Hewlett Packard Enterprise Data Science Institute

Key Takeaways

• The University of Houston is leading a multidisciplinary coalition backed by a $2.88 million Department of Energy grant to discover and synthesize next-generation permanent magnets using advanced artificial intelligence.
• The project aims to protect U.S. economic and national security by finding sustainable, domestically sourced alternatives to neodymium iron boride magnets that rely on foreign-controlled minerals.
• UH will use its state-of-the-art facilities to turn AI predictions into physical products, laying the foundation for a possible university-wide center.

University of Houston researchers are leading a multidisciplinary coalition leveraging artificial intelligence to design and manufacture next-generation permanent magnets, an effort aimed at securing the nation’s domestic supply chain for advanced energy and industrial technologies.

Funded by a $2.88 million grant from the U.S. Department of Energy’s Advanced Research Projects Agency-Energy, the research project seeks to develop new magnets that reduce American reliance on supply-vulnerable foreign sources by finding alternatives to "critical minerals" — the raw materials essential to U.S. economic and national security.

The grant is part of a $100 million initiative from the DOE to support early-stage research and development projects aimed at boosting domestic magnet manufacturing and critical mineral production.

The UH-led team aims to surpass the properties of neodymium iron boron, the current industry-standard material for high-performance permanent magnets, which are vital components in electric vehicles, industrial motors, generators, electronics and other advanced technologies. They also play a critical role in modern heating and cooling systems.

“Strong magnets are used all over our economy. For example, many modern air-conditioning systems rely on permanent-magnet motors to drive compressors and blower fans,” said principal investigator Jakoah Brgoch, the Eby Nell McElrath Professor of Chemistry at UH. “This has been a longstanding challenge to think about how we replace these magnets with high-performing and more reliable materials, and optimization by just replacing elements is not working. Our goal is to use AI to find entirely new materials while simultaneously balancing these supply constraint concerns.”

Supply chains for neodymium-iron-boride magnets are heavily concentrated overseas, so the federal grant will support UH researchers in their effort to discover sustainable, alternative materials that can be sourced and manufactured more reliably within the U.S.

Meet the Coalition

Over the three-year grant period, Brgoch will head Guided AI for Magnetic Boride/Carbide Intermetallic Technologies (GAMBIT). The multidisciplinary research coalition includes UH Assistant Professor Joshua Bocarsly, alongside scientists from Rice University, Colorado State University, Houston-based startup Newfound Materials and Carrier Global.

"Our goal is to use AI to find entirely new materials while simultaneously balancing these supply constraint concerns.”

— Jakoah Brgoch, UH professor and principal investigator

To accelerate discovery, the GAMBIT team is pairing predictive AI with synthetic validation. AI prediction systems will identify millions of atomic compounds likely to have ideal magnetic capabilities, while a separate AI system will predict the most probable and efficient chemical pathways to actually create the material in a lab.

UH’s role in this project is twofold: researchers will not only help predict viable compounds but also physically synthesize these materials and use the University’s new Advanced Magnetic Characterization Facility to test the results.

“A big bottleneck in discovering new magnets has been finding ways to quickly and accurately measure all these new materials we are making in the labs,” Bocarsly said. “We are excited that this program gives us the opportunity to expand our magnetic characterization facilities at UH, building a data-driven pipeline all the way from prediction to synthesis to validation.”

Because ARPA-E focuses on translation to the commercial market, the project’s ultimate milestone is commercialization through a new startup or expanding Newfound Materials’ business units to bring these magnets to market.

This research is aligned with UH's Advanced Materials and Manufacturing research priority area. Brgoch has also been leading university-wide efforts to create a center that integrates AI-guided design, which can be applied to other fields, such as quantum materials and catalysis.

"This grant is a significant step toward developing a center for intelligent material design and synthesis, and we are looking forward to continuing to build in this area," said Claudia Neuhauser, vice president of research at UH.

In February, Brgoch was among seven UH honorees named a Senior Member of the National Academy of Inventors. NAI Senior Members are faculty, scientists and administrators who have demonstrated innovation with the potential for meaningful societal impact, along with success in patents, licensing and commercialization, and a commitment to mentoring future inventors.

Vedhus Hoskere, the Kaspar J. Willam Assistant Professor of Civil and Environmental Engineering at the University of Houston, has received a five-year, nearly half-million-dollar Faculty Early Career Development Program award from the U.S. National Science Foundation (NSF) to develop new ways for engineers and artificial intelligence to collaborate in the design and assessment of resilient civil infrastructure systems.

The project, “BRACE-CI: Building Resilience through Human-AI Co-Engineering Cyberinfrastructure,” is supported through NSF’s CAREER program — the foundation’s most prestigious award program for early-career faculty. The program recognizes researchers with the potential to become academic leaders through the close integration of research and education.

As infrastructure systems become more complex and communities face growing exposure to natural hazards, their design and assessment increasingly require coordination among architects, engineers, contractors and other specialists. Yet these teams often work across disconnected drawings, photographs, engineering analyses and 3D models, making coordination difficult, introducing inconsistencies and limiting the alternatives they can explore.

BRACE-CI will investigate a human-centered alternative in which engineers work alongside AI agents within a shared cyberinfrastructure. These agents will connect project information, support the creation and revision of engineering models, identify inconsistencies and help teams compare alternatives, while human experts retain responsibility for defining objectives, reviewing results and making final decisions.

“The goal is to give civil engineers capable autonomous assistants,” Hoskere said. “By reducing the effort required to move between disconnected drawings, models and analyses, we can help engineering teams explore more alternatives within project timelines, recognize potential problems earlier and devote more attention to the decisions that require human creativity and judgment.”

“I am deeply grateful to NSF’s Office of Advanced Cyberinfrastructure for supporting this vision. We are excited to uncover foundational principles for engineer—AI collaboration and pioneer new paradigms in service of safer, more resilient communities.”

Hoskere directs UH’s Structures and Artificial Intelligence Lab, where his research combines artificial intelligence, computer vision and robotics with structural engineering and infrastructure assessment. The CAREER project builds on that interdisciplinary foundation while expanding the focus from AI-assisted inspection to AI-supported engineering design and decision-making.

The project will also examine how engineers can establish appropriate trust in AI collaborators.

“Engineering applications require more than an AI system that can produce an answer,” Hoskere said. “The system must help users understand where the answer came from, recognize when information is missing and incorporate engineering principles, standards and human feedback throughout the process.”

Research and education will be closely integrated. Undergraduate and graduate students will participate in developing and evaluating the cyberinfrastructure, and findings from the project will be introduced into engineering courses and professional workshops. The educational activities will emphasize both the capabilities and limitations of AI, preparing students to use emerging technologies responsibly while remaining accountable for engineering decisions.

“Students entering the profession will increasingly work with intelligent systems,” Hoskere said. “We want to prepare them not simply to operate AI tools, but to question their outputs, connect them to physical principles and use them responsibly to create safer and more resilient communities.”

Hoskere expressed gratitude to those who have played an instrumental role in his academic journey.

“This award reflects the guidance, collaboration and support of many people throughout my career,” Hoskere said. “I am deeply grateful to my mentors, Billie F. Spencer Jr. at Illinois and Craig Glennie at UH; to Chair Roberto Ballarini, Dean Pradeep Sharma and my colleagues in UH Civil and Environmental Engineering; and to my academic and industry collaborators. At the heart of this work are the students and researchers in the Structures and Artificial Intelligence Lab, whose creativity and dedication make it possible.”

“Above all, I am grateful to my wife for her unwavering love and support, and to our son, whose joyful presence makes every achievement more meaningful.”

On May 29, the Hewlett Packard Enterprise Data Science Institute hosted the AI for Accelerating Discovery Workshop. The event brought together over 50 researchers, creators and innovators from across the University of Houston to explore how artificial intelligence can transform research and creative practices.

Framing the Opportunities: AI Across Disciplines

The workshop aimed to close the gap between "user" domains and "developer" domains in an effort to leverage the University’s unique strengths across creative and scientific fields.

The afternoon kicked off with a networking lunch, followed by presentations from faculty representing six UH colleges that delivered insights into specific areas of inquiry. Speakers highlighted groundbreaking AI applications already taking root and opportunities for further research collaboration. Presenters introduced projects in laboratory data management, qualitative analysis, photonic device development, RNA delivery, medication adherence, superconductivity and other emerging frontiers for innovation.  

“Research and creative work at UH is incredibly wide-ranging,” said Claudia Neuhauser, UH’s vice president/vice chancellor for research and director of the HPE Data Science Institute. “There’s real opportunity for advancing this work by connecting faculty to expertise beyond their own domains, and AI is proving to be an incredible catalyst for helping to break down traditional technical barriers.”

Turning Ideas into Action: Seed Grants for Interdisciplinary Teams

During the hands-on teaming session, participants broke out into cross-disciplinary tables to brainstorm, pitch ideas and start conversations with peers outside of their departments.

Facilitators guided these discussions to help researchers find complementary skill sets, matching domain experts with AI and machine learning developers to tackle complex, real-world problems.

To support the promising interdisciplinary teams that emerged from these discussions, HPE DSI will offer seed grants to jumpstart collaborative research projects.

For more information on upcoming workshops and resources, visit https://hpedsi.uh.edu/news-events. 

With more people using artificial intelligence tools like ChatGPT, C. T. Bauer College of Business researchers have found that middle-class workers may be the most receptive to incorporating the tool on the job. 

The rise of large language models (AI models including ChatGPT) have led people to ask what they mean for society, and what benefits they offer, explained Professor and Endowed C. T. Bauer Chair of AI Meng Li. These questions are part of the thought process behind Li’s research, which looks at workers’ social class backgrounds and how that impacts their adoption of LLMs in place of supervisor assistance. 

“We already understand that AI tools, ChatGPT, self-driving cars — they are not going away,” Li said. “They are going to be there regardless of if we like it or not, so just answering this question will be critical for our society.”

In their quest to see the relationship between social classes and adopting AI instead of getting help from supervisors, researchers did large scale surveys and behavioral experiments. This included early career professionals from various social class backgrounds.   

The paper, co-authored by Li, Bauer Ph.D. student Yao Yao and Boston College Assistant Professor Lai Wei, defines “early career” as workers with less than two to three years of experience. This group was selected because of their typical reliance on their supervisors, and because their relatively standardized current social class allows for more context to examine their social class background. 

The research insights found that middle-class workers are more willing to use LLMs instead of asking their supervisor for help compared to their lower-class and upper-class peers. 

“For the upper class, they are comfortable to talk to humans,” Li said. “They have the resources. For the lower class, they don't have the literacy or the knowledge of large language models. So, it turns out the middle class is more willing to adopt AI tools such as large language models.”

The results could be seen as an inverted U-shaped pattern and bring a light to the middle-class workers. The middle-class group stood out because they were most inclined to use the LLMs in this way. 

“They have the knowledge,” Li said. “They know how to use it. They know how the large language model can help them, or they are comfortable with technology. I think this unique advantage makes their adoption easier.” 

Li says it’s important to understand that LLMs impact people differently. 

“Trying to help the people who are not adopting AI, or have the need to, like the lower class, but don't know how to use it,” Li said. “I think finding a way to help them will be important.” 

Moving forward, how these dynamics will impact workplace inequality is a question the paper says is still up for future research. 

The next step to continue advancing research on how AI impacts the workplace is an exploration of how these dynamics may impact workplace inequality, Li said.