Computing the future: Inside the NSF CyberTraining Quantum Computing for Materials Science and Chemistry Summer School

Despite the incredible advancements in computing over the past several decades, some scientific problems remain beyond the reach of even today’s most powerful supercomputers. 

As conventional computers approach the physical limits of their processing power, researchers are turning to quantum computing; a fundamentally different approach that harnesses the behavior of atoms and molecules to solve problems that would be nearly impossible for classical computers. 

Unlike traditional computers, which process information using bits that exist as either 0 or 1, quantum computers use quantum bits, or qubits. Qubits can exist in multiple states simultaneously; instead of storing a 0 or 1, they can store a 0, 1, or both at the same time. This capability makes quantum computers especially suited for modeling molecules and materials, which opens possibilities for advancement in chemistry, materials science, and other fields. 

Earlier this summer, Houlong Zhuang, an associate professor in the School for Engineering of Matter, Transport and Energy, helped host the NSF Quantum Computing for Materials Science and Chemistry Summer School, a program designed to introduce undergraduate and graduate students to this rapidly emerging field. 

Supported by a National Science Foundation CyberTraining grant, the workshop brought together students from universities across Arizona for lectures, hands-on tutorials and collaborative research activities led by experts in quantum computing. 

“This workshop is the main event of our CyberTraining grant that we have been planning for almost the entire year,” Zhuang says. 

The summer school is a collaboration between ASU and Purdue University, with Purdue hosting the inaugural workshop last year. Bringing the event to ASU expanded quantum computing education in Arizona, giving students opportunities to interact with researchers from academia and industry. 

The workshop was organized through a collaborative effort between faculty and staff from both universities. Zhuang worked alongside Purdue University professor and co-principal investigator David Liu. Additional contributions came from ASU co-principal investigator Douglas M. Jennewein, while Marisa Brazil and Torey E. Battelle contributed instructional content, with Battelle giving a virtual presentation to participants. 

Bridging quantum computing with engineering

Planning for the workshop began months in advance through biweekly meetings between faculty from ASU and Purdue. Together, they developed a curriculum that balanced theoretical concepts with practical applications, allowing students to explore how quantum computing can address real-world problems in materials science, chemistry, and engineering. 

Behind the scenes, numerous staff members helped ensure the program ran smoothly. Amber Carlson coordinated the conference venue and catering, while Lorie Diller and April MacCleary managed logistical and financial arrangements, including hotel accommodations and participant reimbursements.

For Zhuang, one of quantum computing’s greatest strengths is its ability to model electron behavior, allowing researchers to better understand why materials behave the way they do. 

“If we can simulate electron behaviors, then we can predict material properties before they are made in the lab,” Zhuang says.

Those simulations could help scientists identify the most stable atomic structures before materials are physically synthesized, accelerating the development of next-generation batteries, semiconductors and other advanced technologies. Similar algorithms are also being explored to study how drug molecules interact with proteins, advancing the discovery of new medicines and pharmaceuticals. 

Although quantum computers are decades away from being perfected, Zhuang believes researchers can already benefit from combining classical computing with quantum algorithms and artificial intelligence. 

“You can use classical computing to generate some parameters that can be used to control the operators and gates in quantum computers,” Zhuang says. “Combining the advantages of both systems, and implementing them with machine learning, is really beneficial to many research domains.”

He believes introducing students to these technologies now will prepare them for a career in this rapidly emerging field.

“It’s almost equivalent to students needing to have a very solid understanding of artificial intelligence,” Zhuang says. “It’s extremely important for students to learn quantum computing prior to graduation.”

Building the quantum workforce

Each morning of the summer school featured presentations from researchers in academia and industry, including SEMTE professor Terry Alford, who discussed the role of quantum computing in the semiconductor industry. Other sessions introduced students to quantum machine learning, computational chemistry and quantum computing platforms before the afternoon sessions shifted to hands-on learning. 

Participants then formed interdisciplinary teams with students from different universities to develop research projects inspired by the school’s lessons. 

For Zhuang, those student presentations became the highlight of the workshop. 

“Watching students from very different backgrounds who hadn’t learned about quantum computing before come up with very good ideas was my favorite part of the workshop,” Zhuang says.

A student who had previously taken Zhuang’s finite element analysis course proposed a way to connect concepts from that class with quantum computing. 

“The idea sounds really, really good,” Zhuang says. “Quantum computing is for everyone. It’s not limited to where you are right now, no matter whether you are a sophomore or senior Ph.D. student.”

The presentations reinforced the primary goal of the workshop: quantum computing is accessible to students regardless of their discipline or experience. 

Beyond teaching technical skills, the workshop was designed to spark long-term interest in quantum computing. 

“We want to train students so when they graduate, they have enough understanding to potentially pursue careers in that area,” Zhuang says. “I think that’s our purpose – to stimulate interest in the students.” 

According to Zhuang, one participant was so inspired by the workshop she began sharing what she learned about quantum computing on LinkedIn, an encouraging sign that the program had succeeded in sparking curiosity beyond the classroom. 

As the interest in quantum technology continues to grow, ASU is expanding its effort through participation in the Phoenix Quantum Initiative, led by ASU Professor Sethuraman Panchanathan. The initiative aims to strengthen Arizona’s leadership in quantum research and semiconductor innovation, creating new opportunities for students and researchers.