Materials Universe Podcast – Dr. Jean Anne Incorvia – Final
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[00:00:00] Bailey: Welcome to the Materials Universe podcast, where we will explore the materials world and how it shapes our lives. My name is Bailey Tibbett, and I will be your host this season. Please join me as I interview researchers from the Center for Dynamics and Control of Materials at the University of Texas at Austin.

[00:00:17] Hi everyone, and welcome to the Materials Universe podcast. My name is Bailey Tibbett, and I’ll be your host for this episode. And I also have with me our co host and producer,

[00:00:30] Audrey: Audrey Colgrove. Hi everyone.

[00:00:32] Bailey: And we would like to introduce our guest for this episode, Dr. Anne Anne Corvea.

[00:00:37] Dr. Jean Anne Incorvia: Hi, it’s so good to be here.

[00:00:39] I’m Anne Anne Corvea. I’m an associate professor at UT Austin in electrical and computer engineering. Um, I’ve been at UT for about seven and a half years and, um, my research is in, um, Nanoelectronic devices and their application mostly to computing, um, with some focus on magnetic materials, 2D materials, and, um, applications to unconventional computing.

[00:01:05] Bailey: Cool. If I remember correctly, your background is actually in physics, so how did you come across this field to start your research in?

[00:01:13] Dr. Jean Anne Incorvia: Oh yeah, thanks for asking. Yes, my undergraduate and my PhD are both in physics, and my postdoc was in electrical engineering. But, Even during my PhD, I actually had three advisors during my PhD, one in physics, one in electrical engineering, and one in material science.

[00:01:28] So even at that time, I was between these three fields, and, and it sounds like a lot, but you know, that’s actually like, when I was just at the, actually the big magnetism conference last week, I know there’s people from across these fields at these conferences, so it’s really a confluence of these three areas.

[00:01:41] Areas. Um, so I’m, I’m happily between all three, even from a while ago. You’re in the middle of the

[00:01:46] Audrey: Venn

[00:01:47] Dr. Jean Anne Incorvia: diagram, but I really am still happy. I did my PhD in physics. I, um, kind of early on my PhD realized that like, I really love learning the fundamentals and then in my research, I really like applying them and that’s like some advice I give to my students.

[00:02:00] I think about like, what brings you joy and it might be different in what you’re learning versus what you’re doing. Right. And some people actually prefer it, what they’re more like. Yeah. Doing discovery like what they’re in their research is more about, um, to everything’s aren’t known, or maybe you’re more like me.

[00:02:15] I really like to be inspired by one of my making that’s going to be useful for the world. And so that brings me more to the engineering side of that spectrum. And so I’ve since for a while realized I’m happy to be an engineer, but I am also a physicist. Um, yeah, but in terms of what drew me to this field, um, it was a lot of that.

[00:02:34] Um, Happy medium of fundamentals versus applied that drew me to it. Since I was kind of interested in both. I like that. I can still like write down planks constant in my day to day life. And yet what I’m doing. Um, I can connect to industry on I can connect to national labs. Um, and it has, um, this, um, impact that that is a little more near term.

[00:02:55] So that’s what drew me to it. Um, starting when I was actually beginning of grad school. That’s so cool.

[00:03:02] Bailey: I feel like when it comes to dealing with different fields that are so interdisciplinary, it kind of requires a very

[00:03:11] So I guess as a PI and as like a bunch of students, mentors and whatnot, like how do you foster that environment in your lab?

[00:03:19] Dr. Jean Anne Incorvia: Yeah, that’s a great question. It’s definitely a very interdisciplinary and Um, in my group, I have students who are working across that spectrum. So, um, some of my students are working on first principles, density functional theory for things like spin transport through new types of materials for like new types of tunnel barriers or new types of magnetic materials.

[00:03:39] So that’s very much on the bottom. And then some of my students are working on growth, doing this better deposition, um, And characterization of materials, um, doing things like transmission, electron microscopy, XRD, um, XPS, um, really like making use of the Texas Materials Institute a lot. So my students are more on the nano device side.

[00:04:01] Um, so there we use a combination of modeling to then come up with creative device designs based on the materials and the kind of application we want them to have. And then from the modeling, we, um, We narrow down to what kind of device structures we want to make, and so those students then are using our nanofabrication facility, which is the Microelectronics Research Center, um, making devices and then testing them, um, both in our lab and across campus.

[00:04:26] And then I even have students who are working up the stack from there. So some of my students are very interested in these applications to probabilistic computing, neuromorphic computing, brain inspired computing. They’re working on, um, Taking our device behaviors and material behaviors and putting them into neural network models and machine learning models and understanding of how can these new materials make a system level impact.

[00:04:49] So we try to do all that within our lab, but we also still, um, do need a lot of collaboration on it as well. So, um, I love to collaborate. It’s one of the reasons I became a professor. And we collaborate with people tangentially at all those different layers. And I would say in terms of mentoring such a diverse group, um, I just try to, um, understand what the student is interested in, you know, so I just find that some students really like one or two of those aspects and not the other ones, and that’s the ones I let them focus on, um, and then as I’m hiring new students, I just think about, okay, where in that stack do I kind of need more effort, and then I try to find students with those types of interests.

[00:05:23] Bailey: That’s really cool. I feel like Well, as a joke, I guess, sometimes I like to say the EC in MRSEC stands for Extensive Collaboration, because I feel like that’s all we do, like, not in a bad way by any means. I mean, obviously it’s quite wonderful, and I think your lab is. It’s definitely like the pinnacle of that.

[00:05:41] I know that you’ve like recently received tenure or got tenure and you also received several early career awards. So I think it’s very clear that like whatever method you’re using, it’s working.

[00:05:54] Dr. Jean Anne Incorvia: Yeah. I mean, collaboration is, um, you kind of have to decide like what kind of attitude are you going to have about research.

[00:06:00] And then you have to kind of, like, stick to that amidst the imperfections of the real world, right? So, I, I like to collaborate, and I, therefore, am really open to collaborations, and I don’t mind if that means, like, sharing the credit on something. You know, I’m always trying to think of, like, Who are the authors that should be on paper and don’t let anyone feel left out.

[00:06:21] I mean, I don’t, I’m always perfect at it, but I try, you know, so, and I try to like, then the people who join my group, I’m very clear. This is the kind of group we are. We’re a collaborative group. And if someone wants to be more competitive or doesn’t want that, then this isn’t the right group for them.

[00:06:35] Right. And then when you talk about things like tenure, you know, When you’re assistant professor, tenure track, you do need to establish independence as well. And so I made sure to do that as well. So things like, you don’t want every paper to be collaborating with the same people because you want to show that you can stand out on your own.

[00:06:51] So having a mix, you know, so some things that are really just driven by my group and some things that are a bunch of authors from across the world. I like to have both.

[00:07:02] Bailey: So you mentioned that your research is mainly around like magnetic materials. I think you’re Probably one of the very few labs at UT Austin, if not maybe the only lab that kind of studies magnetic materials in that facet.

[00:07:14] Does this impact like how you work or how you approach magnetic materials or kind of what’s your general approach?

[00:07:21] Dr. Jean Anne Incorvia: Yeah, so magnetic materials is a large class of materials. materials that, um, have magnetic properties and they’re a lot of fun because there’s something we’re all very familiar with. And magnets we use every day to hold things to our fridges and et cetera.

[00:07:38] Also magnets are used in a lot of other technologies that we’re familiar with. And then as magnets get smaller and smaller down to the nano scale, they have very interesting physical properties, both fundamental and then applied to technology. I’m probably the person at UT Austin most closely working in this field, but there are actually quite a few labs across UT Austin who either work in more, um, applied or fundamental sides of magnetic materials and also materials that utilize or have spin dependent properties across electrical engineering, physics, and also mechanical engineering.

[00:08:14] Can you expand more about the spin dependent properties?

[00:08:17] Audrey: I’m very interested in that.

[00:08:18] Dr. Jean Anne Incorvia: Yeah, yeah. So one of the reasons that this field of magnetic materials really caught my attention is that it’s a macroscopic example of quantum effects that actually influence our everyday lives. So the origin of magnetism can actually not be well explained by classical methods.

[00:08:38] You really need to look at quantum mechanics to explain magnetism. And yet, You would get these macroscopic objects, magnets, that we use day to day. A magnetic material is unique in that it has some correlation between the spin of neighboring atoms. And what does that mean? We’re all familiar with atoms where you have a nucleus and you have electrons orbiting the nucleus.

[00:09:04] So those electrons can have, um, different quantum properties. They can have orbital properties. angular momentum that’s quantized, and they can also have every individual electron has spin angular momentum, and so really, um, in these magnetic materials, we’re interested in how the orbital and spin quantum of every individual atom get coupled together across the atoms, and then you can get emergent properties like ferromagnetism, which is what we’re most familiar with, with magnets, but we can measure, and then you can get other properties like Thank you.

[00:09:35] antiferromagnetism. That’s when, um, there’s like every other ordering of the spin and angular momentum, um, and also more complicated things beyond that. And since these properties are existing at this kind of this correct, both, um, speed and, um, Dimensional levels of being around the nanosecond, picosecond regime, and usually we can make these devices around the hundreds of nanometers down to a few nanometers of sizes, um, they’re very appropriate for the speeds and dimensions of what we want to use as computing elements and memory.

[00:10:10] That’s a long answer to your short question.

[00:10:13] Bailey: I mean, I remember it’s been being talked about in like, Quantum chem classes a long time ago. It was very hard for me to conceptualize, but that was a really great explanation. Um, I guess like a good next question would be, you know, studying these materials and studying their spin magnetic materials as a whole.

[00:10:30] Like, where do you see There’s having an impact on material science.

[00:10:34] Dr. Jean Anne Incorvia: Yeah. So I think there’s a lot of impact in material science and then also in technology. So which one you want me to talk about first, maybe more material science to start?

[00:10:43] Bailey: Uh, yeah. Material science for sure. We are a material science podcast.

[00:10:46] Yeah. That’s what I love about

[00:10:47] Dr. Jean Anne Incorvia: this podcast because I absolutely love material science. And yeah, I mean, at the heart of it, what we do is material science. The nice thing about these materials is they can be tailored in so many ways. So the most common way is to grow thin films of them and then, um, have what we call like multi layers.

[00:11:05] So, um, we can have different thin films that are then sandwiched together in different ways to create heterostructures. One thing, again, it’s hard not to talk about the material science and the technology together because one thing I like about our field of nanomagnetism and spintronics is that We’re very closely tied to industry applications.

[00:11:22] So like the fundamentals and the applied really go hand in hand. And because of that, um, actually a lot of the materials growth are done using like industry compatible methods for then using them in technologies like memory and computing. So we like to use physical like sputter deposition to grow these films.

[00:11:39] Bailey: Are there any like specific magnetic behaviors that you’ve kind of grown that you’re like using specifically for a specific purpose? Technological application?

[00:11:48] Dr. Jean Anne Incorvia: Yes, that comes to what I’ve been talking about how in our field of nanomagnetism and spintronics, um, the material science and the technology really are very closely related.

[00:11:58] It’s kind of just been the, um, historically what’s been has driven our field. So, um, the biggest example is in the mid 90s, there was a Nobel Prize awarded for, um, the discovery of giant magnetoresistance in these magnetic thin film stacks. So that’s when you have a magnetic layer, like, say, cobalt, and you have a non magnetic conductive spacer, say, copper, and you layer another magnetic material, more cobalt, and then what they saw was, depending on the relative magnetization of those two magnetic layers, they could get a resistance change.

[00:12:31] If you pass current across these structures, and so you get on off ratio. So there you have something that could be a memory element. It’s one of the examples of the fastest from which something was discovered to use in technology to winning a Nobel prize. So I think the other example maybe was graphene, right?

[00:12:47] So, um, this was discovered and then very quickly after it was discovered, it was used in hard disk drives for read, write heads to both read and write data storage and these hard disk drives. Magnetic based memory drives and DMR and then after that, that’s giant magneto resistance GMR. Then the next that was covered after that is called tunnel magneto resistance, where instead of having a conductive layer like copper, they replaced that with a insulating layer.

[00:13:14] And now you actually have spin dependent quantum tunneling across that barrier between the two magnets. And that actually ended up producing, um, even bigger on off ratio than the giant magnetorresistance. So that’s a lesson in don’t call something giant because you never know when something more giant is going to come along.

[00:13:31] And so now they have to keep having to come up with a bigger term like colossal magnetorresistance. They’re like, what’s next? Macro,

[00:13:37] Audrey: macro. I think the astronomy field has a similar issue because they named the very large telescope and now they’re a little stuck.

[00:13:44] Dr. Jean Anne Incorvia: Exactly. So you have to be careful. But anyways, um, so really like.

[00:13:50] Um, due to this discovery of like GMR and that being so quickly used in like in memory technology, I think it really just like jump started this whole like this relationship between these magnetic materials and technology, right? So tunnel magnetoresistance then was first discovered in the like late 90s and then, um, really started ramping up in the mid 2000s and now here we are.

[00:14:13] Like, you know, 20 years later from that, and really now we’re seeing this magnetic random access memory, MRAM, as like a really exciting emerging, um, memory technology that’s come out of tunnel magnetoresistance.

[00:14:25] Audrey: Hello, everyone. This is Audrey popping in after the fact just to break down a few terms. We’re going to start with RAM, R A M.

[00:14:33] Also known as random access memory. In general, RAM is the storage spot in your technology where data lives when it is being used. The random in RAM refers to the fact that the computer can read through the specific data it needs regardless of the order the data is stored in. Let’s start with an example.

[00:14:52] Let’s say you’re packing things to move. Your apartment stores all of your items in specific locations, much like computer storage. Unfortunately, you can’t teleport all of your items to your new apartment, and you need boxes to help you carry stuff. In this scenario, RAM acts as the computer’s moving boxes, or moving capacity.

[00:15:12] Using a box, you can retrieve any data in your old apartment, regardless of where it is stored, and put it in the box to actually use and interact with the items. But what happens when you’re all done moving? The short answer is, it depends. The important part is whether or not you finish storing your items.

[00:15:29] In cases where you are using SRAM, static random access memory, or DRAM, dynamic random access memory, if you don’t finish storing your items and putting them back in the box, And are somehow interrupted by the computer, your computer will discard everything that is in that box. So, if your computer crashes, every piece of data being stored in the SRAM or DRAM will be erased.

[00:15:52] Dr. Jean Anne Incorvia: And so, that’s been like, just recently, last couple years, really rapidly growing. I can tell you more about that if you like. So, um, this, this really close connection then to industry, um, really helps drive our research.

[00:16:03] Audrey: I would love to know a little bit more about that, because I know you have quite a few, like, Really solid connections with industry.

[00:16:09] For example, the Taiwan Semiconductor Manufacturing Company, right? Do y’all do a lot of your magnetics works with them as well? Yes,

[00:16:15] Dr. Jean Anne Incorvia: we do. Yeah. So, um, a lot of this is driven by MRAM. So, it’s Magnetic Random Asses Memory. And so, just to briefly describe MRAM, hard disk drives are great, right? They are these magnetic disks with just Unpatterned magnetic media, and then you can go by with this whirring read write head so you can think back to maybe five years ago when your computers had these, and you would hear them turn on and whir around, right?

[00:16:39] And so that’s what’s reading and writing, um, by applying a field that then can write the local magnetic grains into an up or down magnetic orientation, right? And then it reads out by using these tunnel magnetic resistance read heads to then sense. The local magnetization by a resistance change, right?

[00:16:57] So that’s how they worked and they’re great. And one great thing about them is that, um, for long term storage, um, they’re still the best option, like as long as you don’t put a huge magnet on those things, they’re going to keep their data for a long time. So in data centers, hard disk drives are still ubiquitously used, but for things like laptops, they have been replaced by solid state drives, right?

[00:17:21] Because we’d prefer not to have. Moving parts, right? And so solid state drives use like silicon based transistor technology to encode memory. And so now, MRAM is coming along, and MRAM is kind of like the best of both worlds. Because you can still encode the data in the magnetization, but now it’s all solid state.

[00:17:40] So everything is electrically read and written. You don’t need any, um, worrying, hard disk drive, read by head. Yeah, that’s fun. That’s essentially the benefit of MRAM. And then another exciting thing about it is it is back end of the line compatible. That means that an industry has shown this very well, that you can create this memory right on top of your transistors that are doing the computations, and then right above them you can have your magnetic memories, or MRAMs.

[00:18:08] So with that, a lot of the Big semiconductor companies have been heavily invested in MRAM, um, including TSMC, Samsung, Global Foundries. And so they all now are producing MRAM. And what’s been really exciting in the last couple years for MRAM is that for embedded memory, now MRAM and Another type of memory called RRAM are the only two options available for scaled CMOS.

[00:18:33] It used to be that people would use SRAM, but that’s become just too expensive and too hard to scale down to small sizes. So really now, MRAM is one of the two choices that these companies have for embedded memory. And so, because of that, it’s really accelerated, um, MRAM as something that’s going to be used in computers.

[00:18:51] Audrey: Hey everyone, I’m back again. Before engineers like Doctor and Korvia started looking into new technologies, it was clunky and scary to use RAM because of the threat of data loss. MRAM, which Doctor and Korvia referenced as Magnetic Random Access Memory, is considered a whole lot more stable because it uses magnets to store the data you are using, acting like a tiny hard drive.

[00:19:14] Essentially allowing you to temporarily store your box while you take a break. Another type of RAM is called R ram. The R in R RAM stands for resistive and stores data by changing the electrical resistance using ion migration instead of using magnetism, again, allowing the items in your boxes to be stored without fear of them being emptied.

[00:19:36] Now, ideally, you’d have a box like Mary Poppins famous bag, where the storage capacity is limitless despite its small physical size. That is where our last acronym comes in. CMOS, or Complementary Metal Oxide Semiconductor, is used to make RAM as small as possible, which is helpful for making technology as carryable and efficient as possible.

[00:19:57] So

[00:19:57] Dr. Jean Anne Incorvia: now it comes to research. So now all these companies have developed MRAM and so they’re very interested in like, what’s next for MRAM? What else can we do with it? Right? And so that’s where my group’s research comes in. We think a lot about what’s next for these type of magnetic technologies, both on the material side and then on their application to different types of computing beyond simple memory.

[00:20:19] Audrey: So the, the noise of our laptops loading a really big video game is going to become nostalgic, like the, like AOL startup sound or something. Yes,

[00:20:27] Dr. Jean Anne Incorvia: yes, and what will become nostalgic is the time it takes to do that, right? Because in our field, one of the big, um, The problems that are highlighted at the beginning of many talks is what’s called the memory wall.

[00:20:39] Have you heard of the memory wall? Yeah, so there’s in traditional computer architectures, compute and memory are done in different parts of the chip. And then the biggest bottleneck to high performance compute is the time and bandwidth of translating compute and memory. between each other. So that’s where these memories that can be brought closer to the compute, either embedded in 3D, so we call it like CMOS plus X, where the X is the memory or whatever it is on top, or even if you have memory elements that can also compute at the same time.

[00:21:09] So this is all this field of in memory computing can really solve this huge delay, and it’s a very non trivial delay. So, yeah. One of the examples, um, that was in a paper at a Stanford a couple years ago was they analyzed when people do genome sequencing and they look at the time it takes to do genome sequencing, 96 percent of that time is this memory access time.

[00:21:29] So you can imagine, like, what gains we would have if that was gone.

[00:21:34] Bailey: Yeah, as a biomaterials scientist, I can confirm NGS has come a long ways and genetic sequencing. Oh man, that sounds wonderful. I mean, it sounds amazing just to have like faster computing power and like more accessible computing power for sure.

[00:21:49] Where do you see

[00:21:50] Audrey: microelectronics going in the next 10 years? Yeah. They seem to be going places, and I’m kind of curious to see like where we’re going to go next. Because like it started with like phones and computers, but there’s definitely more. No, microelectronics,

[00:22:03] Dr. Jean Anne Incorvia: semiconductor electronics, um, this whole era of nano electronics is really, um, exciting right now, um, so I think that there’s a bright future for it and a lot to do.

[00:22:14] A lot of it is driven by AI. I know we were briefly talking about AI before the start of this podcast. So a few years ago, we celebrated the 75th birthday of the transistor, right? And so you can think of like in those 75 years, our silicon CMOS transistor technology has been evolving hand in hand, which what, with what we call the Von Neumann architecture, which is, um, is memory and compute type architecture, which has this memory wall.

[00:22:41] Right. And so we’re kind of. Now exiting that kind of pipeline and we see this forest of untapped potential and all these different types of applications like these AI applications with or in sensor computing applications, edge computing versus high performance cloud computing and all of them really need to be approached in a unique way.

[00:23:04] I think that A lot of, I see a vision of this application specific accelerators in the future, where, um, instead of having like a universal silicon based chip that just works for everything, we’re going to have these smaller chiplets that are uniquely designed from the bottom up for those applications.

[00:23:21] So you can imagine, and that’s where we get into this neuromorphic computing, maybe for AI tasks and for tasks that are more human like, like interaction with environments and things like that. We’re going to want to have, uh, Processor, which is more like the brain, right? Um, the brain is really good at certain things, like, um, quickly taking in data from all around me and processing it and doing multiple tasks at once, or, um, adapting to new things in the environment.

[00:23:47] But then there’s other things the brain’s not so good at, right? So if I have to factor a large number, I probably still want to use high performance compute for that, right? So, yeah, we’re, so we’re kind of going this direction of these application specific chiplets, um, and, um, And the fun thing is that since we really want them to be well honed and they need to be well honed for these really expensive in terms of energy and time applications, we really do need those designed with the bottom up, including new materials and how we can holistically have system level energy benefits from those new materials.

[00:24:15] So there’s a lot to do there and all these different, um, applications. Um, and then. There’s a lot of innovation also than how these chiplets will be put together. And so that’s this whole area of heterogeneous integration and advanced packaging, um, is also a big focus here at UT Austin. If we can then smartly put them together, have thermal management and create like packaged application specific computing.

[00:24:38] Bailey: Oh, wow.

[00:24:39] Dr. Jean Anne Incorvia: That’s so cool.

[00:24:39] Bailey: I feel like we’ve discussed so many different technologies and applications, but is there one that kind of almost has your heart in a sense, or maybe your brain might be a better way to put

[00:24:49] Dr. Jean Anne Incorvia: it? Um, I still am really excited about this whole area of neuromorphic computing. Um, so also called brain inspired computing.

[00:24:57] And it’s because for magnetic materials, I think they just, maybe somewhat non intuitively, a lot of their. Dynamic behaviors, you can think of them similar to the type of behaviors that go on the brain. They just have, like magnetic materials, you can create oscillations, vibrations, there’s like that natural stochasticity and how a magnet moves in time and space.

[00:25:20] And all these things can be well controlled with voltages and currents. And so we kind of have this like fun maker space that’s happening at the nanosecond timescale and the nanometer, region that we can apply to these brain inspired type applications. Um, that’s a bit of a large focus of my group, um, trying to develop artificial neurons and synapses that make use of magnetic materials.

[00:25:45] Audrey: So, so

[00:25:45] Dr. Jean Anne Incorvia: to clarify,

[00:25:46] Audrey: you’re, you’re essentially trying to make neurons out of magnets.

[00:25:49] Dr. Jean Anne Incorvia: Yes. And synapses.

[00:25:51] Audrey: And synapses, sorry. And

[00:25:52] Dr. Jean Anne Incorvia: I think it can get more complicated from there. We’ve done some work on dendrites, too. Oh, but I love the visual of that brain. Yeah, yeah. So, um, and then, and then it’s a really open field because, um, we also have worked with people in neuroscience and neurology, and it’s a really nice synergy with them because firstly, there’s all of these behaviors that can be measured, and one, like, could we implement these higher order behaviors in our magnetic versions?

[00:26:21] And two, Can we show that that’s useful to do so, right? Like, is it useful to have that? And I can give examples if you want. And then there’s closing the feedback loop. We can then talk to the neuroscientists about how, oh, hey, this was useful in our artificial computers. Maybe we can better understand why these properties exist in the brain.

[00:26:38] So it kind of comes full circle.

[00:26:40] Audrey: I love the like, natural inspiration that’s kind of coming into this. Like a lot of the technology that y’all are working on is inspired by a lot of the world around us. So our brains, and then like, obviously the earth in itself is its own magnet.

[00:26:52] Dr. Jean Anne Incorvia: Yeah, that’s true,

[00:26:53] Bailey: yeah, yeah.

[00:26:55] I guess you could

[00:26:55] Audrey: say the field is magnetizing.

[00:26:58] Bailey: Just kidding, I’m so sorry for that dad joke. But if your group ever needs a tagline, you know, it could just be, we’re just magnetizing. I love it.

[00:27:09] Audrey: Sorry, can you imagine if labs had taglines? I think it would be, make a better world. And this is

[00:27:14] Bailey: very

[00:27:14] Audrey: tangential.

[00:27:15] I’m sorry. Well, awesome. Um, we also wanted to talk about, uh, you seem to have a passion for outreach, like educational outreach. We know that your lab group is part of Girl Day every year, um, and then also y’all been involved in outreach in the MRSEC multiple times. What kind of skills do you think outreach fosters in both, like, yourself as a scientist and in the students you mentor?

[00:27:38] Dr. Jean Anne Incorvia: Yeah, um, So I think outreach is a required part of being a professor or running a research group. I think it’s really important and so it’s something I make sure we devote time to. I mean a lot of it is about fostering the future generations of researchers who are going to get interested in all sorts of fun fields and making them feel like Just aware of what we’re doing and then get them interested and whether or not they go into this field, they’re still aware of it.

[00:28:06] And they, um, have gained something in their understanding. And then therefore, like, you know, there’s various levels of outreach from like K through 12 with things like this Girl Day and STEM that we like to participate in. It’s always a lot of fun to do some hands on demos that they can interact with and we can talk to them and their parents.

[00:28:25] Um, And then in terms of like high school outreach, we’ve done things like had high school students, um, join our lab for the summer, although I should be careful saying that on a podcast because I’ll get a bunch of high school students emailing me. I do get too many emails from high school students asking that.

[00:28:40] I think they somehow found out I’ve done that before. Um, we can cut it if you want. And then, um, College students, um, definitely trying, we actually try to support a lot of undergrad researchers in our lab, which I think is really essential because really to get into a good grad school, you really have to start doing research as an undergrad.

[00:29:01] And then not only that, it’s not just for students going to grad school, even though that’s a great outcome if they do want to get a PhD, but when you really think about like what is the place of education and higher education for like the world, you know, we have this. This has existed synergy between teaching the fundamentals and showing the cutting edge.

[00:29:22] I think that’s why I love the the model of like a research university in the US where I’m teaching a research or go hand in hand. It’s not like you’re teaching somewhere separate and doing research only at a national lab or something like these are happening at the same place. And so I think therefore it’s really important to let the undergrads get exposed to the research of of being at a great research university.

[00:29:45] Yeah. Whether they go to grad school or not. Yeah,

[00:29:48] Audrey: I, I love that so much. Sorry, um, I have a big spot in my heart for educational outreach, obviously. That’s what we’re here to do, um, and so I just love seeing it be embraced so much by like the scientists that we work with here. It’s really inspiring and cool.

[00:30:03] Bailey: Yeah, it’s definitely like a core part of MRSEC for sure, especially with our research experience for undergraduates program. I know like for us allowing undergraduates to have that first taste of research is It’s really important. I feel like people always say like, oh, research, it’s kind of scary because you don’t know what you’re learning.

[00:30:22] But I think sometimes it’s, you’re just learning how to problem solve and that sometimes can be the most important thing.

[00:30:27] Dr. Jean Anne Incorvia: Yeah, I think you touched on something really important there because I really think that’s one reason why. Um, employers like to hire PhDs is that they’ve proven that they can just be independent problem solvers.

[00:30:40] And that’s, I think, me as someone who, um, now has, like, been the boss and mentor for many a person, like, you, you come to understand why that’s, like, important. One of the most important skills to have to really go after big problems. So, yeah, I kind of feel like as long as my PhD students are, like, going to, like, great positions, getting great jobs, like, I’m going to keep doing this thing because I think it’s really good for them to get PhDs, yeah.

[00:31:04] Audrey: This whole subject is actually, um, a really popular topic right now in educational spaces. Because they’re kind of bringing this problem solving, engineering minded rhetoric into STEM education. Because they’re realizing that we need to start teaching problem solving from a younger age. Because it builds, you know, not just scientists, it builds artists, it builds all sorts of people who are really well equipped for all of the interesting problems we come across in our lives.

[00:31:29] And I

[00:31:30] Dr. Jean Anne Incorvia: think a lot of it, like you said, it’s about, um, Um, getting beyond a fear of failure, a fear of the unknown. Um, so yeah, if you, I know we noticed that we teach our freshmen. I usually teach intro to EE, which is, um, freshman class. And some of them are better than others in terms of coming in to university and problem solving.

[00:31:49] That’s something we really try to help them get comfortable with in their first semester, because that’s a lot of what engineering is. And for a lot of them, it can be scary. Like going from more rote memorization type learning to. The exam problem will be based on the same concepts you learned, but it might not be like a rote application of exactly what you learned, you’re going to have to think on your feet.

[00:32:08] That can be scary at first, um, but once they get used to it, I think it makes it a lot more fun, right, than just having to memorize and then regurgitate what you memorized. Yeah. That’s what I loved about studying physics

[00:32:20] Audrey: in college. Every test was like a puzzle.

[00:32:22] Dr. Jean Anne Incorvia: Yes, I had a college professor say the same thing.

[00:32:25] He’s like, well, he’s like, no matter how hard I test is, if you feel like you learned something after taking it, then it was time well spent. Yeah, I’ve

[00:32:32] Bailey: definitely had that experience with most of my engineering and science classes as well. Although sometimes it’s still scary.

[00:32:39] Dr. Jean Anne Incorvia: So it can be scary for younger people.

[00:32:41] So the question is, how can we get them over that fear? I think it’s, it’s scary no matter when you start doing that. So if you start doing it earlier, then you can get more used to it. Since I guess probably not that different other things like public speaking or, um, leadership earlier, you can start practicing it.

[00:32:55] You get comfortable.

[00:32:57] Bailey: Yeah. I guess as a mentor, do you have any kind of tips or any strategies that you use to help? your grad students and maybe your undergrads kind of get over that barrier or just kind of dipping their toes into the failure pool?

[00:33:10] Dr. Jean Anne Incorvia: Um, you know, that’s a great question. I think it’s helpful that we have like a group meeting every week where we all talk about the challenges that we, that we’re experiencing in, in everyone’s different research projects and kind of brainstorm solutions together.

[00:33:25] So, I know when I was a grad student, that was really helpful for me. Actually, I experienced that like, my PhD group, I, my project was a little different from everyone else’s group and had some more challenging nanofabrication. And so, It was like a breath of fresh air when I got to my postdoc group, when everyone else is doing the same type of more challenging nanopropagation as I was, and I, we, we had our group meeting and I’m like, Oh, wow, other people have the same challenges that I do.

[00:33:49] I wasn’t just the only one struggling, right? So seeing that, like, you’re, you’re not in this alone, I think is really helpful. And then, you know, Going back to this idea of collaboration, having this kind of, um, group where everyone is in it together and willing to help each other out. And I’m one of those people that this, hopefully the students feel like they can come to me when they are facing challenges and they can’t get over them.

[00:34:13] Helps you feel like you’re supported in this challenge.

[00:34:16] Bailey: Yeah, there’s nothing like camaraderie formed during struggle. Yes, exactly. Like every movie ever. You make the best connections that way, really.

[00:34:25] Audrey: Now that I think back to it, I definitely connected to some of my physics peers through the struggle and the classes.

[00:34:32] Bailey: Well, I just remember, like, sometimes, you know, in classes, just getting through the homeworks of just, like, sitting in the computer lab for undergrads together for hours until like 8 p. m. being like, I don’t know why this

[00:34:44] Dr. Jean Anne Incorvia: won’t work. I know. Yeah. And it’s, it’s always the balance when I talk to like, say, the freshmen, like, what is an appropriate amount of normal challenge versus what is a sign that, You need to, like, reflect and decide on what’s not working, right?

[00:35:00] And so, and I’ve noticed that with, um, some students that maybe if it’s too challenging, maybe it’s because they’re lacking in some piece of knowledge. Often it’s like a math background that if they can, Uh, they’ll come up to speed on, they’ll realize that, okay, now I feel more in the same place of challenge as people around me.

[00:35:18] So, evaluating that that it’s still fun, it’s not like suffering challenge, is, is, is what you have to be careful of, right? Yeah.

[00:35:25] Bailey: For sure. Uh. I remember in like, elementary school, when they were teaching us how to read. We had like the five finger rule or something like that, but it was basically like you read the first page of a book and if there are one or zero words that you don’t know, the book’s too easy for you.

[00:35:42] You’re not going to learn much from it, but if there are like three ish to four ish words that you don’t know, it’s almost that sweet spot, but if there are more than five or Or five, it’s too hard. You’ll just get really frustrated. Yeah, well,

[00:35:54] Dr. Jean Anne Incorvia: that’s good to know, because that’s a really good analogy for it.

[00:35:57] Yeah, yeah, that can help because I know a lot of times, especially like when you talk to students, like in high school, they’re worried that science and physics and material sciences can be too challenging. So if you give them a more concrete way to kind of evaluate the challenge, maybe it won’t feel as scary.

[00:36:14] Yeah,

[00:36:15] Bailey: yeah, I definitely remember thinking about physics and math. Being like those people are just geniuses. I cannot do the chalkboard thing with the equations But it’s definitely just something that I think you have to practice.

[00:36:27] Dr. Jean Anne Incorvia: Well speaking of helping people start from early age I feel like we’re not like we can’t do this We don’t do this anymore when I a long time ago when I was a freshman at Penn You see, Berkeley in physics, um, my first class, one of my favorite professors, he would have us get up to the board and do problems in front of the class.

[00:36:45] And we would get up there and like, we would often just be stumped and just like, stand there with like, not doing anything, but you know, yeah, at first it was scary, but then like, We all kind of got used to it and like we stopped being scared about it and it was actually really, I really enjoyed that class.

[00:36:59] I

[00:36:59] Audrey: definitely walked out of a few professors offices just covered head to toe in chalk from just sitting there and tapping away on their chalkboard working through it.

[00:37:08] Bailey: So the theme for this season is kind of like emerging materials and kind of exciting technologies. So is there anything in your lab that you’re like really excited to see in the material science, um, space?

[00:37:18] I know you kind of already talked about a lot of them. So Maybe just a brief summary again.

[00:37:24] Dr. Jean Anne Incorvia: Yeah, well, maybe I could just talk, since I was just at this Magnetism and Magnetic Materials conference last week, Um, I can just maybe talk more broadly about where the field is kind of going. Would that be okay?

[00:37:35] Yeah, um, so it was actually a really inspiring conference. I’ve been in the research world long enough to see like, fields kind of go up and down as like new things come along and people figure things out. So I feel like we’re at this nice upswing in magnetic materials right now where there’s A lot of unknowns and interesting things on the horizon materials wise.

[00:37:52] So, um, a couple are those big topics at this conference. One is like these non collinear antiferromagnets. So I talked briefly about how you have like ferromagnets or antiferromagnets where the spin of every other atom, say, are opposite each other. But the non collinear antiferromagnets means that you have a net zero spin, but there is something more complicated going on in the spin structure.

[00:38:14] Like maybe it’s more, uh, angles to each other. And we’re starting to understand that these type of antiferromagnets can have different spin transport properties that could be used in technologies like memory and computing, and maybe at faster speeds. There’s another field right now, similar to that in our, um, field.

[00:38:33] They’ve coined this new term for Certain types of anti ferromagnets, they’re called ultramagnets. So that was actually a big point of debate at the conference last week, like, are these ultramagnets real or are they just like a recategorization of known anti ferromagnets? So it was a lot of fun that this, like, these, like, opened, very open to debate, like, new types of concepts.

[00:38:54] Um, another big future direction are these magnetic Weyl semimetal materials. These materials can have, like, topological species. Been properties where you can have like there’s been momentum tied to their directional motion and things like that, but they’re also conductive compared to like topological inflators.

[00:39:14] So, um, those seemed like they’re going to be really attractive for accomplishing some of the similar All right. purposes as topological insulators while having lower resistivity, which usually is, has been one of the challenges of using topological insulators. So another big area is there’s been a lot of headway and using magnons and spin waves, both for computing and for like sensing them with things like magnetic tunnel junctions, trying to do more commuting processing and like the wave like nature of these.

[00:39:41] Spin and magnetism structures and their AC dynamics as another big topic that is really growing right now. And also another one is, and something that our group does work on too, are these magnetic scurmions, which is like a magnetic spin texture that has like little swirls of magnetism. I think it’s coming along.

[00:40:01] That field has been around for a few years, but now we can more readily make these scurmions and use them for technology. So yeah, there’s just a lot of fun things to do going forward. So

[00:40:12] Audrey: that begs the question, though. Do you think those magnets exist?

[00:40:18] Dr. Jean Anne Incorvia: Well. Depends who my colleagues are listening. Um, I would say from talking to a few people last week where I was trying to assess that out, it was definitely under debate.

[00:40:29] Gotcha, gotcha.

[00:40:31] Bailey: Well, now we know how to ignite some magnetism scientists. It’s a good conversation. That’s so cool. I feel like everything you’ve been talking about, I mean, this whole podcast and especially just like the applications and stuff is just so at the forefront of like what we’re able to do right now in nano electronics.

[00:40:51] I think that’s so cool. So, um, We’ll definitely be looking out, uh, into the future and kind of looking toward these applications that you’ve been talking about and looking toward the wonderful things that your lab does. Great. Thanks for having me. Thank you so much for joining us today. Thank you. That’s all for today’s episode of the Materials Universe podcast.

[00:41:10] Thank you for listening to our interesting conversations with inspiring guests from different fields of science and engineering. We hope you enjoyed learning something new. Please leave us a review and share this podcast with friends. You can follow us on social media at TexasCDCM on Instagram and X.

[00:41:26] Thank you to the National Science Foundation and the University of Texas at Austin, and an additional thank you to the LAITS Audio Studio crew for their help with the production of this podcast.