University Partnerships, Self-Driving Laboratories, and Helping Airports Meet Growing Energy Demands

In this episode of Peaks to Power, learn about:  

• Two Memorandums of Understanding the National Laboratory of the Rockies signed with the University of Utah and the Colorado School of Mines 
• Two researchers working to create self-driving laboratories using artificial intelligence and robotics  
• NLR’s Aeroportal web platform helping airports manage increase infrastructure and energy demands.  

This episode was hosted by Kerrin Jeromin and Taylor Mankle, written and produced by Allison Montroy, Hannah Halusker, and Kaitlyn Stottler, and edited by Taylor Mankle, Joe DelNero, and Brittany Falch. Graphics are by Brittnee Gayet. Our title music is written and performed by Ted Vaca and episode music by Chuck Kurnik, Jim Riley, and Mark Sanseverino of Drift BC. Peaks to Power is created by the U.S. Department of Energy’s National Laboratory of the Rockies in Golden, Colorado. Email us at podcast@nlr.gov. Follow NLR on X, Instagram, LinkedIn, YouTube, Threads, and Facebook.  

Transcript

Taylor Mankle 0:04

Welcome to Peaks to Power, a podcast brought to you by the U.S. Department of Energy's National Laboratory of the Rockies. It's Wednesday, May 20th. I'm Taylor Mankle.

Kerrin Jeromin 0:14

And I'm Kerrin Jeromin, and we are your hosts.

Taylor Mankle 0:17

And we're back again.

Kerrin Jeromin 0:19

Yeah, we are. All right. And really at a very busy moment for the lab. While the podcast relaunch might be the most exciting recent event, in my opinion, a lot has been happening at the National Laboratory of the Rockies over the past month or so, like hosting the annual Industry Growth Forum and Partner Forum.

Taylor Mankle 0:37

Yeah, no kidding, and today's stories give you insights into those big events, as well as linking AI and materials research and helping airports plan for the future.

Kerrin Jeromin 0:55

All right, Taylor, let's kick off this episode with a visit from two universities that resulted in some momentous partnerships.

Taylor Mankle 1:03

And a memorable ceremony, if you will.

Kerrin Jeromin 1:06

I I think I heard some emphasis there. Am I understanding your reference? Ha ha ha. We got jokes for days, friends.

Taylor Mankle 1:13

B ut if you couldn't catch on, we're talking about the memorandums of understanding that NLR signed with the Colorado School of Mines and the University of Utah.

Kerrin Jeromin 1:24

That's right. Commonly known as MOUs, these declarations of future partnerships, collaboration, and shared goals could help with critical minerals innovation, commercialization, and workforce development.

Taylor Mankle 1:37

The MOUs were signed on May 4th, just before the lab hosted its annual partner forum.

Kerrin Jeromin 1:42

Which this year happened to focus on building resilient domestic mineral supply chains for energy systems.

Taylor Mankle 1:48

The MOUs help with that focus by enabling integrated research and facility sharing.

Kerrin Jeromin 1:54

They will support scaling critical mineral innovations from concept to commercialization.

Taylor Mankle 1:59

As well as building pipelines for educating and training a highly skilled domestic workforce.

Kerrin Jeromin 2:05

Now, this isn't the first time the School of Mines has teamed up with the lab. This MOU builds on an energy research partnership that extends back, get this, more than 50 years.

Taylor Mankle 2:14

But this new partnership will involve two new facilities. The first being the lab's upcoming EMAPS facility.

Kerrin Jeromin 2:22

That's right. EMAPS stands for Energy, Materials, and Processing at Scale Facility, in case you were wondering what that acronym stands for.

Taylor Mankle 2:30

And the second facility is the School of Mines' Critical Minerals Innovation and Commercialization Hub, which is a newly acquired 50,000 square foot laboratory and high bay research facility near its campus in Golden, Colorado.

Kerrin Jeromin 2:46

Meanwhile, the memorandum of understanding that was signed with the University of Utah will promote research and technology development for critical minerals, advanced materials, and manufacturing through AI-enabled science workflows, high-performance computing, and data science. It's pretty high-tech stuff, Taylor.

Taylor Mankle 3:03

Yeah, and it also aims to boost education and workforce development through academic programs, internships, and career opportunities connected to the national laboratories.

Kerrin Jeromin 3:13

Ultimately, these MOUs build on the lab's momentum in critical minerals, materials, manufacturing, and advanced computing capabilities while collaborating with great university partners.

Taylor Mankle 3:52

Alright, Kerrin, tell me. Have you tried one of those self-driving cars yet? I've been seeing more and more pop up around these parts in Colorado.

Kerrin Jeromin 3:52

 I admit I'm a little hesitant. It's futuristic to think about. I would love to but I just haven't gotten there yet .

Taylor Mankle 3:52

Yeah, no kidding. And just like self-driving cars that utilize artificial intelligence to get from point A to point B, scientists at NLR are using a similar concept to create what they call self-driving laboratories.

Kerrin Jeromin 4:08

Ooh, interesting. Artificial intelligence is really the key here. By using AI, scientists are automating sets of laboratory tasks to increase the speed, precision, and throughput of our materials research.

Taylor Mankle 4:21

Now the goal here is to speed up routine experimentation to achieve scientific breakthroughs faster.

Kerrin Jeromin 4:27

So far, the lab has started testing this automated manufacturing process for two technologies: thin film semiconductors and catalytic nanomaterials. We'll explain more about what these are shortly, so stick with us.

Taylor Mankle 4:41

These two case studies are forming the foundation for a framework that could help a lot more researchers across the lab move towards self-driving experimentation.

Kerrin Jeromin 4:50

Frederick Baddour, a senior chemist in NLR's bioenergy program, is leading this work alongside senior research fellow Joey Luther. Baddour points out that unlike general-purpose chatbots, AI co-pilots in the scientific domain have an exceedingly small data set to draw from.

Taylor Mankle 5:07

In order for AI to drive innovation in scientific domains, it has to overcome the major hurdle that is the lack of any significant volumes of high-quality, reproducible, domain-specific data.

Kerrin Jeromin 5:19

Baddour hopes to fill this gap and generate the data necessary to drive innovation AI applications in the physical sciences.

Taylor Mankle 5:27

Okay, so we mentioned one of the case studies being semiconductor film manufacturing. Let's dive into that a bit more.

Kerrin Jeromin 5:35

Yes, let's. So semiconductor films can be found in various electronic devices. They're useful for light absorption and energy conversion.

Taylor Mankle 5:43

And it can be tough to replicate this process of manufacturing semiconductor film perfectly, time and time again. But AI can help robotics perform repetitive tasks like this with precision and speed.

Kerrin Jeromin 5:57

For example, scientists might want to study the effects of different temperatures, curing times, solvents, precursors, and concentrations on the growth of semiconductor films. Evaluating just three different conditions for each of these variables could result in hundreds of separate experiments. The self-driving lab can accomplish these types of routine experiments without human intervention, fatigue, or variation.

Taylor Mankle 6:22

And in the other case study on catalytic nanomaterials, NLR scientists reimagined a flow chemistry setup that could be accomplished without human intervention. Here's a great example. Think of a Roomba or self-driving vacuum cleaner. Instead of making a human-shaped robot that can push a vacuum cleaner, engineers totally rethought how to accomplish the task of vacuuming with a different shape of robot. That's what our researchers did here to speed up their manufacturing process.

Kerrin Jeromin 6:53

Very, very clever. Eventually, researchers think AI-powered robotics could form a closed loop where humans point to an area or piece of research that needs to be explored and computers perform their own experiments.

Taylor Mankle 7:07

That would allow AI to become a research co-pilot and help AI systems move beyond their training data and assist in scientific breakthroughs.

Kerrin Jeromin 7:16

Already, Luther and Baddour have been able to acquire, process, and analyze data much faster, sometimes thousands of times faster. Now they're turning their focus to make adoption across the laboratory a reality. Okay, Taylor, any good travel plans coming up for you?

Taylor Mankle 7:39

Nothing crazy, but a couple flights coming up this summer, which feels routine at this point.

Kerrin Jeromin 7:46

That's good. Hopefully, somewhere fun. Well, you know, air travel is a big part of many of our lives, and with millions of passengers moving through U.S. airports every day, it's a pretty big deal.

Taylor Mankle 7:56

Yeah, air travel continues to grow every year.

Kerrin Jeromin 7:59

More travelers means more demand on key energy infrastructure, but airports also need to keep operating costs at manageable levels.

Taylor Mankle 8:07

And most airports are seeking ways to stay competitive, reduce fuel and operating costs, and keep up with regional consumer demand.

Kerrin Jeromin 8:16

All while maintaining smooth, reliable operations.

Taylor Mankle 8:19

That's a lot of pieces and parts that need to fit together into a cohesive, tailored, and cost-effective system that doesn't create unnecessary waste or expenses.

Kerrin Jeromin 8:29

Which is why it's important airports have a system that is sized and structured correctly from the start. And that is where an NLR web platform called Aeroportal can come in. Through the Aeroportal, researchers with the U.S. Department of Energy's Athena project, which is led by NLR, are helping airports plan for future energy demands more confidently by providing advanced modeling and AI tools that can be customized for their specific needs.

Taylor Mankle 8:55

The Aeroportal's computational models were built using data from more than 300 airports and the lab's supercomputer. These models are now available to plan out needs for rental cars, ground support equipment, and rideshare vehicles.

Kerrin Jeromin 9:11

And it helps airports confirm that their energy infrastructure plans can meet their goals. They can model their plans before they put down any money for new equipment and infrastructure.

Taylor Mankle 9:22

The Athena Project's group of 14 airport stakeholders nationwide got a sneak peek at the Aeroportals models in late 2025.

Kerrin Jeromin 9:31

Now, an agentic AI assistant named Amelia can also help airports navigate all the details of planning for new airport energy infrastructure using a chat interface. How about that?

Taylor Mankle 9:43

Yeah, now all you have to do is type in your questions or requests, and Amelia can walk you through the answer, running models, comparing scenarios, interpreting results, and providing recommendations.

Kerrin Jeromin 9:55

Salt Lake City International Airport has also consulted with the Labs Athena team for help with their ground support equipment charging schedule and fleet composition.

Taylor Mankle 10:05

Demand at airports continues to grow, and the Aeroportal helps manage increasing pressure on energy and transportation infrastructure.

Kerrin Jeromin 10:13

So that we travelers can keep taking to the skies. Well that wraps up another episode of Peaks to Power. Make sure to look for us on your favorite podcast feed.

Taylor Mankle 10:17

 We'll catch you in two weeks with more news from the National Laboratory of the Rockies. This episode was adapted from National Laboratory of the Rockies news articles from April and May 2026 written by Brooke Van Zandt, Anna Squires, and Aishwarya Krishnamoorthy. Our theme music is written and performed by Ted Vaca, and episode music by Chuck Kurnick, Jim Riley, and Mark Sanseverino of Drift BC. This podcast is produced by the National Laboratory of the Rockies Communications Office.