Science Friday - Artemis Update, Stellar Art, AI for Mammography, Smoky Grapes, Harvesting Water From Air. Sept 16, 2022, Part 2

Episode Date: September 16, 2022

Pulling Water From Thin Air? It’s Materials Science, Not Magic. You’ve probably seen a magic trick in which a performer makes a playing card, coin, or even a rabbit appear out of thin air. Writing in the journal Nature Communications, researchers at UT Austin describe an experiment where they seem to pull water out of dry air—but it’s not magic, and it’s not a trick. Carefully applied materials science and engineering allows the team to extract as much as six liters of water per day from one kilogram of their polymer, even in areas with 15% humidity. That’s drier than the Sahara Desert. The material itself contains two main ingredients. First, a konjac gum, which can be found in Asian cooking, rapidly absorbs water from the air. (In scientific terms, it’s a “hygroscopic material.”) The second ingredient, hydroxypropyl cellulose, responds dramatically to changes in temperature. So at lower temperatures, the team’s polymer film absorbs water, but can rapidly release that water when the film is heated by the sun or artificial heating. Dr. Guihua Yu, a professor of materials science and mechanical engineering at UT Austin and one of the authors of the report, joins Ira to talk about the material, its applications, and what challenges remain before it can be put into widespread use. An AI Partnership May Improve Breast Cancer Screenings Reading a mammogram is a specialized skill, and one that takes a lot of training. Even expertly-trained radiologists may miss up to 20% of breast cancers present in mammograms, especially if a patient is younger or has larger, denser breasts. Researchers have been working since the advent of artificial intelligence to find ways to assist radiologists in making more accurate diagnoses. This July, a German research team, publishing in The Lancet Digital Health, found that when AI is used to help sort mammograms into low, uncertain, and high risk categories, a partnership between the radiologist and the algorithm leads to more accurate results. To explain how this result may be translated into real clinical settings, Ira talks to Harvard’s Constance Lehman, a longtime researcher in the field of breast imaging. She talks about the promise of AI in breast cancer screening, its limitations, and the work ahead to ensure it actually serves patients. A Smoky Aftertaste: Keeping Wildfires Out Of Your Wine Glass Readers who love wine: It’s time to have a serious talk. California, Washington and Oregon are three of our largest wine-producing states. They’re also some of the states most prone to wildfires. The West Coast is in the midst of its wildfire season, which makes us wonder: How does smoke impact the wines that come from this region? And what could this mean for those who enjoy a Napa Valley merlot, or an Oregon pinot noir? There’s an area of food science research dedicated to answering these questions. Factors like the length of smoke exposure, the chemical composition of that smoke, and the type of wine being created all factor into how the final wine product tastes. The best side of a smoked wine spectrum is a mild campfire flavor. The bad side is burning tires. Joining Ira to talk about how scientists are working to better understand how wildfire smoke impacts wine is Dr. Cole Cerrato, assistant professor of food science at Oregon State University in Corvallis, Oregon. Artemis Update: What Will It Take To Make It Back To The Moon? Sixty years ago this week, President John F. Kennedy gave an historic address at Rice University, in which he laid down a challenge to the nation and the world. “But why, some say, the moon? Why choose this as our goal? And they may well ask why climb the highest mountain? Why, 35 years ago, fly the Atlantic? Why does Rice play Texas? We choose to go to the moon. We choose to go to the moon in this decade and do the other things, not because they are easy, but because they are hard, because that goal will serve to organize and measure the best of our energies and skills, because that challenge is one that we are willing to accept, one we are unwilling to postpone, and one which we intend to win, and the others, too.” Six decades later, going to space is still hard. This week, a flight of Blue Origin’s ‘New Shepard’ rocket experienced ‘an anomaly’ during a launch, triggering the escape system for the capsule (which, thankfully, was uncrewed.) And the Artemis 1 mission, the first test flight of America’s planned return to the moon, is on hold while a leaking fuel line is addressed. Dr. John Blevins, the chief engineer for the Space Launch System, the massive rocket powering the Artemis 1 flight, joins Ira to provide an update on the mission, and why, after 60 years, the trip to the moon still contains so many challenges to be overcome.   This Astrophysicist Holds Star Data In The Palm Of Her Hand When you look into the sky, the space between stars looks empty and void—but it isn’t. That’s where stars are born. And since astronomers and astrophysicists can’t reach these stellar nurseries, they rely on data collected by telescopes to peer into space. But what if you could hold part of the galaxy in their hands? Or peer into an orb and see the birthplace of stars? By combining astrophysics and art, that’s exactly what Dr. Nia Imara does. She’s a visual artist and assistant professor of astronomy at UC Santa Cruz, based in Santa Cruz, California. Imara talks with Ira about studying stellar nurseries, how she creates stellar nursery spheres, and what she can learn from holding them in her hand. Transcripts for each segment will be available the week after the show airs on sciencefriday.com. Subscribe to this podcast. Plus, to stay updated on all things science, sign up for Science Friday's newsletters.

This is Science Friday. I'm I Refleto. You know the old magic trick of pulling a playing card out of thin air, but what if you could do that with water? Pull it out of thin air efficiently and even from dry desert air. Given the critical water shortages we're facing and threatening to get worse in our climate crisis, that would be some trick, wouldn't it? Well, a group of engineers at the University of Texas at Austin claims to be able to do that. joining me now is Dr. Gweha Yu, Professor of Materials Science and Mechanical and Engineering at UT Austin. He works with the Texas Materials Institute and the UT Energy Institute, and his group has developed a material that can literally pull water out of air, and as I say, even from desert air.

And they describe some of its performance in research published in the journal Nature Communications. Welcome to Science Friday, Dr. Yu. Thank you so much for having me, Aaron. What's that old phrase? Any significantly advanced technology is equivalent to magic? I mean, is this magic? Tell us about this material. Oh, sure.

So we actually have been working on designing these soft materials. So we call it hydrogill. So hydrogel means by a scientific term, it's kind of a polymer that is highly cross-linked. So this actually magic material have two chemical ingredients. One of them is doing the function of water harvesting in terms of the hygroscopic property. Hygoscopic means you can absorb water vapor. So we have this one-polymer conject gun. So you can actually find them actually very commonly in kitchens, especially in Asia.

So this country gun actually can be very efficient in terms of absorbing the water vapor and store in their network. So another ingredient that we design doing also the other function is for water release. So you can imagine, right? So in our day life, the desiccans can do the job of dehumidify our ambient air. But really, after water absorption, so it's very hard for them to release the water back to be useful. Right. So, yeah, so that typically we need to pay large energy penalty, meaning that you need to heat up the desicants to release the water. going through this evaporation, condensation.

So that's actually, you need to have external electricity to do that. So our magic materials that has the second ingredient, we call it like hydroxy proxy or cellulers. So that HPC is actually very unique in terms of they are responsible to the thermal heat, meaning that if you have the mild temperature change, for example, if you have 80 and night, and then actually when sun comes in to heat up your gel material, to about 95 Fahrenheit. So that actually temperature change will effectively release the water that you originally stored in the gel.

So by this effective absorption and also effective water release, so we actually found this self-standing gel, they are able to collect the water on their own without any external kind of electricity needed. So you have this gel that is made out of stuff that's readily available. You can buy it in the market. and it absorbs water on its own sitting there, and then if you leave it out in the sun getting warm enough, it can heat it up enough, and the water comes pouring out.

Would that be correct? Yes, yes, exactly. Of course, that's actually, it's every day you can have only one cycle, right? So we call it passive water harvesting. But you can also do active water harvesting. So you can actually do the multi-cycles every day. For example, these materials we design, if you kind of heat it up by some electricity,

that's actually, you can actually even run about 15 to like 20 cycles per day. So that, in fact, we also can increase the water yield per day. So that we calculate that at a different relative humidity. So for example, in a desert area, that relative humidity is about 15%. So we can actually release about 6 liter of water per kilogram of our materials. So to be kind of very effective to be used for really critical, like, of water needs. So our project is funded by Department of Defense. Really, the goal is for a soldier to use in extreme kind of conditions. But of course, given this very simple way that we make the

materials, and it's also this very cost-effective materials, and it's the renewable sellers. So we believe that it actually can benefit many societies in the different areas in the world. So you can get six liters of water from one kilogram of your stuff in a desert condition. Yes. That's amazing. You must be surprised yourself how well it works. Oh, yes. Originally, we thought that if we have these kind of materials, maybe we can have the equal weight of the water that you can absorb. But really, by designing better, how fast they can release water. So this is actually, you have these perfect engineering students. They can design

these material to work to their best. So we found that the optimum condition is these actually gel can be cycle multiple times a day. So that's really kind of boost the water yield per day. So you imagine then first the military and then maybe all of us buying a device that would contain this material on the store shelf somewhere? Yes, we think that's definitely possible because as I mentioned, these materials actually can be made very easily. And once you have the kind of these material precursor to make these materials, so simply by mixing them together, So let them react for about a few minutes. So they will be able to form these gel materials.

And they actually will be able to start to collect the water. Of course, if we design a pro-type device, with these layer of materials, we call it absorbent bats. So that will have the optimum kind of design in terms of that potability and also kind of the high yield. So that actually can be for a disaster relief use. But I imagine that in really kind of in our garage. So people buying these solutions that you can make these materials and then actually

engineer them together. Maybe it's a fun project over the weekends and with kids to make it. I'm sure, though, there must be some patentable, a proprietary method you're using, no, or is it not? Oh, yes. This is actually, we have the patent in terms of how you can actually use these materials, like that material is actually patented. But certainly, like some of these, like, ingredients in terms of that you can make. It's really kind of easy that actually can be made by customers. Does it have a shelf life? I mean, can you, does it get used up at all? Or is it sort of like, I'm taking like a catalyst that it doesn't? Or does it, if you use it too many times, well, we have to go out and buy some more? Oh, that's great questions. So we actually

tested in the lab conditions over several weeks, up to about a month. So these gels, films that we made and then doing this cycle, about 15 to 20 cycles per day. So after so many kind of days, several weeks, so they still perform very similarly as their fresh states. So we believe these gels, because it's actually, we made it, is with these spongy structures. So you can imagine, like our kitchen, like sponge, right? So they are not only just lasting for a few days,

but rather at least quite a few weeks, even months. So these actually gels is mechanically also relatively strong. So they are able to hold their strengths for certain period time. So if for a longer testings, for a few testing, so we will see how long they can last. But I believe this actually can be like with a sufficient kind of a shelf life. Wow. Now, I know you're an engineer. And I know as an engineer, you know you don't get something for nothing, right?

Yes. So there's got to be some downside to this or some weakness. What is that? Yes. Yeah. That's another great question. So talking about potential challenging, one of the key is how you can expose these gel film with a very high surface area to interact with water vapor.

So one of the process we actually made them to host, right, to keep their hierarchical structure, is by freeze drying. So free drying process is actually once the gel form, so you want to get rid of their original solvents. that can be water, can be other organic solvents, but you want to maintain their hierarchical structure. So this structural step by freeze drying is actually kind of more of the limiting factors in terms of scaling up. So if you just simply by drying them with the hot plates or with other means,

so sometimes the structure they make collapse. So the freeze drying step probably will be a determination kind of step, how scalable the process is. So we are actually trying to see whether there's other kind of process that can be used to maintain their microstructures of these gels to have the highest possible kind of efficiency. Are there other applications beyond drinking water? Because you're obviously making fresh water.

Yes. You could grow plants with it, right? Yes, exactly. So that was actually our earlier idea. We actually in 2019, we published the first work on this smack gel. We call it super absorbent. moisture gels. So that was our first generation of this smack gel that can harvest the water from the ambient area. But we also actually, about two years ago, after our first work, we also turned that

smack gel into so-called self-watering soil. So simply put is, you can turn whatever soil, even dry sands, to be able to self-water. So this actually concept is actually a demonstration that can potentially useful for sustainable agriculture. So this self-watering soil by incorporation chemically modified with our smack gel, it is for the harvesting gel, they are able to irrigate themselves and without any additional water. So really, that's our kind of a demo that these gel films, not only just for harvesting fresh water, but they can also be beneficial for agriculture. Okay, so what are we going to see this? Self-watering soil is just, my mind blowing here. When are we going to see this type of material on the market or available?

Oh, yes, you're right. So we actually are working with some of the industry partners and for like more of the few tests because in university lab, right, everything that is actually is in a lab scale. So usually we work with limited amount of materials and we test it in more ideal lab kind of conditions. But when you're actually going out for like a few tests, And it's kind of really open to different areas. So that's actually how we're actually designing kind of the additional experiments to work for a few tests. But we really hope it's in the next few years. Once we have more of these few tests, so we will have the idea what challenges remain for pushing them to be useful

and actually the customer can buy in a warehouse or actually kind of also for farmers they can use on their own. This is incredible. Thank you, Dr. You for taking time to talk with us and keep us in your loop about what's happening, okay? Sure, yeah. Thank you for having me and look forward to more interaction and hopefully society will see some of these products in the new future. Yeah, it looks like you've invented something really cool and useful.

Dr. Gweha, you, a professor of material science and mechanical engineering at the University of Texas in Austin. Thank you, Ira. After the break, can artificial intelligence help radiologists more easily find signs of breast cancer. We'll talk about it. Stay with us. This is Science Friday. I'm Ira Plato. Accurately reading a mammogram is one of the more difficult tasks in radiology, and even a good radiologist can risk missing a patient's cancer. In fact, up 20% of exams might turn up false negatives depending on your age. And as long as we've had artificial

intelligence, researchers have been trying to bring it into health care, including identifying lesions and mammograms. A study published in the Lancet Digital Health in July tried another approach. What happens when a highly trained algorithm works with radiologists to identify which patient's mammograms need a closer look? The team approach resulted in a 2.6% improvement over both radiologists, working alone and the AI working alone. Here to talk more about the possibilities and limitations is Dr. Connie Lehman. She's a professor of radiology at Harvard Med School, a breast imaging specialist at Mass General Brigham and a researcher who has been working on the integration between AI and mammography for many years. She was not involved in this new research. Welcome to

the program, Constance. Thanks for having me. Delighted to be here. I'm so eager to talk about this because it affects so many women, doesn't it? You know, it really does. Well, it's imperfect. Mammography is the best method we have to detect breast cancer early when it can be cured. So we want to address the challenges and the problems with mammography, and AI holds great promise in that domain. So we are very fortunate in breast imaging to have decades of research, believe it or not, in AI. People think it's this very new thing, but computed-assisted detection and diagnosis

tools were developed decades ago, and we had a lot of research in the 1990s and then in early 2000 to demonstrate what we identified and what we found when we had computers helping humans read mammograms better. So we learned a lot. Now we have advanced tools in artificial intelligence, and in particular, much faster computers, or we can do deep learning and neural networks, which really amplifies the potential impact of AI tools. So a lot of the past work was having a computer flag areas on a mammogram that a radiologist should pay extra attention to. So it was really focused on lesions on the woman's mammogram. And what we found out was there was human variation in interpreting mammograms when you didn't have a computer helping you.

And there was human variation in how radiologists interpreted mammograms when they, did have a computer helping them. So it didn't just solve the problem of a lesion that one radiologist might have missed, but the computer flagged it so they diagnosed the cancer. It was more complex than that. So what did you see in this study that might change the conversation? So this study said, let's look at it a little bit differently. Rather than mark specific areas on the mammogram, let's instead sort the mammograms using the computer. Let's sort the mammograms that need more attention and those mammograms that are highly likely to be negative, to not have a cancer. So this is a domain that a lot of us are working on called triage. So you're not going to mark the

mammogram. You're going to triage the case saying this needs some extra attention by the radiologist. We're worried that there's a cancer on this mammogram. And other mammograms are like, this looks totally clean. We think the likelihood there's a cancer on this mammogram is next to zero. So in this study, what they wanted to do was to say, well, how do we know that, you know, radiologists vary and how they listen to the computer that's marking different lesions or different areas on the mammograms. How did the radiologists respond to these cues from the computer? This is such an exciting domain because it's a different paradigm for how to use computers to help us do better at finding cancers on a mammogram. So what did this group do?

they decided to compare a single radiologist reading to a simulated situation where the radiologist would benefit from the AI score on the mammogram. So the first thing we need to know is the study design. This is a retrospective study. So we're going back in time. We're pulling mammograms. We know how the radiologist interpreted the mammogram back in the past. We get AI scores. from those mammograms and we simulate a world where the radiologist would have used that AI score and adjusted their interpretation from that old recorded interpretation we had from the past. So it's retrospective in a simulation. Would this generalize to other populations, for example, outside of Germany because this was all conducted at screening centers in Germany? And really

importantly, will this translate over into clinical practice? So while it's encouraging early results. The authors were also very careful to say these are the limitations of this level of study that we performed. And I think it's important for people to hear that because we're all so excited about AI and we can get ahead of ourselves a little bit on what we actually know and what's promising. So it's promising, but not ready for prime time yet. Is that what you're saying? A hundred percent. You know, many, many investigators are giving us fantastic reviews saying, this is promising, this is exciting, but let's not get ahead of ourselves because we learned from our past. I published a paper in JAMA in the early 2000s of CAD that was being used out in

community practice. And what we found was the simulated reader studies didn't translate over to actual real-world mammography interpretation. And that was really disappointing because the hope was, of course, that women were getting their mammograms interpreted at a higher level when they had CAD applied to their mammogram, and we found that wasn't the case. We don't want to repeat that. So these research publications are so important. They go through extensive peer review. Again, the authors are to be commended for saying, this is what we found. Here's the limitations. These are the next steps that are needed. Well, tell me what kind of research you think it will take to actually improve care with these algorithms. Here's the most important part of this paper.

It's a simulation. It was assumed that that first radiologist, if told by the algorithm, you don't need to worry about calling this patient back, would actually change their mind and not call the patient back. We don't know that that's true at all, or even if that would be the right thing necessarily. It also assumed that if the AI algorithm said, this mammogram is really suspicious, you need to bring this woman back in, that the radiologist would agree. So the assumption that the radiologist would agree to the two extremes and not be influenced at all with the middle range scores of the AI algorithm, that's just a huge assumption. And I don't think it's a reasonable assumption.

We've never seen consistency in humans integrating feedback into their clinical care pathway decision making. And just to think that if it was highly likely negative, the radiologist accepts it, even if they see something suspicious on the mammogram, it's highly like positive, they bring the patient in, even if they don't see a lesion on the mammogram to evaluate. And it absolutely requires that we have that prospective study to say, well, what about that fascinating domain of a human accepting or rejecting feedback from the computer? So what would you say is the takeaway message from this study? The takeaway message is using and leveraging the power of AI to triage mammograms that need more attention from those that need less attention, it's here. This is going to be part of our future in screening mammography,

and I couldn't be more enthusiastic about this roadmap, this pathway that these authors have continued to contribute to with their publication. However, we're on the road. We're not at our destination. We've got a lot of work to do collaboratively to get to that final destination of showing the actual impact on patient outcomes when we leverage and use these tools in true clinical practice. And how soon do you think we can look forward to fewer missed cancers by, you know, A.I.N doctors working together. I think it can be five years if we work together. Research and the science has been very exciting. I've seen my colleagues all around the globe, despite the challenges of the pandemic, continue to push this research forward to work hard. This is what we need more of.

And I think we can get there in a short period of time if we do this right. Well, Dr. Lehman, thank you for your work. We're looking forward to this also. Thank you for taking time to discuss it with us. Thank you so much for having me. It was a pleasure. Dr. Connie Lehman, Professor of Radiology at Harvard Medical School and breast imaging specialist at Mass General Brigham in Boston. This is Science Friday from WNYC Studios. If you're into wines and so many of us are, then we need to have a serious talk because California, Washington, Washington, and Oregon are three of our biggest wine-producing states, and they're also some of the states most prone to wildfires. Yes, the West Coast is in wildfire season, which makes

us wonder how does smoke impact the wines that come from this region? And what could this mean? For those of us who enjoy a Napa Valley Merlot or an Oregon Pinot Noir or a Washington State white, There's a whole area of food science research that is looking into this important question. And joining me now to tell us a little bit about it is my guest, Colerato, assistant professor of food science at Oregon State University in Corvallis. Welcome to Science Friday. Hi, Ira. Thank you for having me.

You're welcome. Okay, let's get right into it. If a wildfire is burning near a vineyard, is that smoke going to impact those grapes and the wine? potentially. Like anything, it will depend on how big the fire is, how much smoke is getting put into the air, how close it is. There's a lot of research that's looking into that, but the overall effect that you would see in the subsequent wine that is made is the wine will take up these chemicals from the wildfire that we tend to associate with that smell. And the grapes will pull in some of those. chemicals and during the fermentation process, either the grape or the fermentation is changing some of this chemistry. And so the wine that you would eventually drink from this can sometimes have an ashy flavor to it. Sometimes it is a campfire type of flavor, like a day-old campfire. Myself, I'm very sensitive to certain types of chemicals that often put off flavors that resemble

tire fires, if you will. It's not a very pleasant experience. Wow. Wow. Yes, it can be very strong. And I think there's something to be said about people's sensitivity, but it's not like anybody is going to be having any of these wines on the market anyway. No, but could there be a market for it? Could people say, hey, you know, I kind of like this smoky burning fire taste and say, hey, I'll drink that wine. I mean, potentially, I believe it would be probably very clearly labeled if that was the case, they're not very likely to just buy a typical wine off the shelf and say, hey, this tastes smoky. But we have some sensory experiments that we do in our lab. And when we do some of these smoke trials, there have been a

couple people that like some of the smoky wine. So potentially there could be a market. Yeah. You know, because we're a science show and a lot of our listeners like to get really into the weeds about the chemistry. Talk about the specific chemicals that affect those grapes. So what's occurring, coming from the smoke itself, there are a series of compounds called phenols that are in the smoke. And what we think is happening is that these phenols are attaching to the grape skin. There's an interaction between the skin and these volatile compounds. And eventually these compounds are absorbed into the grape itself. Now, I know that Pinot Noir is huge in Oregon, right?

Is this particularly bad for those Oregon vineyards? Pinoir is incredibly sensitive to these wildfires. Our red wines typically tend to be more sensitive because these wildfire molecules go into the grape skin itself and because a lot of the red wines are produced on skin, they are fermented with the skin in contact. They tend to extract a lot of those chemicals out of the skin, whereas white wines, such as chardonnay that we have here,

they're still affected, but they often don't pull out some of that kind of campfire effect that you'll get out of this. So the chemistry changes. It's just in a slightly different way. Yeah. So the Pino people are a lot more worried than the chardonnay people are. Correct. And there's often a big overlap.

What is the industry watching for then as the wildfires get worse in some places? I think the industry, first and foremost, is looking at the same things that everybody else is looking at. Like, is this going to affect them more than just from the wildfire smoke, but directly? The other thing that they're looking for is not necessarily whether or not they can prevent this, because the smoke is already in the air. but what they can do is get more information, and that's when they start sending in samples for testing to see how much some of these compounds,

these volatile compounds, are getting into their grapes. So they have more data to work with to make their decisions. And what are the vineyards then doing now if their grapes are affected by smoke? Do they just throw out the affected grapes? There's a number of things, post-processing things that they can do. They have at their disposal. It really depends on how affected they are.

Again, like how close that wildfire is, how much smoke there was. So depending on the flavor experience that they are getting from their wines, some places are able to successfully blend out the smoke smell or the smoke taste, so they can blend it with other types of wine or unaffected wines from previous years. There are a number of ways that they can do some chemical amelioration as well, where they will use things like activated charcoal, reverse osmosis. And again, these are for the wines that are typically not heavily impacted, but are slightly impacted, so that they are able to reduce the amount of that sensory, smoky experience in their wines.

Well, if you consider that these fires are, you know, this is the new normal now, could an answer to this solution possibly be a more, how shall I say, smoke-resistant grape, and is it possible to develop one? We are looking at a number of ways that kind of address this question. I don't know much on the side of kind of developing a different type of grape coming from the chemistry perspective myself. So my points of attack is always going to be looking at ways that we can either prevent it with some sort of chemical intervention.

Is there a way in the back end that we can prevent this flavor? with another type of intervention that is similar to what they use now, but more specific to these compounds. So in that vein, what's next for your research? What do you want to know? The things that I want to know are what exactly are all of the compounds? Are there certain compounds that are more impactful towards the flavor profile of a smoke-impacted wine? And once we know this information, we can start developing more specific strategies to target these molecules so that we can remove this without affecting the overall quality of the

wine itself. Because we would still like to give the wine industry great quality wine without needing to impact any of the chemistry that they want in their wines. Thank you, Dr. Serato, for taking time to talk with us. Thank you, Ira. Thank you for having me. Cole Serrato, assistant professor of food science at Oregon State University in Corvallis. We have to take a break, and when we come back, 60 years ago, JFK said that we choose to go to the moon because it's hard. Is it still hard? And why?

The chief engineer for the Artemis Rocket joins us right after this break. Stay with us. This is Science Friday. I'm Ira Flato. 60 years ago this week, President John F. Kennedy gave a famous speech at Rice University, a challenge to America and to the world. We choose to go to the moon in this decade and do the other things, not because they are easy, but because they are hard. Just how hard getting to the moon was became very clear in the early failures of American

rocketry in the 1950s when test rockets blew up on launch time after time. Then as we moved into the 1960s, came the fiery death of three astronauts during Apollo 1 ground tests, the near loss of the crew of the Apollo 13 mission. the loss of the crew of the Columbia shuttle spacecraft. Because putting humans in space has become so routine, we at times forget the losses and the sacrifices and have to be reminded just how hard it really is. And earlier this month, we were reminded again

when the launch of the Artemis 1 mission, the first step on our path back to the moon, had to be delayed indefinitely due to a leaking fuel line. So we ask, is space travel still so hard? But here with some of the answers is Dr. John Blevins, chief engineer for the space launch system at NASA's Marshall Space Flight Center in Huntsville. Welcome back to Science Friday. Hey, Ira.

It's good to be back. Let's talk about what we're waiting for with the launch of Artemis. Do we know when it will happen and when the repairs will take place? You know, we have several dates that we've submitted to the Space Force for their review on when we can launch. We've actually already made the repairs that we expect will. fix the leak that we had on the connection between the ground and the flight side. So this was just a minor setback with new equipment that were able to quickly move on from. Does this kind of fuel leak problem imply a problem of some sort with the design or the materials, or is it just one of

those things when you hook up a pipe? Maybe it just doesn't seal right. Yeah, it's a little more of the ladder. I don't want to trivialize just hooking up the pipe in this case because we do have temperatures that are around 40 degrees, rank in above absolute zero. It's a challenging environment in any cryogenics, but certainly hydrogen more than the others, just because it's a very, very small molecule. It's a smallest molecule known. And also because it's the coldest that we get with any propellants. So it's a little more challenging than the other propellants, but we've mastered it before. It is really about the pressures, temperatures, connections, the loads on those connections, they're all different in this rocket.

And we've done a lot of testing before we pulled the rocket out there. And we learned kind of the envelope. And we got some signatures that told us it was time to go back and change that seal. And so we've changed that seal. And I'm pretty confident of the work. The truth will be when we load it up and get ready to fly next time. Yeah. So what are the questions that you have to be able to answer to give a go-no-go answer for, let's say, late September or early October?

Well, what we're going to do, Iris, we're going to go ahead and do a tanking test. to verify its function. You know, you may know that the first launch attempt, we were fully tanked up, and we've done that before through this seal. We had a different seal that leaked previously in a wet dress rehearsal, but this particular seal, which is the main fill and drain seal, had worked just a few days before we tried it on this one. So we think we understand the different potential reasons.

We call that a fault tree, and we've gone and mitigated those things down the fault tree. And so we're going to do a tanking test. I believe it's next Wednesday. should weather and everything else cooperate. And once we get through that, we'll submit all the logic for while we're ready to go back and give a launch attempt. So besides just did it work, what things that you're looking for when it launches? What kind of data do you collect that you can use for the next kind of mission, the next launch?

It's a great question because there's so much to learn on a new rocket. It's going to go through transonic and it's going to vibrate differently than other rockets. it's built somewhat differently. It's new hardware, and we're going to go through maximum dynamic pressure, max heating. We're going to have a different separation scheme. It looks a lot the same to folks that are viewing shuttle and this one, but it's a different rocket and it's different clearances. And so we've got a lot of data for all of those different things to ensure that the next flight,

which will carry astronauts, will be safe for us to move forward with. There are those who say you did this with Apollo. Why is it so hard now? Just pull out the old plans and go, back. What's wrong with that kind of thinking? Well, I'll tell you, the Apollo, first of all, we shouldn't take anything away from Apollo. They really stepped up the Saturn 5 rocket. You know, what they did is they met the industrial base of their day. You know, they were already working on the F1 engines. They were building rockets. They were very similar. And then they

scaled that. And they made a bigger rocket for the Saturn 5. We also similarly started with our industrial base, what we can build and what we should build. And we literally focused. focused on the mission. And that's where we ended up with this architecture, is what does it take to get the mission done? And it wants the high performance that we had achieved through the shuttle program with ours 25 engines. And so while it would be fun to have a Saturn 5 setting there, you know, to go back and build that would actually take longer than what we achieved starting with our industrial base. The space landscape has certainly changed it a lot since the 1960s. You have many more

countries, private industry involvement, like SpaceX, does that affect your decision-making with this rocket at all? You know, it's our job to enable that, quite honestly, if you go back to that speech that we're talking about, what a wonderful speech by our president 60 years ago. You know, he said others will go and we can be a leader or not a leader. And it's NASA's job to really enable that among our country and our country's partners to go and do those things. So it's really exciting, quite honestly, to see that evolution of American companies, both the ones that work for us and work with us on SLS, as well as those companies that are doing things more private enterprise. So really, this is the culmination of what was started back in the 60s. And I would just say it's an exciting time to be a rocket scientist. Is it still hard?

It's still hard. The physics hasn't changed. And so there's still danger. And there's still peril and certain areas waiting for us. And we haven't gone back for 50 years. And we don't want to minimize that. And that's why this first launch, this Artemis 1 launch, is unmanned. And I think sometimes because of our travels in north orbit for 50 years and how much easier

that was, we've, I guess, had a memory loss of what it takes to go into the deeper space, go out past the Van Allen belts and experience that radiation. The physiology's hard. The machinery's hard. The heat transfer when you come back is hard. All those things are still hard. I wouldn't say that it's any easier than Apollo. I would say we've learned a lot, and we're going to apply those lessons.

Most of those lessons are that we're applying, are really for the safety of those that are going to go. Back in the Apollo age, not only was during a Cold War, but we were willing to take greater risks, if you will, with our astronauts. And now what we'd like to do is we'd like to have. have a safer travel. When we send people, we want to be assured that they're going to come back if April. It's a very perilous mission. I feel confident that the Orion capsule on top of the rocket has done a good job designing for those environments. And it's our ride, the rocket,

that will get them on that journey. For I will put, Dr. Blevins, a very, really good summation of what we're expecting. Thank you for taking time to be with us today. I'm glad to be here. Thank you, Ira. Dr. John Blevins, Chief Engineer for the Space Launch System at NASA's Marshal Space Flight Center in Huntsville. Thank you for joining me, and good luck with the upcoming mission. Thank you, R. This is Science Friday from WNYC Studios. Astronomers and astrophysicists have a bit of a tricky job,

since they can't exactly get up close and personal with the stars or deep space they work with. But what if I told you they could virtually hold part of this? galaxy in their hands, or appear into an orb and see the birthplace of stars by combining astrophysics and art? That's exactly what my next guest does. Dr. Nia Imara is a visual artist and assistant professor of astronomy at UC Santa Cruz, based in Santa Cruz, California. Nia, welcome to Science Friday. Thanks so much, Ira. I'm really glad to be here. So to help you answer these big questions about the universe and stars. You create spheres that hold part of the galaxy. Wow, can you describe how they look and what they represent? So I describe these as sort of giant marbles or even sort of like crystal

balls. These spheres are about eight centimeters in diameter, a little smaller than a soft ball, so you can hold them in the palm of your hand. And they represent stellar nurseries. They represent the space between the stars where stars are born. I am a painter in addition to being an astronomer. And years ago, I created this self-portrait where I'm touching the stars. And it was, you know, years later where I suddenly had the idea, why not actually try to touch the stars or at least the birthplaces of stars to try to understand them better. How do you study these stellar nurseries? and how do you collect the data to know what to put into these spheres? So many of our observations of stellar nurseries come from radio telescopes and infrared telescopes.

Much of the physical information that we have about these environments comes directly from these observations and what we infer from these observations. And so we can take these ingredients and sort of put them into the computer codes that we use to ultimately create the orbs that are used to represent the stellar nurseries. I'd love to dive in into how you make them, but first I want to learn more about what you can learn from studying stellar nurseries. These are where stars are born, and one of the most important questions in modern astrophysics

is to understand the life cycle of stars, and that really begins in stellar nurseries, or as astronomers call them, giant molecular clouds. So these stellar nurseries or molecular clouds, they exist throughout our galaxy and throughout most other galaxies in the universe. And so we would really like to understand how they evolve, how their evolution leads to the formation of stars. So we can have a more comprehensive view not only of star formation, but how galaxies themselves evolve. So you take this one stellar nursery and you make it into one sphere, right? and it ends up being this beautiful orb with swirls of blues and grays and browns,

and it really feels like you're peering into space. Now, how do you use the data to make those orbs? Do you 3D print them? Exactly. And so I have the idea that because these environments are so complex, you know, if you look at these beautiful pictures of the Carina Nebula, for instance, that just came from the James Webb Space Telescope, you can see how intricate and complex they are. And so I had the idea that in order to visualize them in a different way

and to really get a grip of these complex environments and how that relates to star formation, why not make a three-dimensional model of these environments. Does it really help to actually hold something in your hand? Does that really add new information for you? Absolutely. We're learning quite a bit from these prints. I sort of like to think of them as interactive simulations.

Astronomers learn a lot about simulations because they allow us to look at all sides of a physical object. They allow us to see how time elapses and sort of witness the evolution of various phenomenon and objects in a compressed time. And so humans are great at pattern recognition. And with a three-dimensional object in our hand, we're able to, perceive certain patterns and notice connections that we don't necessarily see on a two-dimensional computer screen or a piece of paper. And so we're learning quite a bit about the complexity of these environments and how the physical structure of stellar nurseries ultimately leads

to the formation of stars. God, that is, that's so interesting. Can you walk me through the process of creating these orb step by step? The idea is we would like to visualize these objects in their full three dimensions. And so we take these ingredients that we have, all the physics about gravity and magnetic fields, and we code that into a computer simulation. And so these simulations are representing the interstellar medium, the space between stars. Once a simulation is finished, you take that information from the simulation, which includes basically the physical structure of the environment, how the density of the gas and dust that makes up a stellar nursery, how that material is distributed. We put that information into a form that a 3D printer can understand. And then finally,

we feed that information into the 3D printer and it prints layer by layer that information from the computer simulation and the output is one of these 3D prints, one of these orbs that represents a vast stellar nursery that could be hundreds of light years across that we can now hold in the palm of hand. Do you feel something special when you're holding one of these in your hand, like you've entered another dimension? It does feel special. I think the wonderful thing about astronomy is that it's very humbling. And on the one hand, it really speaks to the power of human imagination and the power of the human mind to conceptualize these sorts of things. And on the other hand, it's very humbling because we know that As cool as these spheres are, they don't necessarily represent, you know, the absolute truth,

and there's so much more for us to learn. And so they open up quite a few questions, perhaps, you know, opening more questions than we started out with. Do you have an example of something that you learned that you would not have noticed in a 2D image? One of the things that we know from two-dimensional images is that stars are born within certain regions of stellar nurseries. And in particular, they're born in the densest regions. where the gas and the dust is the most compact and dense. However, we can't get a full idea of what's happening into the depth of these stellar nurseries just based on these flat images.

And so, for instance, we see these long, skinny, very dense structures where stars seem to prefer to be born. And they seem sort of like long skinny cigars or pieces of licorice that sort of wind their way through the cloud. When we see these similar objects in a three-dimensional print, oftentimes they're actually sheets. So sort of two-dimensional flat structures, more like pancakes, let's say, that are viewed in projection. And so this raises the tantalizing idea that perhaps filaments emerge from sheet-like structures and that the evolution from the beginning stages of a molecular cloud to a star may be more complex than.

than we had envisioned. That is very interesting. If you step back a little bit and look at the larger, I guess, concept of idea of what you were doing, the intersection of art and science, it sounds like this is very important to you. I think that art and science are two different ways of looking at the world. And we often pose very similar questions as artists and scientists. The question that unites these two fields for me is really about, you know, where we come from, where people come from. And I think the greatest lessons of astronomy for me is that it really shows us that we're united. We all come from the stars, quite literally. I'm fascinated by your work, and it would be great to see you continue what you're doing. Thank you. Dr. Nia Amara

is a visual artist and assistant professor of astronomy at UC Santa Cruz based in San Francisco. Santa Cruz, California. And that's about all the time we have for today. If you missed any part of the program, you'd like to hear it again. Subscribe to our podcasts or ask your smart smoker to play Science Friday. Of course, you can say hi to us all week on social media, Facebook, Twitter, Instagram, or email us the old-fashioned classic way. SciFri at ScienceFri.com.

Send us feedback. Tell us what you'd like us to cover also. Have a great weekend. We'll see you next week. I'm Ira Flato.