E12: Advancing Advanced Manufacturing | associate professor Danielle Cote

Colleen:  Picture it, Worcester, the 18 hundreds, a powerhouse of the first industrial revolution, a Massachusetts city where factories, hummed inventions took shape, and manufacturing helped drive America's growth. Today that legacy continues at Worcester Polytechnic Institute. Where researchers are helping shape industrial growth through advanced manufacturing, from AI powered production lines to recycling critical materials. This new era is all about innovation, sustainability, and resilience. In this episode of the WPI Podcast, we're diving into what advanced manufacturing really means. Why it matters now more than ever. And how WPI is helping lead the way. I'm Colleen Wamback, and our guest is Professor Danielle Cote, a leading expert in material science and engineering at WPI, whose work explores the future of how we make things from the atomic scale to the global supply chain. Whether you're a maker. A curious listener, or just someone who wants to know how technology is transforming the world around us. This conversation is for you.

Hi, Danielle. Can you briefly introduce yourself and explain what materials engineering and advanced manufacturing mean? 

Danielle: I am Danielle Cote, an associate professor in Material Science and Engineering, which is part of our mechanical and material science department at WPI. Materials Science and Materials Engineering, as the name aptly implies, it's really the science of all materials and we think about what materials are. It is. Everything. Everything you are sitting on, everything you are touching. The microphones we're speaking into, everything is a material. And as a material scientist, what we often do is we look at the properties of materials from the large length scale, which is maybe how hard it is, how tough it is, how strong it is, all the way down to the tiny length scale of the atoms and the way the atoms are bonded, how many protons, neutrons, electrons, these atoms have. And we look at that whole spectrum, that whole length scale. And then the materials engineering part of it is not just understanding how the materials are, how they behave, but then figuring out ways we can engineer them to make them better. So, we're improving the properties we make may make material harder or stronger. And we do that by understanding what's happening down at that molecular level. 

Colleen: So, you really can't have advanced manufacturing without materials engineering. 

Danielle: Yeah, absolutely. So advanced manufacturing in WPI terms is very interdisciplinary. So, one of those disciplines, part of advanced manufacturing, is material science, and we're also adding robotics. We're adding computer science, data science, ai writing, all of those different disciplines together to get advanced manufacturing, which is where we're essentially making manufacturing. More efficient by incorporating technology and incorporating these new processes. 

Colleen: Your lab at WPI is tackling something called rubble to rockets. Could you describe how you're using scrap metal and AI to create these high-quality parts even in extreme environments?

Danielle: Yeah, absolutely. So, Rubble the Rock is a really fun program, and essentially, we're taking rubble, or in our case, scrap metal, right? We chose metal as our rubble, and we're building a sounding rocket, and that's proof of concept to show that we have the infrastructure to take scrap metal and produce a component out of it. AI comes in because what we're doing is we're taking this rubble, so in our case, the metal, we're characterizing it, we're getting the composition of the material. Then we're making feedstock metal powder out of it. And that metal powder is really what's used to do our prints. So, we're 3D printing our rocket-we're using two different additive manufacturing techniques to do this, and the AI is able to guide us. So, we don't need to test every single piece of the scrap. We can take new scrap material that maybe we haven't seen before. If you're in a, in an austere environment or just any unpredictable environment, you don't know what you're going to have for scrap. So, using AI, we can take. Properties of the material that we do have and say, alright, we've encountered materials similar to this before. Here's how we can make a rocket that's going to be high quality. That'll actually pass in this case a burst pressure test that it'll actually survive. 

Colleen: I understand this could be used in battlefields if a piece of equipment broke down and just as important. I'm guessing this could be used in search and rescue missions if you couldn't bring in a big piece of machinery. Yeah, absolutely. So, the idea behind this program in particular. Is to develop a framework, and the framework allows you to take whatever resources you have available to you and make something out of it, in this case 3D, print something out of that and really remove a lot of the uncertainty and the variability, which is inherent, especially if you literally have a pile of scrap, right? That you don't know what's in it. So, I think the idea here is just adaptability. The program is super adaptable, so to whatever environment you're in, and this could be on Earth, this could also be in space, right? We can look truly anywhere and use this framework that we're developing to make these components. And again, it could be to repair a component, it could be making a new component depending on the application. 

Colleen: You touched on this AI being incorporated in the process, but can you dive a little deeper into how AI is being used and can be used to identify these scrap materials?

Danielle: Sure. So, one big way that AI is used in the material science field and also in the manufacturing field is we have essentially an infinite combination of periodic table elements. If you picture the periodic table and you combine them, there's so many different ways you can do that and making new materials with each of those. So yes, technically we could combine all of them in all the different ratios. And amounts and develop material, but using AI allows us to create a much smaller selection of those materials and then essentially predict properties of those materials. We're not testing in this program. Again, we don't have a full lab on the battlefield, or we're a full lab wherever we're going, so we're not able to test all the properties and all the materials. So, we're sort of filling in the gaps and using AI to predict what might make good material combinations. 

Colleen: Why are those predictions so important?

Danielle: If we didn't, we would be guessing. And sometimes you have intuition and there's educated guesses for sure, but we're augmenting those educated guesses with another checkpoint. Right. Another a little bit more data to help make that educated guess. 

Colleen: The difference between guessing and knowing for almost certain when you're building a piece of equipment is critical. It could be the matter of, and not to be dramatic, but life and death because of the strength that's needed, and also making sure that. These different materials are bonding together. I know I'm putting on my PhD cap here. I've been spending a lot of time with you, I guess, but are those some of the critical areas that you're looking for?

Danielle: I give you an A for speaking the language that was Thank you very good. That was good. Yeah, absolutely. So, a big part of this too is uncertainty quantification. So, every step of the way we can say, here's what our risk is, right? So, in the end, we're able to calculate that quantitative risk to understand here's what we think the final properties will be, plus or minus a certain percentage or a certain value. So, then the decision makers in the end can make that decision. Is that risk tolerable or not? You're right. It's absolutely crucial to understand that risk. 

Colleen: Sticking with the R words risk and now recycling. I'm guessing when you're looking at all of these metals, you just don't want to throw everything into the mixing bowl, you're able to better allocate and get better recycled materials. Again, I am trying to sound scientific here. 

Danielle: This is actually right up the alley of one of our teammates, VALIS Insights. Emily Moted at Valis is leading our effort on that, where she's characterizing all this recycled material and saying, okay, if you mix certain components, you'll be able to create this particular alloy. Which our models down the line, sort of behind the scenes are able to predict we'll have good properties. So that's really something that Valis has been able to do for us.

Colleen: Okay, we've been speaking about the Rubbles to Rockets program, but this isn't specific just to rubbles, to rockets when we're looking at how to recycle materials, this is across the board in many cases in your work.

Danielle: Absolutely. This is one of our newer efforts that we've been looking at for the past, maybe five or so years, on ways to recycle material, and in our case, because we do a lot of metal 3D printing with powder, metal powder as feedstock material, so as like the ink for your printer, what we're doing is looking at. Collaborating with a partner, Nightshade Industries, who's also on the Rubble to Rocket program, but they have a plasma atomization unit. So, what that does is it takes any of this metal that we have, it melts it down, and it's creating very fine metal powder. And that metal powder allows us then to characterize it, to look at under microscopes, to understand what its chemical composition is, what quality is it, and if it's good quality, then we can print something. And when we print something, you can essentially reprint that exact same component that you melted down in the first place. So, you can come full circle with this. That's been a really interesting effort that's had wonderful success on a variety of different materials, different metals and different metal alloys. Well, that's one way we've been looking at the recycling component. The other way, and this has been again, more of a recent effort when you're printing not all of this powder that you're using as your feed stock, not all of it goes into the final component. So, depending on your process, the powder may be left over.It may be over spray, but basically you end up with a yield. Some of your powder makes it into the material that you're building, and then you have some leftover. And depending on how much it is, what quality it is, we're looking at ways we can recycle that. So, the first part is capturing that. Depending on the process, it could be a very volatile process or turbulent process where you end up with powder all over the place and you have to capture that. Other times the powder may be exposed to high temperatures, or it may be deformed in a certain way, or maybe it has been exposed to laser beams. So, we have to figure out can we capture it? And if we capture it, are there ways we can recover it and reuse it again? So then again, we end up with this a hundred percent recyclability. And the neat part is if we combine those two, we're taking scrap metal, we make the powder we print, and anything left over from printing, we're able to recycle. So, we're able to keep this closed loop, and that's one of our big goals to do in our group.

Colleen: A term that has been in the news, I think a lot of people have heard in recent years is critical materials. So, what are critical materials and why is it so important to source them, or in your case, recycle them domestically rather than rely on foreign supply chains? 

Danielle: Great question. So critical materials really depends on who you're asking, what material, and it literally means materials that are critical to you. So, we may have different critical needs. We, being the US, may have different critical material needs than other countries. It depends on what we use these materials for, but they're materials that have no substitute that we need for our essential day-to-day living. That don't have a substitute. There's nothing we can use to replace them. And when I think about supply chains and why we need our own critical materials, domestic supply chain, or a domestic source of them, I guess I, I think about a pantry at home. You have your pantry in your house, and you have it stocked with certain materials, right? Like we can stockpile some of our critical materials, but then maybe you have your garden outside where you're able to grow. Some other ones, some important. Food items that you need. And then you have your neighbors and those are sort of like your actual neighbors or your allies that have more food. And in that case, you need to make a cake, or you need to do something. It's better to have all your ingredients at home. 'cause you can depend on that. You know, 100%, I will have enough materials to make this cake or to make whatever you need. If you're relying on the grocery store for something, right? That may be an international source. Maybe they don't have that material. Maybe the grocery store is out of eggs. We saw this happen recently, so you can't necessarily depend on that. Or maybe they have an incredibly high price on that material, or maybe there's a tariff on it now. So, while sure you can buy it, you're going to be paying a hundred times more than you would pay if you had your own chickens in your backyard. So, it's important to have our own domestic supply chain for reliability.

Colleen: Okay. Do you see opportunities to use your AI guided additive manufacturing for clean energy applications, like components for wind turbines, solar panels, or new batteries?

Danielle: Essentially, we're creating a framework, and that framework is really agile and really adaptable to different manufacturing techniques, but also different applications. In any of those examples, we'd be able to develop this framework using ai, using our data science capabilities to essentially, again. Calculate that risk, calculate the uncertainty in our final properties, and then tweak the printing process so we're able to produce final properties and get these materials. Again, with that sort of quantification of how much risk would be involved in the final components. Okay. 

Colleen: Can your work play a role in reducing carbon emissions across manufacturing cycles? Perhaps by minimizing transportation, or as you already touched on a bit, reusing waste materials. Yes, to all of those. That's a really a loaded question, but a good question. Inherently, there's a lot of. Discussion on an additive manufacturing being more sustainable anyway, just because you technically use less material as opposed to taking a huge block of material and carving away what you don't need. Theoretically, with additive manufacturing, you're only using material that you do need to make.The final part in terms of minimizing carbon emissions. There's make the process more energy efficient, and a lot of that comes with modeling. So, my group does a lot of process modeling, materials modeling. You can sort of compare that to the weather models that you see on TV with the forecast. It's taking historical data, it's taking current data points, and it's predicting what the forecast will be.

That's what we do with our models. We're taking some existing properties, maybe what's the chemical composition of the material. We're able to put in material processing parameters and predict what those final properties are. In order to make the process more efficient rather than guessing and checking, trying all different processing temperatures and pressures and gas materials, we're able to model and predict what we think will be the best, and then just print once. So that's one definite way of reducing carbon emissions and that. Also falls into the category of reusing waste materials. We can understand which materials we can reuse. Again, we understand those material properties from the material science work that we did and put that into the model. Then also to predict what those final properties will be.

Colleen: I heard the term once when someone was asked, well, what is advanced manufacturing? It's not your grandfather or your grandmother's manufacturing, and we think of the big. Coal smokestacks and the soot, et cetera. So advanced manufacturing in many ways could also be looked at as clean manufacturing or cleaner manufacturing. Would that be accurate?

Danielle: Cleaner, for sure, absolutely. And that's the goal is to make it clean. And in some industries are absolutely there. Others are working on it. But that's exactly our goal, is to make it more efficient. And by making it more efficient, it's certainly making it cleaner.

Colleen: You have a big lab. I've been in there many times. A lot of students are working in there. Are you hiring working with students from undergrad straight through our PhD program? 

Danielle: Yes, absolutely. And we even have a couple high schoolers during the summer that come in. It is. Wonderful to get them exposed to this. And again, all of those levels. So, we do have few high school students, undergrads, graduate postdocs, research professors. We're exposing all of these young scientists to real world problems. And that's one thing that WPI does well and that I think our lab is a. Helping with that for sure. We're exposing them to the scientists in the government in NSF and in all these funding agencies in companies and industries, national labs, that they're getting to work with one-on-one, truly on a daily basis. They're acting as teammates, which is a wonderful experience for them, great exposure, and it gives them a true leg up on competition Who doesn't have that experience in the real world. They're going to come out with their degree, whichever degree it is, already having this real-world experience. 

Colleen: Do you feel as though employers, those that you've spoken with, understand when someone is coming out of your lab or a lab here at WPI and it's on their resume, that they weren't just there observing? These students actually had hands-on input in these research projects. 

Danielle: Yeah, absolutely. And the best way they discover that is having a conversation with the students. You can just hear it in their voice. They're so excited to talk about what they did. They have real world examples. Even their vocabulary is different than the vocabulary of a student who only learned something theoretically. Right. They have a different way of looking at things, a different way of articulating them. Presenting their research. All of these students they're embedded with each other and there's always someone more experienced than them in the lab. And that just gives them a wonderful opportunity to learn so much inherently and naturally.

And I think in a fun way, I think we have a, a really good group and really good dynamics. So, they're just exposed to that and that's their norm. When they get out in the real world, they realize how special that is. 

Colleen: Can you give some examples of how you're training the next generation of engineers and material scientists and Yes, through that hands-on, but actually what materials they're working with, what projects beyond rubble to rockets they're working on in your lab?

Danielle: Yeah. A lot of the programs we have are based on sustainability in some form or another. Again, a lot of the work that we do is modeling involved, so then they're taking more of that fundamental chemistry background, math background, computational background, programming background, and they're coupling all of that. Again, with WPIs true interdisciplinary degrees. It's a great example of all the backgrounds that you need. Using models in a lot of our work to guide what we do, again, to make it more efficient. That's one of our big goals Also. In other sustainability efforts, looking at ways we can make these advanced manufacturing processes and the two additive processes that we have in my lab make those more efficient. And because we're in a university lab, we have the luxury of just tinkering and seeing what happens. But then we also have the real-world examples or the real-world applications where funding agencies want us to solve a problem or find the bigger picture. So, we really get to look at everything, which is a great exposure for them too.

Colleen: With the understanding that so much is changing and will change with technology, what should young professionals be focusing on in your opinion? 

Danielle: That's also a loaded question. I think getting all of them, yes you are. I think getting as much as they can or getting exposed to as many different technologies and things as possible. Staying current. Don't be afraid of technology. Don't be afraid of the new thing. AI to some is very daunting to others. It's. A crutch and you want to be somewhere in the middle where you're focused on it, you're fluent in it, and you stay current. I think that's going to be the biggest thing. That being said, the professor in me is also going to harp on understanding the fundamentals, right? Those fundamentals are not going anywhere. You will still need to know calculus, you will see, need to know chemistry, so don't gloss over those because there are maybe cooler, newer programs and courses out there. It's still really important to understand the basics. Once you have those building blocks, you can do anything.

Colleen: Keeping the crystal ball out there, the future outlook, what breakthroughs or new capabilities do you predict for advanced manufacturing for the next five to 10 years? And will AI be even more a part of it? 

Danielle: I think AI will continue to be part of whatever we do. I think. It will be for the better in that I do believe that we can become more efficient, and again, by becoming more efficient, it takes less time, takes less material, things could cost less. So that's maybe my hope. Maybe not the crystal ball, but my hope is that we can do more with less. That would be my goal for the future in general, not even five to 10 years. 

Colleen: As we're wrapping up, what's one thing you wish more people understood about how material science can reshape our world?

Danielle: A little cliche, but we say materials are everything and they truly are everything. So, it's a wonderful discipline. Understanding, it truly enables us to make the world a better place. 

Colleen: Danielle, you answered so many of my questions and gave me so much information. I hope for our listeners as well have a better understanding of advanced manufacturing and I want to thank you. I think you've been called the material girl in the past, so I am going to bring that back up. The material girl. Danielle, Cote, thank you so much for being on this podcast.

Danielle: It really was a pleasure. Thanks for having me, Colleen.

Colleen: That's it for today's conversation on Advancing Advanced Manufacturing. Another thank you to our guest, professor Cody, for sharing valuable insights into the future of how we design build. And rethink the materials and processes that shape our world. At WPI, advanced manufacturing is more than just a research focus.

It's part of our commitment to solving real world problems with several renowned faculty experts and researchers driving innovation. WPI plays a leading role in shaping this field. We're proud to be a member of 10 manufacturing USA, innovation institutes, connecting industry, academia, and federal partners to tackle national challenges.

Boost economic growth and strengthen US competitiveness and security. To learn more about advanced manufacturing at WPI, visit wpi.edu and search Advanced Manufacturing. To find more WPI podcasts, go to wpi.edu/listen. You can also find us on Spotify, apple and YouTube podcasts. This episode was recorded at the WPI Global Lab with help from PhD candidate Varun Bhat.

Thanks for listening, and we'll see you next time.