. Okay? Um if you're, you know, taking something today, then perhaps it's not public access. You've got like 6 months or something to like grind out as many papers as you can, but pretty soon it's going to go into the public archive. Mhm. So, all of these images were cut out into 100 million
22:40different little image cutouts that are measuring just a few dozen pixels on a side.
New gravitational lenses, mergers, and ring galaxies
22:48And from those hundreds of millions of from those 100 million image cutouts, they identified 1,300 objects that have an odd appearance, right? And more than 800 of these objects have never been identified in scientific literature before. Mhm. Most of these anomalies are just like galaxies going through mergers or interactions, and so they're going to look weird. >> Yes. But every once in a while, there was some pretty cool stuff. So, if we go to our next photo, you'll actually see some of the very cool stuff. Yes. On the upper right-hand side, you're you're seeing galaxy mergers. Mhm. But the lower two on the right, you can see one galaxy that's kind of curving around another. Yes. >> That's a weird gravitational lens. Yeah.
23:30>> Okay? Where because of Einstein's relativity, the gravity from the foreground galaxy is bending the light from a galaxy that's behind it. And so, these are very, very cool gravitational lenses of a background galaxy that's sort of twisting its light around the foreground, which is in the front. >> Yes. >> We've also got really weird wing ring-shaped galaxies, like the one on the upper right. And these are all like completely new. I think that's so cool. >> And you're right, with the ring-shaped galaxy on the upper left. >> Yeah, the upper left. Yes, you're right. >> Yeah. Yep, yep. And I I just think that's so cool that like a machine learning algorithm can go
24:11through these within 2 and 1/2 days and figure out all these new galaxies that now we can maybe get our other telescopes to look at, right? Mhm. Take a look, get some spectra, figure out if maybe there's a supernova that's happening in one of these like lensed galaxies that we can spot at multiple different times because maybe the light is taking longer on one end than the other end. If it's multiply lensed, you can do all sorts of very, very cool science by looking at these new objects, right? It's again one of these examples of a new story about AI helping out scientists >> Yes. that again makes me very hopeful in
24:52all of the drab that we're getting about how AI is is to end the world. I mean, I think we are very much in danger of that as well. Don't get me wrong, but there's also hope. And I think if it's in the right hands, tools like artificial intelligence and the anomaly detection that comes with it can be very fruitful for the pursuit of fundamental science. That is always the question is who controls the button. But the anomaly match, I'm sure I mean part of the Vera C. Rubin already has this built into its existing architecture. >> And that's going to generate like unprecedented volumes of data. So, an anomaly detector is going to be very crucial for analyzing that data just to begin with.
25:32And look at the fact that we're still discovering new stuff today. Yeah. For so for this archive that's, you know, over, you know, had has been gathering for over 30 years. >> Yeah. And the Hubble only looked at a small patch of the sky, right? In in all of its 35 years of history, it didn't like tile the entire night sky like the Vera Rubin will. So, it's very, very exciting time in astronomy. And and that means there's a chance we'll see the Yeah. One day. One day. We haven't looked This is the analogy I always bring up is we're looking out our front window at a house and we're saying there's no one in the street, but we haven't looked out the backyard, we haven't hopped over the fence, we haven't driven around the
26:12neighborhood, but we're just looking out the front window like, "Oh, we're all alone here." And it might just be it might be the
The path to room-temperature superconductivity
26:19might be some roadblocks, right? Maybe they're doing construction on the interstellar highway. I kid. >> Maybe. Maybe. Our last story, one of my favorite almost things that happened that did not happen yes is about room temperature superconductivity. And this is out of the proceedings of the National Academies of Science uh from a combination of universities including MIT, Harvard, Columbia University of Houston, Carnegie Institution, Carnegie Institution, uh Graz University of Technology and Intellectual Ventures. And this was a programmatic paper that lays out a roadmap for achieving one of the pinnacles of I guess would
27:01you say engineering and science intersection of the two, which is the idea of this creating a room temperature superconductor. That's right. This is not a This is not a proper science article that we usually cover. This is in fact a perspective article. So a lot of times scientists will get together and they will write effectively an opinion piece about where the field should be looking at and how the field should be structured for future advancement. And this is one of those, okay? It's in the proceedings of the National Academy of Sciences. It's a strategy paper that assesses the current state of research for room temperature superconductors and then sets out future directions. So
27:42superconductors are these materials that have zero electrical resistance. Not negligible, not next to zero, but because of fundamental quantum mechanics it is literally zero. The resistance of these electrons moving through this material is literally zero because of some very fundamental, very cool quantum mechanics that is going on. Now that could transform our society. More than I think any other technology that I can really think of. A very base example would be if we could have room temperature superconductors or high temperature superconductors we can transfer electricity and power with
28:23almost no dissipation. >> Mhm. Right? Um the problem with modern day superconductors is they either require extremely low temperatures. So even colder than liquid nitrogen sometimes. Or extremely high pressures. If you want to get to high temperature like room temperature, you got to like stick it inside a diamond anvil cell where like you're squishing stuff inside of a diamond and then finally you like make um something that is superconducting, right? If we want industrial scale applications, we need something to be superconducting like on the table. >> Yeah, right. You know? Right. And so there's a prediction challenge, which comes from our ability to predict new
29:04superconductors. Now, that has advanced dramatically because we figured out a lot of the material science and the fundamentals of how to, you know, simulate these things in a computer. Now, what this paper is proposing is a shifting of focus towards like thermodynamics and synthesis modeling. Okay. Because a lot of times when we try to predict new superconductors in our computer programs, those can't be synthesized Uh through the normal processes. It's like you've given me like the recipe, but I have no way of cooking this thing. You've shown me that unobtainium is a thing, but I don't have the root ingredients to create unobtainium. Exa- It's like It's like what are we doing, right? And then there's an engineering
29:46challenge because we've got all these different knobs that we can turn in our lab, things like pressure, things like the nanostructure of light. Let me just say that again. So, there's also an engineering challenge, right? Because we have these various knobs that we can turn in our lab, things like pressure, things like the nanostructure of the material, light, lasers, just like pile a bunch of lasers on it, right? To control that superconductivity, but our ability to predict how each of these knobs affects that material is pretty limited,
Why physics does not rule it out
30:18right? >> So, what this perspective paper is doing is saying, you know, there's actually no physical law theoretically that is preventing room temperature superconductivity. No one's come out with a like this is impossible paper, right? So, it's definitely there. And supercon- conductivity superconductivity has been observed in so many different materials in so many different conditions, and it's almost like a generic property of materials at some point. If you if you lower the temperature down, if you increase the pressure enough, things are going to become superconducting. So, the idea is we want to be able to now gear our research towards creating something
30:58as a community. Yeah. Right? Rather than just going off in all these different tangents, trying to do our own thing, let's like have like a sort of human genome project style moment. >> Yeah, okay. >> Right? Where all of these different researchers from around the world sort of get together, we plan out how are we going to get there. Yes. Right? And the first task is always to improve computer-aided models. So, not just like predict random stuff that we can't cook, but maybe things that we can. Things where the recipe actually makes sense. We've got the tools to do it, and it's there's a light at the end of the tunnel. In in software, there is this phrase or this rallying cry of it's time to build.
31:40Yeah. It sounds like in the super conduct conductor community, the rally cry is it's time to cook. Exactly. Yeah. It's time to cook. >> Exactly. And and and the other thing that they really highlight in the strategy paper is that AI is here. Yeah. And we need to now start leveraging that in the way that AlphaFold kind of leveraged AI to solve protein folding, which for the longest time it was like, oh, this is an impossible problem, right? There's two to the 300 different configurations. There's more atoms in the universe than they are There's more atoms in the universe than there are structures that a protein can take, and so it's an impossible problem. Well, AlphaFold is pretty good at like 90% of
32:22proteins now, right? So, we need to start leveraging these technologies to our advantage. >> Right. Right. And this dovetails with I mean, it's we don't look to always cover AI in our stories on the pod. >> No. It is just a factual reality Yeah. that so many labs and researchers, especially things that are breaking through, happen to have a companion AI component. >> Mhm. And it's just kind of the way that it is. >> Yeah, yeah. Um especially for use cases where it's like protein folding or the where you just want something that can go through a like almost a like there's a brute force >> Mhm. kind of pathway where it's just
33:04like throw compute at it, you'll be able to get down to a more narrow band of options >> Mhm. than we otherwise would be able to without being able to just throw compute with you at the problem set. >> Yeah. Um and that's kind of like a very level one implementation, and there's also level two, three, four, and five. >> But superconductors are going to totally change the face of humanity on this planet if we can get to a way to build them in a way that's uh scalable uh in terms of from a from a manufacturing >> capacity perspective. >> We had we had this whole hype cycle with LK-99 where everyone was doing the think pieces of what is this going to mean for everything? >> That one, can I just say I I looked at
33:44that archive paper and I was like there's no way. Like we can we we should do like a joke episode on it sometime of just like how to recognize nonsense. How to sniff the BS. Uh a bunch of four again really fun papers today. You can kind of see how the difference between our deep dive episodes where we really break down the fundamentals, so it's not just sometimes in the rundowns you can feel like, well, this is just what they're saying. This is why we have the deep dives to make sure we can understand the real fundamentals that build up the knowledge base to be able to have confidence in making these conclusions from these studies. So we touched on the 3D
34:25scanning for ants, incredible use of a particle accelerator for 3D model generation. I mean, I might want to use that for my 3D gaming stuff. How how how how unnecessary it is to use a particle accelerator to do like 3D video game Yeah, we have a mini particle accelerator in the back. It's helping us model this. We follow that up with growing chickpeas on the moon. If you could go to the moon Mhm. and know you're coming back and it's fine and it's safe for you to go. >> like as safe as um air travel. As safe as air travel? And you don't have to pay. Yeah, I'd probably do it. >> Yeah, if it's as safe as air travel, yes, I think I would do it. I would I would go. I'll be honest. Dude, the Earth is going to be the size of the moon. I'm so excited. You know, imagine
35:06looking at the Earth and it's just like, oh, I can like cover it up with my thumb. Hey Jeff, if you want to do another launch, but instead of another identity-based cohort, you want to do people of color where we are very much >> I'll I'll be your token, you know, whatever for the marketing, we'll go. But like there needs to be like 100 launches before because I need I need to make sure We'll start with orbit. We'll just We'll just do a little little small orbit. We're We're being a little facetious. although he is a Princetonian, so that's part of the connection. We hit the cosmic anomalies. I love these uh telescopes, both ground-based and space-based, and the whole ecosystem around them. It's always fascinating. The data continues to give us value and
35:46room temperature superconductivity. Which I I was going to ask you a question about Can you explain resistance? But that's that's for a deep dive episode. So, if you want to know more about superconductors, let us know in the comments cuz I want to know more. Yeah. I'm sure we can do a deep dive on the history of superconductivity. It's a fascinating tale. Uh BCS theory is what it's called from the University of Illinois Urbana-Champaign. Very proud of their work there. Um they have a little plaque in the physics department. Like this is where BCS theory was. I thought you were talking about college football for a second, but you were not talking about the old BCS bowl or whatever it is. I clearly don't watch college football. >> No, I am your host
36:26Lester and I joined as by my co-host and our resident PhD Krishna Chaudhary. As you can tell we are having a fun time on this pod. We really appreciate you. We will see you all next week.
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